Computer Application

The modern growth in fabricate energy efficient Wireless Sensor Network is liberal a novel way
to systematize WSN in applications like surveillance, industrial monitoring, traffic monitoring,
habitat monitoring, cropping monitoring, crowd including etc. The rising use of these networks is
making engineers evolve novel and efficient ideas in this field. A group of research in data
routing, data density and in network aggregation has been proposed in recent years. The energy
consumption is the main apprehension in the wireless sensor network. There are many protocols
in wireless sensor network to diminish the energy consumption and to put in to the network
lifetime. Among a range of types of techniques, clustering is the most efficient technique to
diminish the energy expenditure of network. In this effort, LEACH protocol has been secondhand
for clustering in which cluster heads are nominated on the basis of distance and energy. The
LEACH protocol is been implemented in a simulated environment and analyze their performance
graphically.

Big data is collection of data which is vast range and composite data.. Data obtain created from each and every way, from various fields. These big data has structured semi-structured and unstructured kind of data. In today period data is been gathered on great scale. Social media sites, digital images and videos and countless other. Entire world is going so as to near the digitalization. All this kinds of data is well known as big data. Data mining is a process for uncovering a design which is convenient from huge scale data sets. We gather the healthcare information which comprise all the particulars of the sufferer, their symptoms, ill health etc. Formally we gather the information then there will be pre-managing on that information as we require only strain information for our study. Convenient and significant data can be withdraw from this big information with the assist of data mining by managing on that data. The data will be saved in Hadoop. User can access the data by symptoms, disease etc.

big data can bring huge benefits to businesses of all size. However, as with any business project, proper preparation and planning is essential, especially when it comes to infrastructure. Until recently it was hard for companies and organizations to get into big data without making heavy infrastructure investments (expensive data warehouses, software, analytics staff, etc.). But times have changed. Now cloud computing has opened up a door to the companies to avoid investing lot of money for infrastructure.

In logistics, software aids for transportation planning and scheduling are often based in approximations and abstractions that do not take into account real-world data. The aim of this work is to provide an analysis and methodology, based on real-world data, on how to obtain probability density functions for prediction of activity duration. Such information can be used in planning algorithms, like vehicle routing problem, capable of dealing with stochastic time-windows. Given a large spatio-temporal database of events, where each event consists of the fields event ID, time, location, and event type, the aim is to extract valuable information about activities duration. The process is not straightforward since the log is human-influenced creating uncertainty related with the time at which the events are logged. In order to overcome this, a novel framework is proposed: it uses the spatiotemporal trajectories to identify regions-of-interest based on speed, and builds an ROI activity time-line using the activities extracted from event logs. The framework’s ability to estimate activities durations was tested in three different environments: the Amsterdam Airport Schiphol, the Port of Rotterdam and a single vehicle scenario. Experimental results validate the usefulness of the approach at finding probability density functions for prediction of activity durations at specific locations.

This paper presents a general framework for planning the quasi-static motion of climbing robots. The framework is instantiated to compute climbing motions of a three-limbed robot in vertical natural terrain. An example resulting path through a large simulated environment is presented. The planning problem is one of five fundamental challenges to the development of real robotic systems able to climb real natural terrain. Each of the four other areas—hardware design, control, sensing, and grasping—is also discussed. Keywords Motion planning, climbing, robotics, legged robots, high-risk access, natural terrain.

Enterprise Resource Planning (ERP) systems have become a de facto standard for integrating business functions. But an obvious question arises: if every business is using the same so-called ―Vanilla‖ software (e.g. an SAP ERP system) what happens to the competitive advantage from implementing IT systems? If we discard our custom-built legacy systems in favour of enterprise systems do we also jettison our valued competitive advantage from IT? While for some organisations ERPs have become just a necessity for conducting business, others want to exploit them to outperform their competitors. In the last few years, researchers have begun to study the link between ERP systems and competitive advantage. This link will be the focus of this paper. We outline a framework summarizing prior research and suggest two researchable questions. In conclusion, we present some initial findings from two empirical case studies derived from part of the European food industry.

Cloud computing is growing in popularity due to its ability to offer dynamically scalable resources provisioned as services regardless of user or location device. However, moving data to the cloud means that the control of the data is more in the hands of the cloud provider rather than the data owner. This is a great challenge that continues to hinder cloud computing from successfully achieving its potential. This is due to the fact that with cloud computing, the storage and processing of private information is done on remote machines that are not owned or even managed by the cloud consumers. This brings about significant security and data privacy concerns that impede the broader adoption of cloud computing, which compromises the vision of cloud computing as a new IT procurement model.

The Internet is fast becoming the de facto content delivery network of the world, supplanting TV and physical media as the primary method of distributing larger files to ever-increasing numbers of users at the fastest possible speeds. Recent trends have, however, posed challenges to various players in the Internet content delivery ecosystem. These trends include exponentially increasing traffic volume, increasing user expectation for quality of content delivery, and the ubiquity and rise of mobile traffic. For example, exponentially increasing traffic—primarily caused by the popularity of Internet video—is stressing the existing Content Delivery Network (CDN) infrastructures. Similarly, content providers want to improve user experience to match the increasing user expectation in order to retain users and sustain their advertisement based and subscription-based revenue models. Finally, although mobile traffic is increasing, cellular networks are not as well designed as their wireline counterparts, causing poorer quality of experience for mobile users. These challenges are faced by content providers, CDNs and network operators everywhere and they seek to design and manage their networks better to improve content delivery and provide better quality of experience.

Automated platforms that conduct power line inspections need to have a vision system which is robust for their harsh working environment. State-of-the-art work in this field focuses on detecting primitive shapes in 2D images in order to isolate power line hardware. Recent trends are starting to explore 3D vision for autonomous platforms, both for navigation and inspection. However, expensive options in the form of specialized hardware is being researched. A cost effective approach would begin with multiple view geometry. Therefore, this study aims to provide a 3D context in the form of a reconstructed transmission pylon that arises from image data. To this end, structure from motion techniques are used to understand multiple view geometry and extract camera extrinsic. Thereafter, a state-of-art line reconstruction algorithm is applied to produce a tower. The pipeline designed is capable of reconstructing a tower up to scale, provided that a known measurement of the scene is provided. Both 2D and 3D hypotheses are formed and scored using edge detection methods before being clustered into a final model.

Neural networks are good at classification, forecasting and recognition. They are also good candidates of financial forecasting tools. Forecasting is often used in the decision making process. Neural network training is an art. Trading based on neural network outputs, or trading strategy is also an art. We will discuss a seven-step neural network forecasting model building approach in this article. Pre and post data processing/analysis skills, data sampling, training criteria and model recommendation will also be covered in this article.

Backing up and restoring enterprise applications (EAs) are essential operations that are usually done manually by an administrator or semi-automatically by tools. Backing up an enterprise application (EA) consists of backing up all its components together with the environments and operating systems in a consistent way so that the application can be restored and function properly later. There are many challenges for backing up and restoring EAs. This paper proposes a framework for automating the process of backing up and restoring EAs deployed in a cloud environment to ensure the continuous running of these enterprise applications and prevent the loss of data in case failure of applications

Smart phones are basic needs of our daily life. It’s like a small computer which gives you many facilities such as web browsing, downloading and many more but small data storage space and backup are major problem. On the other hand cloud computing provides efficient computational resources and secure data hosting services. But the data transmission among two secure networks is performed over unsecured network. So need a design to secure data transfer.

