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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 Embedded Systems
Journal Prestige (SJR): 0.48
Citation Impact (citeScore): 1
Number of Followers: 5  
 
Hybrid Journal Hybrid journal   * Containing 1 Open Access Open Access article(s) in this issue *
ISSN (Print) 1741-1068 - ISSN (Online) 1741-1076
Published by Inderscience Publishers Homepage  [443 journals]
  • Microcontroller design for security system: implementation of a
           microcontroller based on STM32F103 microchip
    • Authors: Tabi Fouda Bernard Marie, Dezhe Han, Bowen An
      Pages: 541 - 550
      Abstract: In the monitoring system, the server can crash at any time; therefore a low-cost performant microcontroller is implemented to enable the server to reset after crashing while protecting its data core, and then be able to display in real time the information saved during the crash. This paper encompasses a complete successful designed and tested microcontroller based on STM32F103C8T6 microchip. The design of the microcontroller through a printed circuit board (PCB) prototype, peripherals and chips was assembled to reset the server from the relay chip. The connection and data communication between the microcontroller and the server are via universal serial bus (USB) and J-link connection. The design is also using the AES256encryption algorithm to protect the data of the system. The simulation results show that after the server crashes, it can easily restart and run, avoiding hassles with insurance of protecting the data core of the system.
      Keywords: STM32F103C8T6; microcontroller; J-link; universal serial bus; USB; server; relay; printed circuit board; PCB; AES256 encryption algorithm; security system; embedded systems
      Citation: International Journal of Embedded Systems, Vol. 11, No. 5 (2019) pp. 541 - 550
      PubDate: 2019-09-24T23:20:50-05:00
      DOI: 10.1504/IJES.2019.102440
      Issue No: Vol. 11, No. 5 (2019)
       
  • A dynamic cluster job scheduling optimisation algorithm based on data
           irreversibility in sensor cloud
    • Authors: Zeyu Sun, Jun Liu, Xiaofei Xing, Chuanfeng Li, Xiaoyan Pan
      Pages: 551 - 561
      Abstract: The optimisation algorithm based on irreversible data for the job scheduling of dynamic cluster is crucial to the improvement of the cluster rendering throughput and the cluster rendering efficiency. However, the dispatching imbalance of the cluster rendering task on the massive number of cluster rendering nodes will prolong the waiting time for the completion of job. Therefore, we propose dynamic cluster job scheduling optimisation algorithm based on data irreversibility (DCJS_DI). Firstly, we analyse the job scheduling target. Then, we exploit the frame independence with the clustering rendering and further establish the job scheduling model for the irreversible data dynamic cluster. Next, we elaborate on the job scheduling process of the irreversible data dynamic cluster and the dispatching process of the cluster rendering task. Finally, we investigate via simulation results the impacts of the job hunger and the resource fragmentation issue of the traditional job scheduling strategies on the system performance, the impacts of the multi-progress and multi-threading cluster rendering on the job completion time and the resource efficiency of the irreversible data dynamic cluster. We further study the extension of the cluster computation capability and the reliability issue of the cloud service.
      Keywords: sensor cloud; cluster rendering; job scheduling; data irreversibility
      Citation: International Journal of Embedded Systems, Vol. 11, No. 5 (2019) pp. 551 - 561
      PubDate: 2019-09-24T23:20:50-05:00
      DOI: 10.1504/IJES.2019.102427
      Issue No: Vol. 11, No. 5 (2019)
       
  • Design and application of real-time network abnormal traffic detection
           system based on Spark Streaming
    • Authors: FuCheng Pan, DeZhi Han, Yuping Hu
      Pages: 562 - 572
      Abstract: In order to realise the rapid analysis and identification of abnormal traffic in real-time networks, a distributed real-time network abnormal traffic detection system (DRNATDS) was designed, which could effectively analyse abnormal network traffic. DRNATDS provided effective real-time big data analysis platform and guaranteed network security. The paper proposes K-means algorithm based on relative density and distance, integrated with Spark Streaming and Kafka. It could effectively detect various network attacks under real-time data stream. The experimental results show that DRNATDS has good high availability and stability. Compared to other algorithms, K-means algorithm based on relative density and distance could more effectively identify abnormal network traffic and improve the recognition rate.
      Keywords: Spark Streaming; Kafka; network abnormal traffic identification; K-means
      Citation: International Journal of Embedded Systems, Vol. 11, No. 5 (2019) pp. 562 - 572
      PubDate: 2019-09-24T23:20:50-05:00
      DOI: 10.1504/IJES.2019.102428
      Issue No: Vol. 11, No. 5 (2019)
       
  • Big data and collective intelligence
    • Authors: Mirjana Ivanović, Aleksandra KlaÅ¡nja-Milićević
      Pages: 573 - 583
      Abstract: Nowadays the creation and accumulation of big data is an unavoidable process in a wide range of situations and scenarios. Smart environments and diverse sources of sensors, as well as the content created by humans, contribute to the big data's enormous size and characteristics. To make sense of the data, analyse and use these data, more and more efficient algorithms are being developed constantly. Still, the effectiveness of these algorithms depends on the specific nature of big data: analogue, noisy, implicit, and ambiguous. At the same time, there is the unavoidable scientific area of collective intelligence. It represents the capability of interconnected intelligences to collectively and more efficiently solve concrete problems than each individual intelligence would be able to do on its own. The paper presents an overview of recent achievements in big data and collective intelligence research areas. At the end, the perspectives and challenges of the common directions of these two areas will be discussed.
      Keywords: big data; big data generation and processing; cloud computing; collective intelligence; artificial intelligence techniques; cloud computing; high performance computing
      Citation: International Journal of Embedded Systems, Vol. 11, No. 5 (2019) pp. 573 - 583
      PubDate: 2019-09-24T23:20:50-05:00
      DOI: 10.1504/IJES.2019.102430
      Issue No: Vol. 11, No. 5 (2019)
       
