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Publisher: Inderscience Publishers   (Total: 443 journals)

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Showing 1 - 200 of 443 Journals sorted alphabetically
African J. of Accounting, Auditing and Finance     Hybrid Journal   (Followers: 13)
African J. of Economic and Sustainable Development     Hybrid Journal   (Followers: 14)
Afro-Asian J. of Finance and Accounting     Hybrid Journal   (Followers: 8, SJR: 0.195, CiteScore: 0)
American J. of Finance and Accounting     Hybrid Journal   (Followers: 23)
Asian J. of Management Science and Applications     Hybrid Journal   (Followers: 4)
Atoms for Peace: an Intl. J.     Hybrid Journal   (Followers: 3)
Electronic Government, an Intl. J.     Hybrid Journal   (Followers: 17, SJR: 0.424, CiteScore: 1)
EuroMed J. of Management     Hybrid Journal  
European J. of Cross-Cultural Competence and Management     Hybrid Journal   (Followers: 7)
European J. of Industrial Engineering     Hybrid Journal   (Followers: 10, SJR: 0.595, CiteScore: 1)
European J. of Intl. Management     Hybrid Journal   (Followers: 2, SJR: 0.3, CiteScore: 1)
Global Business and Economics Review     Hybrid Journal   (Followers: 3, SJR: 0.154, CiteScore: 0)
Interdisciplinary Environmental Review     Hybrid Journal   (Followers: 3)
Intl. J. of Abrasive Technology     Hybrid Journal   (Followers: 2, SJR: 0.279, CiteScore: 0)
Intl. J. of Accounting and Finance     Hybrid Journal   (Followers: 18)
Intl. J. of Accounting, Auditing and Performance Evaluation     Hybrid Journal   (Followers: 16, SJR: 0.14, CiteScore: 0)
Intl. J. of Ad Hoc and Ubiquitous Computing     Hybrid Journal   (Followers: 8, SJR: 0.21, CiteScore: 1)
Intl. J. of Adaptive and Innovative Systems     Hybrid Journal   (Followers: 1)
Intl. J. of Additive and Subtractive Materials Manufacturing     Hybrid Journal   (Followers: 5)
Intl. J. of Advanced Intelligence Paradigms     Hybrid Journal   (Followers: 5, SJR: 0.144, CiteScore: 1)
Intl. J. of Advanced Mechatronic Systems     Hybrid Journal   (Followers: 3, SJR: 0.132, CiteScore: 0)
Intl. J. of Advanced Media and Communication     Hybrid Journal   (Followers: 26, SJR: 0.124, CiteScore: 0)
Intl. J. of Advanced Operations Management     Hybrid Journal   (Followers: 9, SJR: 0.163, CiteScore: 0)
Intl. J. of Aerodynamics     Hybrid Journal   (Followers: 32)
Intl. J. of Agent-Oriented Software Engineering     Hybrid Journal   (Followers: 3)
Intl. J. of Agile and Extreme Software Development     Hybrid Journal   (Followers: 5)
Intl. J. of Agile Systems and Management     Hybrid Journal   (Followers: 5, SJR: 0.878, CiteScore: 3)
Intl. J. of Agricultural Resources, Governance and Ecology     Hybrid Journal   (Followers: 2, SJR: 0.152, CiteScore: 0)
Intl. J. of Agriculture Innovation, Technology and Globalisation     Hybrid Journal  
Intl. J. of Alternative Propulsion     Hybrid Journal   (Followers: 14)
Intl. J. of Applied Cryptography     Hybrid Journal   (Followers: 9, SJR: 0.455, CiteScore: 3)
Intl. J. of Applied Decision Sciences     Hybrid Journal   (Followers: 1, SJR: 0.275, CiteScore: 1)
Intl. J. of Applied Management Science     Hybrid Journal   (Followers: 4, SJR: 0.229, CiteScore: 0)
Intl. J. of Applied Nonlinear Science     Hybrid Journal   (Followers: 1)
Intl. J. of Applied Pattern Recognition     Hybrid Journal   (Followers: 8)
Intl. J. of Applied Systemic Studies     Hybrid Journal   (SJR: 0.129, CiteScore: 0)
Intl. J. of Arab Culture, Management and Sustainable Development     Hybrid Journal   (Followers: 7)
Intl. J. of Artificial Intelligence and Soft Computing     Hybrid Journal   (Followers: 11)
Intl. J. of Arts and Technology     Hybrid Journal   (Followers: 6, SJR: 0.225, CiteScore: 1)
Intl. J. of Auditing Technology     Hybrid Journal   (Followers: 5)
Intl. J. of Automation and Control     Hybrid Journal   (Followers: 11, SJR: 0.189, CiteScore: 1)