In new application areas of relational database systems, the join operator is used more than in conventional applications. We propose a simple data structure called join index, for improving the performance of joins in the context of complex queries. For most of the joins, updates to join indices incur very little overhead.

The significance of security devices that protect the numerous transactions, which take place in today‘s distributed virtual environment, cannot be underestimated. The importance of such devices will increase as our society continues to evolve into a cashless electronic society. The continuing increase in the number and size of electronic transactions, the advances in the technology utilized and the growing sophistication of the adversary have led to significant resources being invested in the evaluation and analysis of security devices. There has been a transformation of the traditional security analysis from one focused on mathematical primitives and physical engineering solutions to a holistic approach that seeks to protect against subtle interactions between the cryptographic, logical and physical aspects of such devices that can collude to compromise the security thereof.

This paper presents a principled approach to network redesign that creates more secure and manageable networks. We propose a new network architecture in which a global security policy defines all connectivity. The policy is declared at a logically centralized Controller and then enforced directly at each switch. All communication must first obtain permission from the Controller before being forwarded by any of the network switches. The Controller manages the policy namespace and performs all routing and access control decisions, while the switches are reduced to simple forwarding engines that enforce the Controller’s decisions.

Global energy requirements are continuously increasing. Conventional methods of producing more energy to meet this growth pose a great threat to the environment. CO2 emissions and other bi-products of energy production and distribution processes have dire consequences for the environment. Efficient use of energy is one of the main tools to restrain energy consumption growth without compromising on the customer’s requirements. Improving energy efficiency requires understanding of the usage patterns and practices. Smart energy grids, pervasive computing, and communication technologies have enabled the stakeholders in the energy industry to collect large amounts of useful and highly granular energy us-age data. This data is generated in large volumes and in a variety of different formats depending on its purpose and systems used to collect it. The volume and diversity of data also increase with time. All these data characteristics refer to the application of Big Data.

In this paper we will confer about ad hoc networks for multipath routing. An ad hoc network is a compilation of wireless mobile nodes vigorously forming a
temporary network without the use of any existing network infrastructure or centralized administration.

In this paper we will discuss about different issues of multipath routing protocol for mobile ad hoc networks. Multi-path routing represents a shows
potential routing technique for wireless mobile ad hoc networks. Multi-path routing attains load complementary and is more flexible to route failures.
Recently,various multi-path routing protocols have been planned for wireless mobile adhoc networks; apart from this routing is a major issue in ad hoc
networks,different issues are associates with multipath routing protocol.

Abstract - Tasks assignment in grid computing is a challenge
for most researchers and developers of these types of systems.
This is due to characteristics inherent to grid infrastructures,
namely, heterogeneity, dynamicity and scalability. It becomes
much more complex when it comes to assign tasks with
precedence constraints represented by a Directed Acyclic Graph.
The task assignment problem is well known to be NP-complete.
In this paper, we present and evaluate a dependent task
assignment strategy for Grids. Our goal is two folds: first we
reduce, whenever possible, the average response time of tasks
submitted to the grid, and secondly, we reduce the transfer cost
inducing by the tasks transfer respecting the dependency
constraints.

Abstract— The paper examines information about the role
of “Mobile Computing” an emerging media in the field of
education, and to establishing its primacy and universality
in a technologically propelled world of today. 'Media' is
the medium of carrying information, education and
entertainment to the masses. It is an easier and efficient
means of communication which plays a key role in the
overall development of an economy. Media largely consists
of print media like newspapers, magazines, journals and
other publications, etc. as well as electronic media like
radio, television, internet, etc. In India, the media and
entertainment industry is undergoing remarkable change
and is one of the fastest growing sectors.

HPC applications have been gaining lot of attention in the cloud computing world. Most of these applications are scientific applications that require large CPU capabilities and are also data intensive requiring large data storage. Traditionally they have always required large number of computers inter-connected in a network such as clusters or supercomputers. These clusters are difficult to setup and maintain both technically and financially. With the advent of cloud computing and benefits of Infrastructure as a Service (IaaS) and Platform as a Service (PaaS), scientists and researchers are able to deploy their HPC applications in the cloud without worrying about the costs associated with the infrastructure and other costs involved. They also give guarantees on the quality of service (QoS). This paper focuses on documenting some of the research already done in the field of HPC applications and their current state in cloud computing.

Energy Efficient Collision Aware Multipath
Routing for Wireless Sensor Networks

Connectivity to the Internet while in motion is becoming an extremely important part of computing research and development. Mobile IP, created by the Internet Engineering Task Force (IETF), is a standard protocol that builds on Internet Protocol by making mobility of a user transparent to applications and higher-level protocols such as Transfer Control Protocol. Mobile IP can be seen as the least common mobility denominator – providing seamless macro mobility solutions among the diversity of access. This paper will attempt to introduce Mobile IP from a technical point of view, while taking into consideration that the reader may not know anything about Mobile IP. However, the reader should know some networking basics before reading further. Building on these concepts, this paper will then discuss effective implementations of Mobile IP, the protocols used by Mobile IP and the importance of Mobile IP. This paper will also introduce Mobile IP from

Cloud Computing is a concept that has been defined differently by many and there seem not to be a consensus. Despite these views, cloud computing is not a complete new idea as it has intricate connections to technologies or domain such as the Grid Computing paradigm, and the general distributed computing. This overview gives the basic concept of cloud computing, and highlights the relationship between Cloud computing and other cloud enabling technologies by providing their similarities and differences. This insight into the essential characteristics of cloud and its enabling technologies provides a good foundation for understanding and a hint on how to leverage desirable strengths of these technologies in the cloud by way of extension and or inheritance.

This article will discuss how m-commerce conducts transactions of the mobile device through Internet and how these technologies are developed throughout the years. The article will also judge the security and privacy levels when dealing with mobile commerce, and what kind of issues are encountered when using mobile commerce systems. The article will also evaluate the solutions on how m-commerce issues are avoided and how they are tackled by the technology evolution.

The advent of computing technology has significantly influenced our lives and two major impacts of this effect are Business data Processing and Scientific Computing. During the early years of the development of computer techniques for business, computer professionals were concerned with designing files to store the data so that information could be efficiently retrieved. There were restrictions on storage size for storing data and on the speed of accessing the data. Needless to say, the activity was restricted to a very few, highly qualified professionals. Then came an era when Database Management System simplified the task. The responsibility of intricate tasks, such as declarative aspects of the programs was passed on to the database administrator and the user could pose his query in simpler languages such as query languages. Thus almost any business-small, medium or large scale began using computers for day-today activities. Now what is the use of all this data? Up to the early 1990’s the answer to this was “NOT much”. No one was really interested in utilizing data, which was accumulated during the process of daily activities. As a result a new discipline in computer science, Data Mining gradually evolved.
Index Terms – Data Mining,

The concept of green computing has begun to spread in the past few years, gaining increasing popularity. Besides the widespread sensitivity to ecological issues, such interest also stems from economic needs, since both energy costs and electrical requirements of IT industry around the world show a continuously growing trend. Green computing is the environmentally responsible use of computers and related resources. Such practices include the implementation of energy-efficient central processing units (CPUs), Servers and Peripherals as well as reduced resource consumption and proper disposal of electronic waste (e-waste). Green computing is the study and practice of efficient and eco-friendly computing. The principle behind energy efficient coding is to save power by getting software to make less use of the hardware, rather than continuing to run the same code on hardware that uses less power. This paper, first discuss the connotation of green computing and sketch researcher’s view on the next generation of IT systems for green computing. Subsequently, this paper helps to identify key issues relevant to green computing and evaluate different approaches to these problems. Finally, paper point out future directions of research and conclude the paper.

