Accepted Papers

  • Big Graph: Tools, Techniques, Issues, Challenges and Future Directions
    Dhananjay Kumar Singh and Ripon Patgiri,National Institute of Technology Silchar,India

    Analyzing interconnection structures among the data through the use of graph algorithms and graph analytics has been shown to provide tremendous value in many application domains (like social networks, protein networks, transportation networks, bibliographical networks, knowledge bases and many more). Nowadays, graphs with billions of nodes and trillions of dges have become very common. In principle, graph analytics is an important big data discovery technique. Therefore, with the increasing abundance of large scale graphs, designing scalable ystems for processing and analyzing large scale graphs has become one of the timeliest problems facing the big data research community. In general, distributed processing of big graphs is a challenging task due to their size and the inherent irregular structure of graph computations. In this paper, we present a comprehensive overview of the state-of-the-art to better understand the challenges of developing very high-scalable graph processing systems. In addition, we identify a set of the current open research challenges and discuss some promising directions for future research.

  • Technology Road Map Drawing Of Cloudbased Payment Based on BibliometricsApproach from Mining the Patent and Literature
    Ni Zeng and Shunxi Li,Wuhan University of Technology,P.R.China

    This paper quantitatively analyses and evaluates current research status of cloud-based payment based on bibliometrics for the first time, through content analysis involving analysis of author, keywords and abstracts. Then qualitative analysis is performed for all kinds of cloud-based payment, essential characteristics involving pros and cons, interconnections and improvement potential among various methods to realize cloud-based payment. Finally, latest developing trends in cloud-based payment are presented to improve the development of cloud-based payment based on above quantitative analysis and qualitative analysis, such as HCE. And draw a technology road map of Cloud-based Payment industry for the first time. This paper not only first provides a comprehensive analysis of cloud-based payment, but also puts forward the emphasis and orientation of future study by realizing the technology road map, which will broaden relevant researchers' vision and promote the development of a simple and practical cloud-based payment system.

  • Automated Short Answer Grader Using Friendship Graphs
    Soumajit Adhya1 and S.K. Setua2,1J.D. Birla Institute,India and 2University of Calcutta,India

    The paper proposes a method to assess short answer written by student by using friendship matrix which is derived from friendship graph. The Short Answer is a type of answer which is based on facts. These answers are quite different from long answers and MCQ type answers. The friendship graph is a graph which is based on friendship condition i.e. the nodes have only one common neighbor. Friendship matrix is the matrix form of the friendship graph. The student answer is stored in a friendship matrix and the teacher answer is stored in another friendship matrix and both the matrices are compared. Based on the number of errors encountered from student answer an error marks is calculated and that number is subtracted from full marks to get student grade.

  • Implementation and Comparative Study of Improved Apriori Algorithm for Association Pattern Mining
    Sonali Sonkusare and Mr. Jayesh Surana,Shri Vaishnav Inst. of Science and Technology,India

    The data mining includes different kinds of data models for analysing the data. The data mining based analysis leads to produce the outcomes according to the employed algorithms over similar kind of data. Thus according to the databases and their mining based outcomes data mining algorithms can be classified in association rule mining algorithm, classification algorithm or clustering methods. In literature a number of different techniques and algorithms are available by which the association rules are mined for different purposes. Among them Apriori algorithm is one of most popular technique of association rule mining. The Apriori algorithm is basically used for transactional pattern analysis using the frequent pattern evaluation of target itemsets. Therefore to execute the process, algorithm generates the candidate sets for association pattern analysis. In this presented work first the implementation of Apriori algorithm is performed and then to reduce the time and space complexity a new technique using the Apriori algorithm is performed for finding the association rules. In the proposed rule mining technique the candidate generation is limited by pre-analysis of itemsets during candidate set generation process. Due to this less number of candidates and high quality rules are formed. The implementation of Apriori algorithm is performed using JAVA technology. Additionally the performance in terms of space and time complexity is measured. According to comparative performance study proposed Apriori algorithm provides better and less number of rules in efficient manner.

  • A Survey on Security Risk Management Frameworks in Cloud Computing
    Rana Alosaimi and Mohammad Alnuem,King Saud University,Saudi Arabia

    Cloud computing technology has experienced exponential growth over the past few years. It provides many advantages for both individuals and organizations. However, at the same time, many issues have arisen due to the vast growth of cloud computing. Organizations often have concerns about the migration and utilization of cloud computing due to the loss of control over their outsourced resources and cloud computing is vulnerable to risks. Thus, a cloud provider needs to manage the cloud computing environment risks in order to identify, assess, and prioritize the risks in order to decrease those risks, improve security, increase confidence in cloud services, and relieve organizations’ concerns on the issue of using a cloud environment. Considering that a conventional risk management framework does not fit well with cloud computing due to the complexity of its environment, research in this area has become widespread. The aim of this paper is to review the previously proposed risk management frameworks for cloud computing and to make a comparison between them in order to determine the strengths and weaknesses of each of them. The review will consider the extent of the involvement and participation of consumers in cloud computing and other issues.

  • Automatic Generation and Optimization Of Test Data using Harmony Search Algorithm
    Rajesh Kumar Sahoo1,Deeptimanta Ojha2,Durga Prasad Mohapatra3 and Manas Ranjan Patra4,1,2Ajay Binay Institute of Technology,India,3National Institute of Technology,India and 4Berhampur University,India

    Software testing is the primary phase, which is performed during software development and it is carried by a sequence of instructions of test inputs followed by expected output. The Harmony Search (HS) algorithm is based on the improvisation process of music. In comparison to other algorithms, the HSA has gain popularity and superiority in the field of evolutionary computation. When musicians compose the harmony through different possible combinations of the music, at that time the pitches are stored in the harmony memory and the optimization can be done by adjusting the input pitches and generate the perfect harmony. The test case generation process is used to identify test cases with resources and also identifies critical domain requirements. In this paper, the role of Harmony search meta-heuristic search technique is analyzed in generating random test data and optimized those test data. Test data are generated and optimized by applying in a case study i.e. a withdrawal task in Bank ATM through Harmony search. It is observed that this algorithm generates suitable test cases as well as test data and gives brief details about the Harmony search method. It is used for test data generation and optimization.