Intl. J. of Automation and Logistics     Hybrid Journal   (Followers: 5)
Intl. J. of Automotive Composites     Hybrid Journal   (Followers: 5)
Intl. J. of Automotive Technology and Management     Hybrid Journal   (Followers: 6, SJR: 0.374, CiteScore: 1)
Intl. J. of Autonomic Computing     Hybrid Journal   (Followers: 2)
Intl. J. of Autonomous and Adaptive Communications Systems     Hybrid Journal   (Followers: 3, SJR: 0.128, CiteScore: 0)
Intl. J. of Aviation Management     Hybrid Journal   (Followers: 7)
Intl. J. of Banking, Accounting and Finance     Hybrid Journal   (Followers: 16, SJR: 0.137, CiteScore: 0)
Intl. J. of Behavioural Accounting and Finance     Hybrid Journal   (Followers: 11)
Intl. J. of Behavioural and Healthcare Research     Hybrid Journal   (Followers: 8)
Intl. J. of Bibliometrics in Business and Management     Hybrid Journal   (Followers: 2)
Intl. J. of Big Data Intelligence     Hybrid Journal   (Followers: 24)
Intl. J. of Bio-Inspired Computation     Hybrid Journal   (Followers: 1, SJR: 0.721, CiteScore: 4)
Intl. J. of Bioinformatics Research and Applications     Hybrid Journal   (Followers: 16, SJR: 0.157, CiteScore: 0)
Intl. J. of Biomechatronics and Biomedical Robotics     Hybrid Journal   (Followers: 4)
Intl. J. of Biomedical Engineering and Technology     Hybrid Journal   (Followers: 5, SJR: 0.205, CiteScore: 1)
Intl. J. of Biomedical Nanoscience and Nanotechnology     Hybrid Journal   (Followers: 7)
Intl. J. of Biometrics     Hybrid Journal   (Followers: 5, SJR: 0.155, CiteScore: 0)
Intl. J. of Biotechnology     Hybrid Journal   (Followers: 6, SJR: 0.269, CiteScore: 1)
Intl. J. of Blockchains and Cryptocurrencies     Hybrid Journal  
Intl. J. of Bonds and Derivatives     Hybrid Journal   (Followers: 1)
Intl. J. of Business and Data Analytics     Hybrid Journal  
Intl. J. of Business and Emerging Markets     Hybrid Journal   (Followers: 2)
Intl. J. of Business and Globalisation     Hybrid Journal   (Followers: 3, SJR: 0.263, CiteScore: 1)
Intl. J. of Business and Systems Research     Hybrid Journal   (Followers: 1, SJR: 0.104, CiteScore: 0)
Intl. J. of Business Competition and Growth     Hybrid Journal   (Followers: 5)
Intl. J. of Business Continuity and Risk Management     Hybrid Journal   (Followers: 15)
Intl. J. of Business Environment     Hybrid Journal   (Followers: 3)
Intl. J. of Business Excellence     Hybrid Journal   (Followers: 4, SJR: 0.274, CiteScore: 1)
Intl. J. of Business Forecasting and Marketing Intelligence     Hybrid Journal   (Followers: 6)
Intl. J. of Business Governance and Ethics     Hybrid Journal   (Followers: 6, SJR: 0.171, CiteScore: 0)
Intl. J. of Business Information Systems     Hybrid Journal   (Followers: 17, SJR: 0.266, CiteScore: 1)
Intl. J. of Business Innovation and Research     Hybrid Journal   (Followers: 11, SJR: 0.28, CiteScore: 1)
Intl. J. of Business Intelligence and Data Mining     Hybrid Journal   (Followers: 30, SJR: 0.249, CiteScore: 2)
Intl. J. of Business Intelligence and Systems Engineering     Hybrid Journal  
Intl. J. of Business Performance and Supply Chain Modelling     Hybrid Journal   (Followers: 18, SJR: 0.18, CiteScore: 0)
Intl. J. of Business Performance Management     Hybrid Journal   (Followers: 9, SJR: 0.197, CiteScore: 1)
Intl. J. of Business Process Integration and Management     Hybrid Journal   (Followers: 12, SJR: 0.149, CiteScore: 1)
Intl. J. of Chinese Culture and Management     Hybrid Journal   (Followers: 4)
Intl. J. of Circuits and Architecture Design     Hybrid Journal   (Followers: 6)
Intl. J. of Cloud Computing     Hybrid Journal   (Followers: 25)
Intl. J. of Cognitive Biometrics     Hybrid Journal   (Followers: 3)
Intl. J. of Cognitive Performance Support     Hybrid Journal   (Followers: 4)
Intl. J. of Collaborative Engineering     Hybrid Journal   (Followers: 1)
Intl. J. of Collaborative Enterprise     Hybrid Journal   (Followers: 1)