These days MANET (Mobile Ad-hoc Network) is an amazing remarkably altering or rising technology, for the reason that of its elite nature of scattered mobile devices and self-motivated network topology. The mobile ad-hoc routing protocol follows several principles in wireless MANET’s. The up to date and novel applications based on wireless technology are being produced in the private as well as commercial sectors. A lot of challenges which are facing wireless MANETs like network stability, security, energy efficiency and performance analysis etc. At present wireless ad-hoc network get much more attention because of its accessibility everywhere. As a result researchers produce several routing protocols. In this paper first of all we analyzed the performance investigation of wireless routing protocols on the basis of ROH (Routing Overhead), throughput, end-2-end delay and PDR (Packet Delivery Ratio). After that we proposed an MRP (Mixed Routing Protocol) framework which improve performance.

Opinion Mining (OM), which is also known as Sentiment classification or a
Polarity classification, is that binary classification of task labelling of an
opinionated text/document that expresses either a positive or an overall
opinion that is negative. Several technique of analysis of a subjective
information in the classification of sentiment is available. The extraction of feature chooses sufficient features for characterizing the opinion. The feature
selection (FS) that is also known as the variable selection, subset selection or
attribute reduction available in machine learning. It does select an input of
dataset which closely defines its specific outcome. Here in this research a
feature selection mechanism that is wrapper based is used based on a heuristic
algorithm. The experiments demonstrate that the proposed method improves
the efficiency of the classifiers and achieve higher accuracy.

The issue of feature subset selection for data of high dimensionality in classifying opinions has been investigated in this paper. Feature selection schemes select the crucial feature subset producing similar or superior classification outcomes compared to the original feature set obtained. Despite their higher efficiencies, wrapper-based feature selection schemes have high overheads of computation. However, the issue is the problem is Non-deterministic Polynomial (NP) hard. This work suggests the clustering scheme based on MST optimized by the Group Search Optimization (GSO) for efficient selection of features. The Amazon camera review dataset is used for evaluating the suggested scheme. Experiments are conducted to evaluate the proposed method and compared with the MRMR feature selection, FCM clustering, and MST based clustering.

This survey article intent presents knowledge into the security execution issues related to
steering in wireless networking like MANET’s (Mobile Ad hoc Networks).The mobile adhoc
networks are exposed to attacks at all the layers especially at the network layer. This study
specially provides a set of solutions for the issues of various attacks like attacks on
modifications, impersonation attacks, fabrication and rushing attacks. A few methodologies are
analysed for prevention, detection and reaction on various attacks by malicious nodes. The
study of this article has examined the methodologies meant for fathoming the implementation
issues like, changes in topology, vitality utilization of stations, delay, throughput, transmit time,
packet transmission ratio, systems or nodes security and administration.

Mobile ad hoc networks (MANETs) are a collection of wireless mobile devices with restricted
broadcast range and resources. Communication is achieved by relaying data along appropriate
routes that are dynamically discovered and maintained through collaboration between the nodes.
Discovery of such routes is a major task, both from efficiency and security point of view.
This paper presents a proficient and secure routing, based on asymmetric authentication using
key exchange approach (KEA). The proposed mechanism ensures secure routing and quality of
service in MANETs and minimizes the network overhead. The KEA mechanism can be
effectively used to develop a new routing protocol for Mobile Adhoc Networks which will
provide maximum security against all kinds of attacks. In this paper, KEA is compared with
other secure routing protocols like EEACK, AODV, and ARIADANE, to evaluate the efficiency
of KEA in Ad Hoc Networks. The empirical results show that

The modern growth in fabricate energy efficient Wireless Sensor Network is liberal a novel way
to systematize WSN in applications like surveillance, industrial monitoring, traffic monitoring,
habitat monitoring, cropping monitoring, crowd including etc. The rising use of these networks is
making engineers evolve novel and efficient ideas in this field. A group of research in data
routing, data density and in network aggregation has been proposed in recent years. The energy
consumption is the main apprehension in the wireless sensor network. There are many protocols
in wireless sensor network to diminish the energy consumption and to put in to the network
lifetime. Among a range of types of techniques, clustering is the most efficient technique to
diminish the energy expenditure of network. In this effort, LEACH protocol has been secondhand
for clustering in which cluster heads are nominated on the basis of distance and energy. The
LEACH protocol is been implemented in a simulated environment and analyze their performance
graphically.

Big data is collection of data which is vast range and composite data.. Data obtain created from each and every way, from various fields. These big data has structured semi-structured and unstructured kind of data. In today period data is been gathered on great scale. Social media sites, digital images and videos and countless other. Entire world is going so as to near the digitalization. All this kinds of data is well known as big data. Data mining is a process for uncovering a design which is convenient from huge scale data sets. We gather the healthcare information which comprise all the particulars of the sufferer, their symptoms, ill health etc. Formally we gather the information then there will be pre-managing on that information as we require only strain information for our study. Convenient and significant data can be withdraw from this big information with the assist of data mining by managing on that data. The data will be saved in Hadoop. User can access the data by symptoms, disease etc.

Big data can bring huge benefits to businesses of all size. However, as with any business project, proper preparation and planning is essential, especially when it comes to infrastructure. Until recently it was hard for companies and organizations to get into big data without making heavy infrastructure investments (expensive data warehouses, software, analytics staff, etc.). But times have changed. Now cloud computing has opened up a door to the companies to avoid investing lot of money for infrastructure.

In logistics, software aids for transportation planning and scheduling are often based in approximations and abstractions that do not take into account real-world data. The aim of this work is to provide an analysis and methodology, based on real-world data, on how to obtain probability density functions for prediction of activity duration. Such information can be used in planning algorithms, like vehicle routing problem, capable of dealing with stochastic time-windows.

This paper presents a general framework for planning the quasi-static motion of climbing robots. The framework is instantiated to compute climbing motions of a three-limbed robot in vertical natural terrain. An example resulting path through a large simulated environment is presented. The planning problem is one of five fundamental challenges to the development of real robotic systems able to climb real natural terrain. Each of the four other areas—hardware design, control, sensing, and grasping—is also discussed.

Enterprise Resource Planning (ERP) systems have become a de facto standard for integrating business functions. But an obvious question arises: if every business is using the same so-called ―Vanilla‖ software (e.g. an SAP ERP system) what happens to the competitive advantage from implementing IT systems? If we discard our custom-built legacy systems in favour of enterprise systems do we also jettison our valued competitive advantage from IT? While for some organisations ERPs have become just a necessity for conducting business, others want to exploit them to outperform their competitors. In the last few years, researchers have begun to study the link between ERP systems and competitive advantage. This link will be the focus of this paper. We outline a framework summarizing prior research and suggest two researchable questions. In conclusion, we present some initial findings from two empirical case studies derived from part of the European food industry.

Alzheimer’s disease is a 100-year-old concept. As a diagnostic label, it has evolved over the 20th and 21st centuries from a rare diagnosis in younger patients to a worldwide epidemic common in the elderly, said to affect over 35 million people worldwide. In this opinion piece, we use a constructivist approach to review the early history of the terms ‘‘Alzheimer’s disease’’ and related concepts such as dementia, as well as the more recent nosological changes that have occurred in the four major editions of the Diagnostic and Statistical Manual since 1952. A critical engagement of the history of Alzheimer’s disease and dementia, specifically the evolution of those concepts in the DSM over the past 100 years, raises a number of questions about how those labels and emergent diagnoses.