Intl. J. of Collaborative Intelligence     Hybrid Journal   (Followers: 3)
Intl. J. of Communication Networks and Distributed Systems     Hybrid Journal   (Followers: 7, SJR: 0.177, CiteScore: 1)
Intl. J. of Comparative Management     Hybrid Journal  
Intl. J. of Competitiveness     Hybrid Journal   (Followers: 3)
Intl. J. of Complexity in Applied Science and Technology     Hybrid Journal  
Intl. J. of Complexity in Leadership and Management     Hybrid Journal   (Followers: 28)
Intl. J. of Computational Biology and Drug Design     Hybrid Journal   (Followers: 1, SJR: 0.231, CiteScore: 1)
Intl. J. of Computational Complexity and Intelligent Algorithms     Hybrid Journal   (Followers: 2)
Intl. J. of Computational Economics and Econometrics     Hybrid Journal   (Followers: 5)
Intl. J. of Computational Intelligence in Bioinformatics and Systems Biology     Hybrid Journal   (Followers: 13)
Intl. J. of Computational Intelligence Studies     Hybrid Journal   (Followers: 3)
Intl. J. of Computational Materials Science and Surface Engineering     Hybrid Journal   (Followers: 6, SJR: 0.135, CiteScore: 0)
Intl. J. of Computational Science and Engineering     Hybrid Journal   (Followers: 2, SJR: 0.373, CiteScore: 1)
Intl. J. of Computational Systems Engineering     Hybrid Journal   (Followers: 1)
Intl. J. of Computational Vision and Robotics     Hybrid Journal   (Followers: 5, SJR: 0.129, CiteScore: 0)
Intl. J. of Computer Aided Engineering and Technology     Hybrid Journal   (Followers: 3, SJR: 0.131, CiteScore: 0)
Intl. J. of Computer Applications in Technology     Hybrid Journal   (Followers: 1, SJR: 0.225, CiteScore: 1)
Intl. J. of Computers in Healthcare     Hybrid Journal   (Followers: 3)
Intl. J. of Computing Science and Mathematics     Hybrid Journal   (Followers: 1, SJR: 0.299, CiteScore: 1)
Intl. J. of Continuing Engineering Education and Life-Long Learning     Hybrid Journal   (Followers: 5, SJR: 0.196, CiteScore: 0)
Intl. J. of Convergence Computing     Hybrid Journal   (Followers: 2)
Intl. J. of Corporate Governance     Hybrid Journal   (Followers: 5)
Intl. J. of Corporate Strategy and Social Responsibility     Hybrid Journal   (Followers: 6)
Intl. J. of Creative Computing     Hybrid Journal   (Followers: 1)
Intl. J. of Critical Accounting     Hybrid Journal   (Followers: 3)
Intl. J. of Critical Computer-Based Systems     Hybrid Journal   (Followers: 1, SJR: 0.127, CiteScore: 0)
Intl. J. of Critical Infrastructures     Hybrid Journal   (Followers: 2, SJR: 0.173, CiteScore: 1)
Intl. J. of Data Analysis Techniques and Strategies     Hybrid Journal   (Followers: 17, SJR: 0.23, CiteScore: 0)
Intl. J. of Data Mining and Bioinformatics     Hybrid Journal   (Followers: 19, SJR: 0.217, CiteScore: 1)
Intl. J. of Data Mining, Modelling and Management     Hybrid Journal   (Followers: 14, SJR: 0.209, CiteScore: 0)
Intl. J. of Data Science     Hybrid Journal   (Followers: 10)
Intl. J. of Decision Sciences, Risk and Management     Hybrid Journal   (Followers: 9)
Intl. J. of Decision Support Systems     Hybrid Journal   (Followers: 2)
Intl. J. of Design Engineering     Hybrid Journal   (Followers: 12)
Intl. J. of Digital Culture and Electronic Tourism     Hybrid Journal   (Followers: 6)
Intl. J. of Digital Enterprise Technology     Hybrid Journal   (Followers: 1)
Intl. J. of Digital Signals and Smart Systems     Hybrid Journal   (Followers: 2)
Intl. J. of Diplomacy and Economy     Hybrid Journal   (Followers: 6)
Intl. J. of Dynamical Systems and Differential Equations     Hybrid Journal   (Followers: 1, SJR: 0.184, CiteScore: 0)
Intl. J. of Earthquake and Impact Engineering     Hybrid Journal   (Followers: 4)
Intl. J. of Economic Policy in Emerging Economies     Hybrid Journal   (Followers: 4, SJR: 0.134, CiteScore: 1)
Intl. J. of Economics and Accounting     Hybrid Journal   (Followers: 1)
Intl. J. of Economics and Business Research     Hybrid Journal   (Followers: 5, SJR: 0.129, CiteScore: 0)
Intl. J. of Education Economics and Development     Hybrid Journal   (Followers: 5, SJR: 0.156, CiteScore: 0)
Intl. J. of Electric and Hybrid Vehicles     Hybrid Journal   (Followers: 10, SJR: 0.225, CiteScore: 1)
Intl. J. of Electronic Banking     Hybrid Journal   (Followers: 5)
Intl. J. of Electronic Business     Hybrid Journal   (Followers: 2, SJR: 0.24, CiteScore: 0)
Intl. J. of Electronic Customer Relationship Management     Hybrid Journal   (Followers: 3, SJR: 0.148, CiteScore: 0)
Intl. J. of Electronic Democracy     Hybrid Journal   (Followers: 2)
Intl. J. of Electronic Finance     Hybrid Journal   (Followers: 5, SJR: 0.155, CiteScore: 0)
Intl. J. of Electronic Governance     Hybrid Journal   (SJR: 0.142, CiteScore: 1)
Intl. J. of Electronic Healthcare     Hybrid Journal   (Followers: 2, SJR: 0.254, CiteScore: 1)
Intl. J. of Electronic Marketing and Retailing     Hybrid Journal   (Followers: 7, SJR: 0.249, CiteScore: 1)
Intl. J. of Electronic Security and Digital Forensics     Hybrid Journal   (Followers: 8, SJR: 0.137, CiteScore: 0)
Intl. J. of Electronic Transport     Hybrid Journal   (Followers: 9)
Intl. J. of Embedded Systems     Hybrid Journal   (Followers: 5, SJR: 0.48, CiteScore: 1)
Intl. J. of Emergency Management     Hybrid Journal   (Followers: 11, SJR: 0.185, CiteScore: 0)
Intl. J. of Energy Technology and Policy     Hybrid Journal   (Followers: 7, SJR: 0.224, CiteScore: 0)
Intl. J. of Engineering Management and Economics     Hybrid Journal   (Followers: 4)
Intl. J. of Engineering Systems Modelling and Simulation     Hybrid Journal   (Followers: 8, SJR: 0.175, CiteScore: 0)
Intl. J. of Enterprise Network Management     Hybrid Journal   (SJR: 0.118, CiteScore: 0)
Intl. J. of Entrepreneurial Venturing     Hybrid Journal   (Followers: 1, SJR: 0.308, CiteScore: 1)
Intl. J. of Entrepreneurship and Innovation Management     Hybrid Journal   (Followers: 29, SJR: 0.255, CiteScore: 1)
Intl. J. of Entrepreneurship and Small Business     Hybrid Journal   (Followers: 30, SJR: 0.401, CiteScore: 1)
Intl. J. of Environment and Health     Hybrid Journal   (Followers: 5, SJR: 0.181, CiteScore: 0)
Intl. J. of Environment and Pollution     Hybrid Journal   (Followers: 2, SJR: 0.215, CiteScore: 1)
Intl. J. of Environment and Sustainable Development     Hybrid Journal   (Followers: 17, SJR: 0.132, CiteScore: 0)
Intl. J. of Environment and Waste Management     Hybrid Journal   (Followers: 4, SJR: 0.175, CiteScore: 0)
Intl. J. of Environment, Workplace and Employment     Hybrid Journal   (Followers: 6, SJR: 0.117, CiteScore: 0)
Intl. J. of Environmental Engineering     Hybrid Journal   (Followers: 6)
Intl. J. of Environmental Policy and Decision Making     Hybrid Journal   (Followers: 2)
Intl. J. of Environmental Technology and Management     Hybrid Journal   (Followers: 1, SJR: 0.141, CiteScore: 0)
Intl. J. of Exergy     Hybrid Journal   (Followers: 3, SJR: 0.396, CiteScore: 1)
Intl. J. of Experimental and Computational Biomechanics     Hybrid Journal   (Followers: 8)
Intl. J. of Experimental Design and Process Optimisation     Hybrid Journal   (Followers: 7)
Intl. J. of Export Marketing     Hybrid Journal   (Followers: 3)
Intl. J. of Financial Engineering and Risk Management     Hybrid Journal   (Followers: 4)
Intl. J. of Financial Innovation in Banking     Hybrid Journal   (Followers: 3)
Intl. J. of Financial Markets and Derivatives     Hybrid Journal   (Followers: 5)
Intl. J. of Financial Services Management     Hybrid Journal   (Followers: 1)
Intl. J. of Food Safety, Nutrition and Public Health     Hybrid Journal   (Followers: 21)
Intl. J. of Forensic Engineering     Hybrid Journal   (Followers: 3)
Intl. J. of Forensic Engineering and Management     Hybrid Journal   (Followers: 3)
Intl. J. of Foresight and Innovation Policy     Hybrid Journal   (Followers: 7, SJR: 0.115, CiteScore: 0)