Neurodegenerative diseases are frequently associated with structural changes in the brain. Magnetic Resonance Imaging (MRI) scans can show these variations and therefore be used as a supportive feature for a number of neurodegenerative diseases. The hippocampus has been known to be a biomarker for Alzheimers disease and other neurological and psychiatric diseases. However, it requires accurate, robust and reproducible delineation of hippocampal structures. This work utilises a datasets consisting of MR images shared by EADC-ADNI working group . Hippocampus volume is a feature used in this analysis. For the other features we used publicly available brain segmentation package FreeSurfer v.5.1 (FS) (freesurfer.nmr.mgh.harvard.edu) [17] to process the structural brain MRI scans and compute morphological measurements. The FreeSurfer pipeline is fully automatic and provides 184 features per MRI scan in total. Volumes of cortical and sub-cortical structures such as the caudate and average thickness measurements within cortical regions, such as the precuneus. We use the FS features but for hippocampus volume we use the segmentation proposed in [16]. For the diagnosis classification we passed all the features to a C-Support Vector Classifier (C-SVC) with a linear kernel on a 5-fold cross validation. The goal is evaluating the performance of an algorithms for multi-class classification: AD, MCI and controls. Methods that are developed for binary classification can be used for three-way classification by using either a one-vs-one (ovo) or one-vs-all (ova) strategy. In this approach, three classifiers are trained for the three binary problems using the ovo methodology and thereafter their outputs are combined into three predictions.

Cloud computing is growing in popularity due to its ability to offer dynamically scalable resources provisioned as services regardless of user or location device. However, moving data to the cloud means that the control of the data is more in the hands of the cloud provider rather than the data owner. This is a great challenge that continues to hinder cloud computing from successfully achieving its potential. This is due to the fact that with cloud computing, the storage and processing of private information is done on remote machines that are not owned or even managed by the cloud consumers. This brings about significant security and data privacy concerns that impede the broader adoption of cloud computing, which compromises the vision of cloud computing as a new IT procurement model.

The Internet is fast becoming the de facto content delivery network of the world, supplanting TV and physical media as the primary method of distributing larger files to ever-increasing numbers of users at the fastest possible speeds. Recent trends have, however, posed challenges to various players in the Internet content delivery ecosystem. These trends include exponentially increasing traffic volume, increasing user expectation for quality of content delivery, and the ubiquity and rise of mobile traffic.

Automated platforms that conduct power line inspections need to have a vision system which is robust for their harsh working environment. State-of-the-art work in this field focuses on detecting primitive shapes in 2D images in order to isolate power line hardware. Recent trends are starting to explore 3D vision for autonomous platforms, both for navigation and inspection. However, expensive options in the form of specialized hardware is being researched. A cost effective approach would begin with multiple view geometry. Therefore, this study aims to provide a 3D context in the form of a reconstructed transmission pylon that arises from image data. To this end, structure from motion techniques are used to understand multiple view geometry and extract camera extrinsic.

Smart phones are basic needs of our daily life. It’s like a small computer which gives you many facilities such as web browsing, downloading and many more but small data storage space and backup are major problem. On the other hand cloud computing provides efficient computational resources and secure data hosting services. But the data transmission among two secure networks is performed over unsecured network. So need a design to secure data transfer.

Backing up and restoring enterprise applications (EAs) are essential operations that are usually done manually by an administrator or semi-automatically by tools. Backing up an enterprise application (EA) consists of backing up all its components together with the environments and operating systems in a consistent way so that the application can be restored and function properly later. There are many challenges for backing up and restoring EAs. This paper proposes a framework for automating the process of backing up and restoring EAs deployed in a cloud environment to ensure the continuous running of these enterprise applications and prevent the loss of data in case failure of applications

In new application areas of relational database systems, the join operator is used more than in conventional applications. We propose a simple data structure called join index, for improving the performance of joins in the context of complex queries. For most of the joins, updates to join indices incur very little overhead.

The significance of security devices that protect the numerous transactions, which take place in today‘s distributed virtual environment, cannot be underestimated. The importance of such devices will increase as our society continues to evolve into a cashless electronic society. The continuing increase in the number and size of electronic transactions, the advances in the technology utilized and the growing sophistication of the adversary have led to significant resources being invested in the evaluation and analysis of security devices. There has been a transformation of the traditional security analysis from one focused on mathematical primitives and physical engineering solutions to a holistic approach that seeks to protect against subtle interactions between the cryptographic, logical and physical aspects of such devices that can collude to compromise the security thereof.

This paper presents a principled approach to network redesign that creates more secure and manageable networks. We propose a new network architecture in which a global security policy defines all connectivity. The policy is declared at a logically centralized Controller and then enforced directly at each switch. All communication must first obtain permission from the Controller before being forwarded by any of the network switches. The Controller manages the policy namespace and performs all routing and access control decisions, while the switches are reduced to simple forwarding engines that enforce the Controller’s decisions.

From the past few years, there has been a rapid progress in Cloud Computing. With the increasing number of companies resorting to use resources in the Cloud, there is a necessity for protecting the data of various users using centralized resources. Some major challenges that are being faced by Cloud Computing are to secure, protect and process the data which is the property of the user. The main aim of this research is to understand the security threats and identify the appropriate security techniques used to mitigate them in Cloud Computing.

Global energy requirements are continuously increasing. Conventional methods of producing more energy to meet this growth pose a great threat to the environment. CO2 emissions and other bi-products of energy production and distribution processes have dire consequences for the environment. Efficient use of energy is one of the main tools to restrain energy consumption growth without compromising on the customer’s requirements. Improving energy efficiency requires understanding of the usage patterns and practices. Smart energy grids, pervasive computing, and communication technologies have enabled the stakeholders in the energy industry to collect large amounts of useful and highly granular energy us-age data. This data is generated in large volumes and in a variety of different formats depending on its purpose and systems used to collect it. The volume and diversity of data also increase with time. All these data characteristics refer to the application of Big Data.

With the growing prevalence of cyber threats in the world, various security monitoring systems are being employed to protect the network and resources from the cyber attacks. The large network datasets that are generated in this process by security monitoring systems need an efficient design for integrating and processing them at a faster rate. In this research, a storage design scheme has been developed using HBase and Hadoop that can efficiently integrate, store, and retrieve security-related datasets. The design scheme is a value-based data integration approach, where data is integrated by columns instead of by rows. Since rowkeys are the most important aspect of HBase table design and performance, a rowkey design was chosen based on the most frequently accessed columns associated with use cases for the retrieval of the dataset statistics. Tests conducted on various schema design alternatives prove that the rate at which the datasets are stored and retrieved using the model designed as part of this research is higher than that of the standard method of storing data in HBase.

Text mining has become a popular research area for discovering knowledge from unstructured text data. A fundamental process and one of the most important steps in text mining is representation of text data into feature vector. Majority of text mining methods adopt a keyword-based approach to construct text representation which consists of single words or phrases. These representation models such as vector space model, do not take into account semantic information since they assume all words are independent. The performance of text mining tasks, for instance Information Retrieval (IR), Information Extraction (IE) and text clustering, can be improved when the input text data is enhanced with semantic information.