Intl. J. of Functional Informatics and Personalised Medicine     Hybrid Journal   (Followers: 4)
Intl. J. of Fuzzy Computation and Modelling     Hybrid Journal   (Followers: 2)
Intl. J. of Gender Studies in Developing Societies     Hybrid Journal   (Followers: 5)
Intl. J. of Global Energy Issues     Hybrid Journal   (Followers: 8, SJR: 0.199, CiteScore: 0)
Intl. J. of Global Environmental Issues     Hybrid Journal   (Followers: 3, SJR: 0.153, CiteScore: 0)
Intl. J. of Global Warming     Hybrid Journal   (Followers: 2, SJR: 0.259, CiteScore: 1)
Intl. J. of Globalisation and Small Business     Hybrid Journal   (Followers: 14, SJR: 0.233, CiteScore: 1)
Intl. J. of Governance and Financial Intermediation     Hybrid Journal  
Intl. J. of Granular Computing, Rough Sets and Intelligent Systems     Hybrid Journal   (Followers: 3)
Intl. J. of Green Economics     Hybrid Journal   (Followers: 6, SJR: 0.209, CiteScore: 0)
Intl. J. of Grid and Utility Computing     Hybrid Journal   (SJR: 0.341, CiteScore: 2)
Intl. J. of Happiness and Development     Hybrid Journal   (Followers: 8)
Intl. J. of Healthcare Policy     Hybrid Journal  
Intl. J. of Healthcare Technology and Management     Hybrid Journal   (Followers: 7, SJR: 0.139, CiteScore: 0)
Intl. J. of Heavy Vehicle Systems     Hybrid Journal   (Followers: 7, SJR: 0.23, CiteScore: 0)
Intl. J. of High Performance Computing and Networking     Hybrid Journal   (Followers: 4, SJR: 0.428, CiteScore: 1)
Intl. J. of High Performance Systems Architecture     Hybrid Journal   (Followers: 6, SJR: 0.116, CiteScore: 0)
Intl. J. of Higher Education and Sustainability     Hybrid Journal   (Followers: 5)
Intl. J. of Hospitality and Event Management     Hybrid Journal   (Followers: 4)
Intl. J. of Human Factors and Ergonomics     Hybrid Journal   (Followers: 20, SJR: 0.117, CiteScore: 0)
Intl. J. of Human Factors Modelling and Simulation     Hybrid Journal   (Followers: 17)
Intl. J. of Human Resources Development and Management     Hybrid Journal   (Followers: 29, SJR: 0.162, CiteScore: 0)
Intl. J. of Human Rights and Constitutional Studies     Hybrid Journal   (Followers: 14)
Intl. J. of Humanitarian Technology     Hybrid Journal  
Intl. J. of Hybrid Intelligence     Hybrid Journal  
Intl. J. of Hydrology Science and Technology     Hybrid Journal   (Followers: 8, SJR: 0.43, CiteScore: 2)
Intl. J. of Hydromechatronics     Hybrid Journal  
Intl. J. of Image Mining     Hybrid Journal   (Followers: 1)
Intl. J. of Immunological Studies     Hybrid Journal   (Followers: 1)
Intl. J. of Indian Culture and Business Management     Hybrid Journal  
Intl. J. of Industrial and Systems Engineering     Hybrid Journal   (Followers: 11, SJR: 0.34, CiteScore: 1)

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Similar Journals
Journal Cover
International Journal of High Performance Computing and Networking
Journal Prestige (SJR): 0.428
Citation Impact (citeScore): 1
Number of Followers: 4  
 
  Hybrid Journal Hybrid journal (It can contain Open Access articles)
ISSN (Print) 1740-0562 - ISSN (Online) 1740-0570
Published by Inderscience Publishers Homepage  [443 journals]
  • Telecom customer clustering via glowworm swarm optimisation algorithm
    • Authors: Yanli Liu, Mengyu Zhu
      Pages: 397 - 404
      Abstract: The glowworm swarm optimisation (GSO) algorithm is a novel algorithm with the simultaneous computation of multiple optima of multimodal functions. Data-clustering techniques are classification algorithms that have a wide range of applications. Since K-means algorithm is easy to fall into the local optimum by the selection of initial clustering centre, GSO algorithm is used for the telecom customers clustering. The customer consumption data is extracted by means of the recency frequency monetary (RFM) model and the standardised data is clustered automatically using the GSO algorithm's synchronous optimisation ability. In the clustering optimisation algorithm, adaptive step size is used instead of the original fixed step size to avoid local optimisation of the algorithm and obtain higher accuracy. Compared with K-means clustering algorithm, GSO approach can automatically generate the number of clusters and use RFM model to reduce effectively the size of the data processing. The results of the experiments demonstrate that the GSO-based clustering technique is a promising technique for the data clustering problems.
      Keywords: glowworm swarm optimisation; customer's subdivision; data clustering; high performance computing
      Citation: International Journal of High Performance Computing and Networking, Vol. 14, No. 4 (2019) pp. 397 - 404
      PubDate: 2019-09-23T23:20:50-05:00
      DOI: 10.1504/IJHPCN.2019.102345
      Issue No: Vol. 14, No. 4 (2019)
       
  • A comparative study on automatic parallelisation tools and methods to
           improve their usage
    • Authors: S. Prema, R. Jehadeesan, B.K. Panigrahi
      Pages: 405 - 415
      Abstract: Automatic parallelisation assists users in parallelising the serial code even without acquiring knowledge about the application. Auto-parallelisers focus on loop-level parallelisation and dependence analysis. Apart from dependences present within the loop, specific coding complexities make the code not amenable to parallelisation due to the limitations of the parallelising tool. To overcome these programming complications, we can explore the possibility of minimal manual intervention to make the code suitable for parallelisation. This paper provides a study of currently available auto-parallelisers and their competence on parallelisation of different programming features. The pitfalls faced by these tools are unveiled and categorised for detailed analysis. A solution-based approach in the form of coding changes circumvents the pitfalls and achieves efficient parallelisation. It also underlines the overall capability of the tools in supporting programming features during parallelisation.
      Keywords: automatic parallelisation; open multi-processing; OpenMP parallel programming; coding complexities; loop parallelisation
      Citation: International Journal of High Performance Computing and Networking, Vol. 14, No. 4 (2019) pp. 405 - 415
      PubDate: 2019-09-23T23:20:50-05:00
      DOI: 10.1504/IJHPCN.2019.102346
      Issue No: Vol. 14, No. 4 (2019)
       
  • FollowMe: a mobile crowd sensing platform for spatial-temporal
           data sharing
    • Authors: S. Prema, R. Jehadeesan, B.K. Panigrahi
      Pages: 416 - 424
      Abstract: Mobile crowd sensing becomes a promising solution for massive data collection with the public participation. Besides the challenges of user incentives, and diversified data sources and quality, the requirement of sharing spatial-temporal data drives the privacy concerns of contributors as one of the top priorities in the design and implementation of a sound crowdsourcing platform. In this paper, <i>FollowMe</i> is introduced as a use case of mobile crowd sensing platform to explain possible design guidelines and solutions to address these challenges. The incentive mechanisms are discussed according to both the quantity and quality of users' contributions. Then, a k-anonymity based solution is applied to protect contributors' privacy in both scenarios of trustworthy and untrustworthy crowdsourcers. Thereafter, a reputation-based filtering solution is proposed to detect fake or malicious reports, and finally a density-based clustering algorithm is introduced to find hotspots which can help the prediction of future events. Although <i>FollowMe</i> is designed for a virtual world of the popular mobile game Pokémon Go, the solutions and discussions are supposed to be applicable to more complex applications sharing spatial-temporal data about users.