Data Mining is an analytic process to explore data (usually large amounts of data - typically business or market related) in search of consistent patterns and/or systematic relationships between variables, and then to validate the findings by applying the detected patterns to new sets of data. The main target of data mining application is prediction. Predictive data mining is important and it has the most direct business applications in world. The paper briefly explains the process of data mining which consists of three stages: (1) the Initial exploration, (2) Pattern identification with validation, and (3) Deployment (application of the model to new data in order to generate predictions). Data Mining is being done for Patterns and Relationships recognitions in Data analysis, with an emphasis on large Observational data bases. From a statistical perspective Data Mining is viewed as computer automated exploratory data analytical system for large sets of data and it has huge Research challenges in India and abroad as well. Machine learning methods form the core of Data Mining and Decision tree learning. Data mining work is integrated within an existing user environment, including the works that already make use of data warehousing and Online Analytical Processing (OLAP). The paper describes how data mining tools predict future trends and behaviour which allows in making proactive knowledge-driven decisions.

Data-driven decision support systems, such as data warehouses can serve the requirement of extraction of information from more than one subject area. Data warehouses standardize the data across the organization so as to have a single view of information. Data warehouses can provide the information required by the decision makers. Developing a data warehouse for educational institute is the less focused area since educational institutes are non-profit and service oriented organizations. In present day scenario where education has been privatized and cut throat competition is prevailing, institutes needs to be more organized and need to take better decisions. Institute’s enrollments are increasing as a result of increase in the number of branches and intake. Now a day, any reputed Institute’s enrollments count in to thousands. In view of these factors the challenges for the management are meeting the diverse needs of students and facing increased complexity in academic processes. The complexity of these challenges requires continual improvements in operational strategies based on accurate, timely and consistent information. The cost of building a data warehouse is expensive for any educational institution as it requires data warehouse tools for building data warehouse and extracting data using data mining tools from data warehouse. The present study provides an option to build data warehouse and extract useful information using data warehousing and data mining open source tools. In this paper we have explored the need of data warehouse / business intelligence for an educational institute, the operational data of an educational institution has been used for experimentation. The study may help decision makers of educational institutes across the globe for better decisions.

When data is shared and/or published, the need for revealing data must be balanced with the need for sanitizing it. This is because some information considered “sensitive”, if revealed may cause damaging consequences, for example, privacy violations, legal and financial liabilities, embarrassment, national security risks, and loss of reputation. Although many techniques for sanitizing data have been developed and used over the years, attackers have still managed to de-sanitize data. One of the reasons for this problem is the tremendous growth of publicly available information. Data like telephone numbers, date of birth, movie ratings, personal preferences like favorite movies and favorite food recipes, property records, real-time geolocation information through social media content and photo metadata can now be easily found on the Internet. This has enabled attackers to gather an immense amount of information about a user or a group of users and correlate it with sanitized datasets. Such correlations can lead to many methods of inferring sensitive information. In this dissertation, we show a method by which data can be evaluated to see if it can be sanitized effectively, while maintaining needed utility from the data, and if so, how can it be done optimally.

The necessity of information security within an organization has undergone major changes in the past and present times. In the earlier times physical means is used to provide security to data. With the advent of computers in every field, the need for software tools for protecting files and other information stored on the computer became important. The important tool designed to protect data and thwart illegal users is computer security. Security mechanisms usually involve more than a particular algorithm or protocol for encryption & decryption purpose and as well as for generation of sub keys to be mapped to plain text to generate cipher text. It means that participants be in possession of some secret information (Key), which can be used for protecting data from unauthorized users. Thus a model has to be developed within which security services and mechanisms can be viewed. With the introduction and revolution in communications, one more change that affected security is the introduction of distributed systems which requires carrying of data between terminal user and a set of computers. Network security measures are needed to protect data during their transmission. The mechanisms used to meet the requirements like authentication and confidentiality are observed to be quite complex. As the importance of information systems is ever growing in all most all fields, electronic information takes on many of the roles, earlier they being done on papers. Few information integrity functions that the security mechanism has to support are security and confidentiality of the data to be transmitted and authentication of users.

Data mining technology has emerged as a means of identifying patterns and trends from large quantities of data. Data mining and data warehousing go hand-in-hand: most tools operate by gathering all data into a central site, then running an algorithm against that data. However, privacy concerns can prevent building a centralized warehouse – data may be distributed among several custodians, none of which are allowed to transfer their data to another site. This project addresses the problem of computing association rules within such a scenario. We assume homogeneous databases: All sites have the same schema, but each site has information on different entities. The goal is to produce association rules that hold globally, while limiting the information shared about each site. In this project, a new protocol is proposed which combines the advantages of the existing approaches to perform privacy preserving in distributed mining of association rules. Both the privacy and performance characteristics of the proposed protocol are studied and compared with the mining and cryptographic approaches.

Data Mining is a widely used technique for discovering valuable information in a complex data set. In this paper we discussed the main issues about Mobile User Behavior Mining. In mobile transaction database, users in the different user groups may have different behaviors. So that we proposed parameter-less clustering algorithm named CO-Smart-CAST. This behavior mining can produce better accuracy of predicting the mobile user information using that algorithm and to provide efficient mining of sequential access in mobile patterns. Here, the clustering method provides a way to calculate the time interval between one transaction to another transaction. We have predicted the behavior of mobile user using CO-Smart-CAST method. This method of process can be done by following ways. 1. Movements and transaction time measurements, 2. Discovering sequence patterns during transaction using clustering and classification. The behavior using communication model can be classified as following three ways. 1. Angry chat, 2. Happy chat, 3. Chat with deep thoughts. To our best knowledge, this work on mining and prediction of mobile behavior with user relation are done simultaneously. Finally, the methods in proposed system will deliver the better performance.

In biological research domain like “Study of animal social behavior” and “Wild life migration” object tracking sensor networks are used. In this application concentrating on finding the group of object with similar movement pattern using distributed mining techniques. But generally WSN concentrating on finding moving patterns of single object or all objects. Tracking moving objects having two phases i.e. mining phase and cluster ensembling phase. In first phase of algorithm we find movement patterns based on local data then we are identifying new term of similarity measure of to computing the similarity of moving objects and find relationship between them. In second phase algorithm combine the local grouping results to derive the group relationship from global view. We hope that the final output shows that the proposed mining algorithm achieves good grouping quality and the mining technique helps reduce the energy consumption by reducing the amount of data to be transmitted.

In this work, we propose a novel prediction framework, which takes into account the spatial property, temporal property, users’ behavior and environment at the same time, for semantic place prediction. The core idea of our proposal is to extract features to represent end users’ behaviors in each place related to its semantic. To achieve this goal, we define 54 features to represent end users’ behaviors to capture the key properties of places recorded in MDC Data Set. In our framework, we propose a novel model, namely Multi-Level Classification Model , to solve the imbalanced data problem. Based on the Multi-Level Classification Model, we make semantic prediction of a place by combining several classification models. To our best knowledge, this is the first work on predicting semantic label of places through integrating sub-classification models into a multi-level structure.

Telecommunication companies today are operating in highly competitive and challenging environment. Huge volume of data is generated from various operational systems and these are used for solving many business problems that required urgent handling. These data include call detail data, customer data and network data. Data Mining methods and business intelligence technology are widely used for handling the business problems in this industry. The main application areas of BI and Data Mining in telecommunication industry include fraud detection, network fault isolation and improving market effectiveness.

Assessing the Awareness and Perceptions of Academic Staff in Using E-learning Tools for Instructional Delivery in a Post-Secondary Institution: A Case Study

Demonetization is a generations’ memorable experience and is going to be one of the economic events of our time. Its impact is felt by every Indian citizen. Demonetization affects the economy through the liquidity side. Demonetizing is Progressive shift to a cashless economy with a greater focus on electronic transactions is being envisaged. Rising use of credit/debit cards, net banking and other online payment mechanisms will be another positive effect of demonetization, as these would not only lower transaction costs but some of these could help earn some fee income as well.