      Keywords: mobile crowd sensing; spatial-temporal data; crowdsourcing; privacy; k-anonymity; hotspot; reputation; incentive mechanism
      Citation: International Journal of High Performance Computing and Networking, Vol. 14, No. 4 (2019) pp. 416 - 424
      PubDate: 2019-09-23T23:20:50-05:00
      DOI: 10.1504/IJHPCN.2019.102347
      Issue No: Vol. 14, No. 4 (2019)
       
  • A novel graph compression algorithm for data-intensive scientific
           networks
    • Authors: Xiao Lin, Haizhou Du, Shenshen Chen
      Pages: 425 - 434
      Abstract: As one of the world's leading scientific and data-intensive computing grids, the worldwide LHC computing grid (WLCG) faces the challenge of improving its computing efficiency and network utilisation. To achieve this goal, WLCG needs an important piece of information: the network topology graphs of participating computing grids. Directly collecting such information from all of the grids, however, would cause high communication overhead and raise many security issues. In this paper, we address these issues by proposing a novel algorithm to compress such a large network topology into a compact, equivalent network topology. We formally define our problem, develop a novel, efficient topology compression algorithm and evaluate its performance using real-world network topologies. Our results show that our algorithm not only achieves a much higher topology compression ratio than state-of-the-art topology transformation algorithms, but also leads to at most 100× reduction in computation time.
      Keywords: network topology; data-intensive; compression; shortest path tree; SPT; weighted graph; high performance networking
      Citation: International Journal of High Performance Computing and Networking, Vol. 14, No. 4 (2019) pp. 425 - 434
      PubDate: 2019-09-23T23:20:50-05:00
      DOI: 10.1504/IJHPCN.2019.102348
      Issue No: Vol. 14, No. 4 (2019)
       
  • Outlier detection of time series with a novel hybrid method in cloud
           computing
    • Authors: Qi Liu, Zhen Wang, Xiaodong Liu, Nigel Linge
      Pages: 435 - 443
      Abstract: In the wake of the developments in science and technology, cloud computing has obtained more attention in different fields. Meanwhile, outlier detection for data mining in cloud computing is playing significant role in different research domains and massive research works have been devoted to outlier detection. However, the existing available methods require lengthy computation time. Therefore, the improved algorithm of outlier detection, which has higher performance to detect outliers, is presented. In this paper, the proposed method, which is an improved spectral clustering algorithm (SKM++), is fit for handling outliers. Then, pruning data can reduce computational complexity and combine distance-based method Manhattan distance (<i>dist<SUB align="right">m</i>) to obtain outlier score. Finally, the method confirms the outlier by extreme analysis. This paper validates the presented method by experiments with real collected data by sensors and comparison against the existing approaches. The experimental results show that our proposed method outperforms the existing.
      Keywords: cloud computing; data mining; outlier detection; spectral clustering; Manhattan distance
      Citation: International Journal of High Performance Computing and Networking, Vol. 14, No. 4 (2019) pp. 435 - 443
      PubDate: 2019-09-23T23:20:50-05:00
      DOI: 10.1504/IJHPCN.2019.102350
      Issue No: Vol. 14, No. 4 (2019)
       
  • A priority-based queuing system for P2P-SIP call communications
           control
    • Authors: Mourad Amad, Djamil Aïssani, Razika Bouiche, Nouria Madi
      Pages: 444 - 452
      Abstract: Regarding the shortcoming of fundamental existing solutions for VoIP communications (e.g., SIP) based on centralisation, both academia and industry have initiated research projects that focus on the integration of peer-to-peer (P2P) paradigms into session initiation protocol (SIP) communication systems (e.g., P2P-SIP). P2P-SIP builds an overlay network to provide efficient, interoperable and flexible SIP-based services. In this paper, we propose a new model for critical calls, that takes into consideration the priority aspect of some specific requests (e.g., emergency calls). The proposed model is generic regarding the P2P underlying and physical architectures. For illustration purposes, we consider Gnutella, as a representative of unstructured P2P networks, and Chord, as a representative of structured P2P networks. In order to validate the proposed solution, a M/M/1 queuing model is considered. Performance evaluations show that the preliminary results are globally satisfactory and that our proposed model under certain conditions is relevant.