Grid Computing has become another buzzword after Web 2.0. However, there are dozens of different definitions for Grid Computing and there seems to be no consensus on what a Grid is.

This paper describes about Grid Computing. In various ways we are trying to explain grid computing along with its architecture and the standards available for grid computing. Then at last we have discussed about the benefits of grid computing.

Today’s era is completely dependent on computers. Cloud Computing is the most important technology which is diffusing in the sky of IT. It covers number of advantages like resource sharing; provide large servers for data storage on pay per use basis. But some users still have an impression that saving their confidential data on cloud will no longer remain confidential due to security issues. This paper will concentrate on the basic aspect and the nine security threats related to cloud computing.

A wireless sensor network consists of a large number of battery powered sensor nodes that are capable of sensing and processing the data, and can transmit the data wirelessly to the base station. The effective and practical way for enhancing the performance of WSNs is clustering. As the clusters are formed dynamically and periodically in a cluster based WSN, securing the data transmission in these networks is a critical issue. A secure and efficient data transmission (SET) protocol, called SET-IBS is been recently proposed whose security relies on the hardness of the Diffie-Hellman problem in the pairing domain. Though results show that this protocol has better performance than the existing secure protocols for CWSNs in terms of security overhead and energy consumption, the computational overhead of this protocol is comparatively high. The existing SET-IBS protocol is based on bilinear pairings, where the computation of pairing is time-consuming. This paper aims to provide a reliable and efficient data transmission for CWSNs with low computational overhead using identity based digital signature from elliptic curve digital signature algorithm (IB-ECDSA), which is an identity based signature protocol without pairings, to enhance the existing SET-IBS protocol. As a result, the computation cost can be saved when compared to the existing SET-IBS scheme that uses pairing.

Cloud Computing is using hardware and software as computing resources to provide service through internet. We can access the data from anywhere, at any time on demand. The major problem in cloud data storage is security. So in order to provide high security, we proposed Privacy Preserving Auditing Protocol along with blow fish algorithm which enables an external auditor to audit user’s outsourced data in cloud without reading the actual data content. We also improved efficiency by means of Batch Auditing.

Mining sequential patterns has been a focused theme in data mining research for over a decade. One of the promising approaches of SPM is mainly deal with finding the behaviour of a sequential pattern that can help in many analyzing applications like predicting next event. There are several efficient algorithms that cope with the computationally expensive task of sequential pattern mining. One of them is Generalized Sequential Pattern (GSP) mining algorithm which is an Apriori-based algorithm used for sequential pattern mining. The GSP algorithm has several deficiencies whenever the database size is large, too many scanning of database when seeking frequent sequences and very large amount of candidate sequences generated unnecessary. PrefixSpan which is pattern growth method outperforms GSP and solves all above problems. Its main idea is to examine only the prefix subs equences with minimum support. This paper investigates these algorithms by classifying study of SPM algorithms.

This paper discusses different issues of Wireless Sensor Network (WS N) and the relevance of the Elliptic curve y cryptography. Security in WS N is a greater challenge in WS N due to the processing limitations of sensor nodes and nature of wireless links. Extensive use of WS Ns is giving rise to different types of threats. To defend against the threats proper security schemes are required. Traditionally security is implemented through hardware or software and is generally achieved through cryptographic methods. Limited area, nature of links, limited processing, power and memory of WS Ns leads to strict constraints on the selection of cryptographic techniques. Elliptic Curve Cryptography (ECC) is the best candidate due to its smaller key size. High security despite of smaller key size results in area and power efficient crypto systems.

Wireless Sensor Network is a type of wireless network which consists of a collection of tiny device called sensor node. Wireless Sensor Network is one of the rapidly developing areas. Applications of Wireless Sensor Network includes remote environmental monitoring, target tracking, etc. Various algorithms are proposed in 2D for location tracking which provides accuracy but in the real world, we require all the three planes for correct estimation and more accuracy in localization. The 2D works on flat terrain but we need to position WSN in harsh terrain also, so we need an algorithm in 3D that provide better accuracy and decrease the error of estimation and provide a real world view also. The goal of our survey is to present the localization techniques of node.

Nowadays companies are starting to realize the importance of using more data in order to support decision for their strategies. It was said and proved through study cases that “More data usually beats better algorithms”. With this statement companies started to realize that they can chose to invest more in processing larger sets of data rather than investing in expensive algorithms. The large quantity of data is better used as a whole because of the possible correlations on a larger amount, correlations that can never be found if the data is analyzed on separate sets or on a smaller set. A larger amount of data gives a better output but also working with it can become a challenge due to processing limitations.

This article intends to define the concept of Big Data and stress the importance of Big Data Analytics.

Cloud computing, a disruptive technology, is a model for enabling ubiquitous, convenient, on-demand network access to a shared pool of configurable computing resources having its intrinsic potentiality to enhance collaboration and agility along with immense opportunity for cost-reduction through optimized and efficient computing. Its tremendous envision capability to cater components rapidly orchestrated, provisioned, implemented and decommissioned, scaling and on-demand utility-like model of allocation and consumption, is however, not free from some serious drawbacks due to its inherent security breach - a big concern for both for providers and users. With the improvement of technologies, the attackers or hackers are able to launch attack vectors over cloud services causing a headache to all. While threat, privacy, compliance, integrity, security and alike words are no more buzzwords in the recent era of high-end information technology, cloud security has evolved as a significant research area not only for the researchers but also for the cloud providers and users as well.

In trend mobile is one of the important devices in public sector. In mobile community there are N numbers of vendors, manufacturers available. The telecommunications industry was first to adopt data mining technology. Telecommunication companies day by day generate and store enormous amounts of high-quality data, have a very large customer data base and operate in a rapidly changing and highly competitive business environment. Telecommunication companies utilize data mining technique to improve their marketing efforts, identify fraud and better manage their telecommunication network connection. In this paper we provide an effective solution to identify the fraud detection in telecommunication using Data Mining clustering techniques with GA as well as misbehavior users. We believe this approach will help in our society.

Cloud Computing has become a scalable services consumption and delivery platform in the field of Services Computing. The technical foundations of Cloud Computing include Service-Oriented Architecture (SOA) and Virtualizations o f hardware and software. Cloud computing is the development of parallel computing, distributed computing, grid computing and virtualization technologies which define the shape of a new era. Cloud computing is an emerging model of business computing. In this paper, we explore the concept of cloud architecture and compares cloud computing with grid computing. We also address the characteristics and applications of several popular cloud computing platforms. In this paper, we aim to pinpoint the challenges and issues of cloud computing. We identified several challenges from the cloud computing adoption perspective and we also highlighted the cloud interoperability issue that deserves substantial further research and development. However, security and privacy issues present a strong barrier for users to adapt into cloud computing systems. In this paper, we investigate several cloud computing system providers about their concerns on security and privacy issues.

Wireless Sensor Network is a type of wireless network which consists of a collection of tiny device called sensor node. Wireless Sensor Network is one of the rapidly developing areas. Applications of Wireless Sensor Network includes remote environmental monitoring, target tracking, etc. Various algorithms are proposed in 2D for location tracking which provides accuracy but in the real world, we require all the three planes for correct estimation and more accuracy in localization. The 2D works on flat terrain but we need to position WSN in harsh terrain also, so we need an algorithm in 3D that provide better accuracy and decrease the error of estimation and provide a real world view also. The goal of our survey is to present the localization techniques of node.

Grid Computing has become another buzzword after Web 2.0. However, there are dozens of different definitions for Grid Computing and there seems to be no consensus on what a Grid is.

This paper describes about Grid Computing. In various ways we are trying to explain grid computing along with its architecture and the standards available for grid computing. Then at last we have discussed about the benefits of grid computing.

Network security is one of the significant aspects of

information security. Network security is involved in various business organizations, enterprises, and other types of institutions and it has become a pivotal function in building and maintaining today's modern high-growth networks. Cryptography is a technology used to provide of information security by encoding the data. It provides a high secured data transmission by encrypting the data that cannot be accessed by a third party. This paper encompasses the basics of network security and types of symmetric algorithms and new approach for symmetric encryption algorithm for encryption and decryption of data and the merits of the new proposed algorithm.

Security is the most challenging aspects in the internet and network applications. Internet and networks applications are growing very fast, so the importance and the value of the exchanged data over the internet or other media types are increasing. Hence the search for the best solution to offer the necessary protection against the data intruders’ attacks along with providing these services in time is one of the most interesting subjects in the security related communities. Cryptography is the one of the main categories of computer security that converts information from its normal form into an unreadable form. The two main characteristics that identify and differentiate one encryption algorithm from another are its ability to secure the protected data against attacks and its speed and efficiency in doing so.

Modular multiplication is an important operation in several public key cryptosystems. This paper brings a novel idea based on the idea in the exponentiation computation. In this paper a new algorithm for modular multiplication for public key cryptosystem is presented. This proposed method is based on the following two ideas.(i) The remainder in regard to n can be constructed from the remainder with modulus (2n+1) and the remainder with modulus (2n+2 ). (ii) It often happens that 2n+1 and 2n+2 can easily be factorized, even if n is a prime number or difficult to be factorized into prime factors. The performance of new algorithm using estimation of the computational complexity is observed, and it is shown that the procedure is much faster than the previous algorithms.

It is well -known that cloud computing has many potential advantages and many enterprise applications and data are migrating to public or hybrid cloud. But regarding some business-critical applications, the organizations, especially large enterprises, still wouldn’t move them to cloud. The market size the cloud computing shared is still far behind the one expected. From the consumers’ perspective, cloud computing security concerns, especially data security and privacy protection issues, remain the primary inhibitor for adoption of cloud computing services. This paper provides a concise but all-round analysis on data security and privacy protection issues associated with cloud computing across all stages of data life cycle. Then this paper discusses some current solutions. Finally, this paper describes future research work about data security and privacy protection issues in cloud.

Any communication in the language that you and I speak—that is the human language, takes the form of plain text or clear text. That is, a message in plain text can be understood by anybody knowing the language as long as the message is not codified in any manner. So, now we have to use coding scheme to ensure that information is hidden from anyone for whom it is not intended, even those who can see the coded data.

Cryptography is the art of achieving security by encoding messages to make them non-readable. Cryptography is the practice and study of hiding information. In modern times cryptography is considered a branch of both mathematics and computer science and is affiliated closely with information theory, computer security and engineering. Cryptography is used in applications present in technologically advanced societies; examples include the security of ATM cards, computer passwords and electronic commerce, which all depend on cryptography.

n this paper, we explore a new data mining capability for a mobile commerce environment based on location based service(LBS). The mobile commerce environment has received a lot of interests from both of the industry and academia. A novel framework,called Mobile Commerce Explorer (MCE), used for mining and prediction of mobile users’ movements and
purchase transactions under the context of mobile commerce. The MCE framework consists of three main components like 1) Similarity Inference Model (SIM)measuring the similarities among stores and items; 2) Personal Mobile Commerce Pattern Mine (PMCP-Mine) algorithm used for finding the mobile users’ Personal Mobile Commerce Patterns (PMCPs); 3) Mobile Commerce Behavior Predictor (MCBP) for prediction the future mobile user behaviors. Location-based service(LBS) is used for recommending the stores and items previously unknown to a user. The, Administrator controller will monitor the whole transaction process, so there will be secure transaction

The usage of location aware devices, such as mobile phones and GPS-enabled devices, is widely spread nowadays, allowing access to large spatiotemporal datasets. The space-time nature of this kind of data results in the generation of huge amounts of mobility data and imposes new challenges regarding the analytical tools that can be used for transforming raw data to knowledge. In our research, we investigate the extension of Data Warehousing and data mining technology so as to be applicable on mobility data. In this paper, we present the, so far, developed framework for analyzing mobility data and some preliminary results.

This paper summarizes opportunities and challenges of big data. It identifies important research directions and includes a number of questions that have been debated by the panel.

The major aspire of this paper is to make a study on the concept Big data and its application in data mining. The paper mainly concentrating different types of big data and its application in knowledge discovery.

The term “cloud computing” has been in the spotlights of IT specialists the last years because of its potential to transform this industry. The promised benefits have determined companies to invest great sums of money in researching and developing this domain and great steps have been made towards implementing this technology. Managers have traditionally viewed IT as difficult and expensive and the promise of cloud computing leads many to think that IT will now be easy and cheap.

The article describes the application of mobile communication technology for enhancing of educational process.

Hash functions are the most widespread among all cryptographic primitives, and are currently used in multiple cryptographic schemes and in security protocols. This paper presents a new Secure Hash Algorithm called (SHA-192). It uses a famous secure hash algorithm given by the National Institute of Standard and Technology (NIST).The basic design of SHA-192 is to have the output length of 192.The SHA-192 has been designed to satisfy the different level of enhanced security and to resist the advanced SHA attacks. The security analysis of the SHA-192 is compared to the old one given by NIST and gives more security and excellent results as shown in our discussion. In this paper the digital signature algorithm which is given by NIST has been modified using the proposed algorithms SHA-192. Using proposed SHA-192 hash algorithm a new digital signature schemes is also proposed. The SHA-192 can be used in many applications such s public key cryptosystem, digital signcryption, message authentication code, random generator and in security architecture of upcoming wireless devices like software defined radio etc.

The improved capabilities of the recent cellular phones compared to older ones had lead the telephone companies offer a lot of value added services. Emergence of new technologies will lead to emergence of new services increasing the percentage of users for such services. To improve the quality of services provided for the users, mining and clustering of different mobile transaction behavior are useful. For clustering we have LBS based algorithm. LBS based services which are in demand are used to find a location, people, services and to find similarities to predict next behavior of mobile user.

This research deals with data security management in distributed and client/server computer systems, placing special emphasis on access security. The paper presents the subject of data security management in these systems by describing them, examining their vulnerable points and presenting adequate solutions. The paper includes a survey on the subject of authorization, authentication, encryption and access control - the main components in data security management of distributed systems.

In addition to a survey and analysis of data security management aspects, a plan of an access security system based on client/server architecture is presented, which may be combined with applications requiring access security services. The model describes the access security server and the interface for access security which is combined with the application and constitutes the client portion.

Abstract
Cloud Computing promises cost cutting efficiencies to
businesses and specifically their accounting
departments through the use of third party vendors to
store and process information. However this cloud
computing innovation of storing and managing data
off site also adds risk to the data security of a
company. The Committee of Sponsoring
Organizations (COSO), the Big Four accounting firms
and other industry analysts have identified the
benefits and concerns surrounding use of cloud
technology and have prepared recommendations for
companies who wish to utilize cloud computing on a
formal or informal basis in their business operations.
This paper will analyze the current advise on the risks
of cloud computing in an effort to determine Best
Practices for implementing use of and regulation of
use of Cloud Computing within an organization.