      Keywords: VoIP; peer-to-peer; session initiation protocol; P2P-SIP; calls control; priority; queuing systems
      Citation: International Journal of High Performance Computing and Networking, Vol. 14, No. 4 (2019) pp. 444 - 452
      PubDate: 2019-09-23T23:20:50-05:00
      DOI: 10.1504/IJHPCN.2019.102351
      Issue No: Vol. 14, No. 4 (2019)
       
  • Budget-aware task scheduling technique for efficient management of
           cloud resources
    • Authors: Mokhtar A. Alworafi, Atyaf Dhari, Sheren A. El-Booz, Suresha Mallappa
      Pages: 453 - 465
      Abstract: Cloud computing technology offers many services using pay as per use concept where the user gets to specify constraints such as the budget. Task scheduling algorithms are therefore the most preferred option under a budget constraint which is used to improve some of the metrics like makespan and cost. In this paper, we propose a budget-aware scheduling (BAS) model to schedule the tasks based on the budget constraint. At first, the VMs which meet the budget are labelled and the task priority is determined. Next, the task attributes are checked and assigned to the resources which meet the budget constraint to keep makespan as low as possible with minimal cost for resource usage. The experiments demonstrate that the proposed model outperforms other algorithms by reducing average of makespan, mean of average response time, and the cost of resources with an increase in resource utilisation and profit of provider.
      Keywords: cloud computing; scheduling; budget constraint; budget-aware scheduling; BAS; makespan; provider profit
      Citation: International Journal of High Performance Computing and Networking, Vol. 14, No. 4 (2019) pp. 453 - 465
      PubDate: 2019-09-23T23:20:50-05:00
      DOI: 10.1504/IJHPCN.2019.102352
      Issue No: Vol. 14, No. 4 (2019)
       
  • Sparse reconstruction of piezoelectric signal for phased array structural
           health monitoring
    • Authors: Yajie Sun, Feihong Gu, Sai Ji
      Pages: 466 - 472
      Abstract: Structural health monitoring technology has been widely used in the detection and identification of plate structure damage. Ultrasonic phased array technology has become an important method for structural health monitoring because of its flexible beam scanning and strong focusing performance. However, a large number of phased array signals will be produced, which leads to difficulty in storing, transmitting and processing. Therefore, under the condition of the signal being sparse, compressive sensing theory can make signal acquisition with much lower sampling rate than traditional Nyquist sampling theorem. Firstly, the sparse orthogonal transformation is used to make the sparse representation. Then, the measurement matrix is used for the projection observation. Besides, the reconstruction algorithm is used for sparse reconstruction. In this paper, the experimental verification of the antirust aluminium plate material is carried out. The experiment shows that the proposed method is useful for reconstructing the signal of phased array structure health monitoring.
      Keywords: structural health monitoring; ultrasonic phased array; compressive sensing; matching pursuit algorithm
      Citation: International Journal of High Performance Computing and Networking, Vol. 14, No. 4 (2019) pp. 466 - 472
      PubDate: 2019-09-23T23:20:50-05:00
      DOI: 10.1504/IJHPCN.2019.102354
      Issue No: Vol. 14, No. 4 (2019)
       
  • Malicious web pages detection using feature selection techniques and
           machine learning
    • Authors: Dharmaraj R. Patil, Jayantrao B. Patil
      Pages: 473 - 488
      Abstract: In recent years, researchers have provided significant solutions to detect malicious web pages, still there are many open issues. This paper proposes a methodology for the effective detection of malicious web pages using feature selection methods and machine learning. Our methodology consists of three modules: feature selection, training and classification. To evaluate our methodology, six feature selection methods and eight supervised machine learning classifiers are used. Experiments are performed on the balanced binary dataset. It is found that by using feature selection methods, the classifiers achieved significant detection accuracy of 94-99% and above, error-rate of 0.19-5.55%, FPR of 0.006-0.094, FNR of 0.000-0.013 with minimum system overhead. Our multi-model system using majority voting classifier and wrapper+Naive Bayes feature selection method with GreedyStepwise search technique using only 15 features achieved a highest accuracy of 99.15%, FPR of 0.017 and FNR of 0.000.
      Keywords: malicious web pages; feature selection; machine learning; supervised learning; multi-model system; web security; cyber security
      Citation: International Journal of High Performance Computing and Networking, Vol. 14, No. 4 (2019) pp. 473 - 488
      PubDate: 2019-09-23T23:20:50-05:00
      DOI: 10.1504/IJHPCN.2019.102355
      Issue No: Vol. 14, No. 4 (2019)
       
 
 
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