Many technologies and applications have appeared
recently which are directed at mobile computing and
the wireless Web. Wireless (or mobile) e-commerce is
concerned with conducting transactions and other
business activity with these new technologies and
applications. This research looks at some of the
relevant technologies, applications, and issues in
wireless e-commerce.

Cloud Computing promises cost cutting efficiencies to
businesses and specifically their accounting
departments through the use of third party vendors to
store and process information. However this cloud
computing innovation of storing and managing data
off site also adds risk to the data security of a
company. The Committee of Sponsoring
Organizations (COSO), the Big Four accounting firms
and other industry analysts have identified the
benefits and concerns surrounding use of cloud
technology and have prepared recommendations for
companies who wish to utilize cloud computing on a
formal or informal basis in their business operations

The problem of conceptual descriptions and evaluation of
sustainable development are analyzed in the work. As the
objectives, descriptions of the concept of sustainable
development are analyzed and classified. Then the analysis of
the concept of sustainable development is given. After this
analysis the systematic view of the dimensions of sustainable
development is provided. Methods of systematic scientific
literature analysis, general and logical analysis, comparison
and generalization were used for the research.

Multipath routing can reduce the need for route updates, balance the traffic load and increase the data transfer rate in a wireless sensor network, improving the utilization of the limited energy of sensor nodes. However, previous multiple path routing methods use flooding for route discovery and transmit data with maximum power regardless of need, which results in waste of energy. Moreover, often a serious problem of collisions among multiple paths arises. In this paper, we propose an energy efficient and collision aware (EECA) node-disjoint multipath routing algorithm for wireless sensor networks. With the aid of node position information, the EECA algorithm attempts to find two collision- free routes using constrained and power adjusted flooding and then transmits the data with minimum power needed through power control component of the protocol. Our preliminary simulation results show that ECCA algorithm results in good overall performance, saving energy and transferring data efficiently.

HPC applications have been gaining lot of attention in the cloud computing world. Most of these applications are scientific applications that require large CPU capabilities and are also data intensive requiring large data storage. Traditionally they have always required large number of computers inter-connected in a network such as clusters or supercomputers. These clusters are difficult to setup and maintain both technically and financially. With the advent of cloud computing and benefits of Infrastructure as a Service (IaaS) and Platform as a Service (PaaS), scientists and researchers are able to deploy their HPC applications in the cloud without worrying about the costs associated with the infrastructure and other costs involved. They also give guarantees on the quality of service (QoS). This paper focuses on documenting some of the research already done in the field of HPC applications and their current state in cloud computing.

The importance of awareness with regard information systems (IS) security has been recently acknowledged. This paper studies the applicability of one aspect of the awareness approach, namely ethics and morality, to the context of pervasive computing.

This paper presents an overview of ethical theories by discussing descriptivism and universal prescriptivism, the latter of which is then applied to the context of IS security. A model of ethical thinking in organizational context is developed, problem areas and hypotheses are identified and preliminary solutions are presented.

As more and more information of individuals and companies is placed in the cloud, concerns are beginning to grow about just how safe an environment it is. This paper deals with a security mechanism which ensures the integrity of the data stored in the cloud. In this paper, a password based digital signature technique has been proposed. This combination mechanism provides three way security i.e. data security, authentication and verification. In this paper, I have proposed RSA encryption algorithm for confidentiality of data and for authentication hash algorithm can be implemented and PBKDF2 key derivation function for generating the key for encryption.

This paper deals with some security issues which are occurred often in some areas like personal systems, Networking in Industries etc. Here we discussed some concepts which are related to encryption techniques in Cryptography like Security attacks, Services and Mechanism, Cryptanalysis, Steganography, Cryptographic attacks, Symmetric and public key algorithm, Conventional, Classical and Transposition techniques. And there is some network security related threats along with their solutions like non-complex, weak network access passwords, viruses and worms, Trojen Horses, SPAM, Phising, Packet sniffers, Shared computers, Zombie computers and botnets.

Nowadays Internet of Things (IoT) gained a great awareness from researchers, since it becomes allowing a communications between machines, objects and everything together with peoples and important technology that promises a smart human being life. In the real world connected to the Internet via wireless network and IOT can use different types of connections like RFID, Bluetooth, WIFI and ZigBee. Technology of IOT becomes smart in every aspect. Since the IOT will provide a means of smart cities, smart healthcare, smart homes and building using this having various important applications as smart energy, grid, transportation, waste management and monitoring.

Cloud computing provides several attractive benefits for users like on-demand computing, pay as per use. It brings great convenience to consumers; where shared resources, data and information are provided to computers on-demand and consumer has to pay as per use. Ideally for these services, consumers should be in a position to verify the charges billed to them. Cloud computing and storage solutions provide users and enterprises with various capabilities to store and process their data. But on other hand consumers are facing serious difficulties that how to search the most suitable services from cloud. It is desirable to store data on data storage servers such as mail servers and file servers in encrypted form to reduce security and privacy risks. Encryption is the process of encoding messages or information in such a way that only authorized parties can read it. Multiple encryption techniques are invented to encrypt the data. That way encrypted search has become an important problem in security. This is due to a combination of three things: (1) search is now the primary way we access our data;

Cloud computing is getting attention of the researchers these days. Large number of users are attached with cloud computing. But as there are several merits of cloud computing some demerits are also there. The one of the greatest threat in cloud computing is security. This security is concerned with data of the users that is present in cloud and is transferred across the clouds and the virtualization concept. In this paper several attacks on cloud are studied and solutions to those threats are compiled. In this paper a secure technique to handle data in cloud and secure virtualization is proposed in this paper. A secure VM migration technique which gives VM isolation guarantee and VM escape protection is proposed here. And it is shown that this security algorithm posses no considerable overhead.

big data can bring huge benefits to businesses of all size. However, as with any business project, proper preparation and planning is essential, especially when it comes to infrastructure. Until recently it was hard for companies and organizations to get into big data without making heavy infrastructure investments (expensive data warehouses, software, analytics staff, etc.). But times have changed. Now cloud computing has opened up a door to the companies to avoid investing lot of money for infrastructure.

E learning is a tool for using information technology to enable user to learn anytime and anywhere in the world. It provides the learners to get information from experts and can be imparted training with the use of internet technological channels and networks, e-learning uses
web to serve not just for the core-teaching and for learning process. E-Learning is the convergence of learning through internet. It has brought about profound changes in world over in the way of learning and training of users anytime and anywhere e-learning is increasingly perceived by governments and educators. This paper speaks about the what and why is E-Learning and this characteristics, Advantages, Disadvantages of E-Learning.

E learning is a tool for using information technology to enable user to learn anytime and anywhere in the world. It provides the learners to get information from experts and can be imparted training with the use of internet technological channels and networks, e-learning uses
web to serve not just for the core-teaching and for learning process. E-Learning is the convergence of learning through internet. It has brought about profound changes in world over in
the way of learning and training of users anytime and anywhere e-learning is increasingly perceived by governments and educators. This paper speaks about the what and why is E-Learning and this characteristics, Advantages, Disadvantages of E-Learning.

It has been said that the system mostly produces robots who possesses an amazing capacity for storing facts and churning them out at the press of the right button. Qualities like independent thinking, problem solving ability, initiative leadership skills and social competence fall by the wayside as getting high grades becomes their only goal.