  • DDoS attack detection based on global unbiased search strategy bee colony
           algorithm and artificial neural network
    • Authors: Qiuting Tian, Dezhi Han, Zhenxin Du
      Pages: 584 - 593
      Abstract: Distributed denial of service (DDoS) attacks are one of the common cyber threats today and are difficult to trace and prevent. The DDoS attack detection method for a single artificial neural network has the problems of slow convergence speed and easy to fall into local optimum. A DDoS attack detection method combining global unbiased search strategy bee colony algorithm and artificial neural network is proposed. This method uses the loss function of the artificial neural network as the objective function of the global unbiased search strategy bee colony algorithm. The optimal weights and thresholds are chosen as the initialisation parameters of the artificial neural network, in order to avoid the artificial neural network falling into a slow convergence speed and local optimum, thereby realising efficient DDoS attack detection. Experimental results show that the DDoS attack detection method has improved the detection accuracy, convergence speed and has good generalisation ability.
      Keywords: artificial neural network; ANN; artificial bee colony algorithm; ABC; distributed denial of service; DDoS; loss function; convergence speed; attack detection
      Citation: International Journal of Embedded Systems, Vol. 11, No. 5 (2019) pp. 584 - 593
      PubDate: 2019-09-24T23:20:50-05:00
      DOI: 10.1504/IJES.2019.102432
      Issue No: Vol. 11, No. 5 (2019)
       
  • Research on profit abilities of order placement strategies in pairs
           trading
    • Authors: Qiuting Tian, Dezhi Han, Zhenxin Du
      Pages: 594 - 601
      Abstract: This paper discusses profit abilities of three pairs-trading strategies. When spreads of one pair reach an entry threshold, traders submit limit orders for one lowly liquid stock and market orders for the other highly liquid stock. In order to research on profit abilities, this paper models spreads of that pair of stocks as an Ornstein-Uhlenbeck (OU) process and supposes execution time of limit orders as a random variable independent of spreads of the pair. Strategy 1 is a traditional pairs-trading strategy with market orders. Inversely, strategies 2 and 3 are pairs-trading strategies related to limit orders. Finally, this research finds out that pairs-trading strategies with limit orders can beat pairs-trading strategies with market orders through an empirical experiment with real-world data. The contribution of this paper is to analyse three strategies and verify that strategy 3 has the best performance when the investment threshold is low. The results of this paper can help investors to make rational investment.
      Keywords: pairs-trading; market order; limit order; Ornstein-Uhlenbeck process
      Citation: International Journal of Embedded Systems, Vol. 11, No. 5 (2019) pp. 594 - 601
      PubDate: 2019-09-24T23:20:50-05:00
      DOI: 10.1504/IJES.2019.102433
      Issue No: Vol. 11, No. 5 (2019)
       
  • Research on borrower's credit classification of P2P network loan based
           on LightGBM algorithm
    • Authors: Sen Zhang, Yuping Hu, Zhuoyi Tan
      Pages: 602 - 612
      Abstract: The credit classification of a borrower is the main method to effectively reduce the credit risk of P2P online loans. In this paper, LightGBM algorithm has the advantage in the high accuracy of data classification. Feature extraction, selection and reconstruction of the original data are performed by feature engineering. The One hot Encoding technology is used to re-encode the discretised feature indicators. Z-score data normalisation normalises the characteristics of continuous variables. Re-sort all feature indicators by contribution and perform PCA dimensionality reduction, and filter out effective feature indicators for training and testing. Finally, the problem of imbalance of samples and optimisation of model parameters is solved by ten-fold cross-validation. Result of simulation experiment shows that the LightGBM model has good stability, good fitting ability and high classification prediction accuracy.
      Keywords: P2P network loan; light gradient boosting machine; LightGBM; feature engineering; cross-validation; credit classification
      Citation: International Journal of Embedded Systems, Vol. 11, No. 5 (2019) pp. 602 - 612
      PubDate: 2019-09-24T23:20:50-05:00
      DOI: 10.1504/IJES.2019.102434
      Issue No: Vol. 11, No. 5 (2019)
       
  • Differentially private geospatial data publication based on grid
           clustering
    • Authors: Dongni Yang, Songyan Li, Zhaobin Liu, Xinfeng Ye
      Pages: 613 - 623
      Abstract: Collecting geospatial data from location-based services can provide location evidence while analysing spatial information. However, releasing location data may result in the disclosure of sensitive personal information. The adaptive grid method (AG) uses differential privacy to protect information. In AG, the algorithm uses two levels of grids over data domain. However, it does not take into account the data distribution. Usually, the accuracy will be reduced in response to long-range counting queries. In this paper, the adjacent grid cells with similar data density are clustered together. Laplace noise is added to the clusters created by the clustering of the grid cells. The noisy count obtained from the grid cells that form each cluster is evenly redistributed to the grid cells in the cluster. Extensive experiments on real-world datasets showed that the query accuracy of the proposed method is higher than the existing methods.
      Keywords: differential privacy; grid clustering; big data privacy
      Citation: International Journal of Embedded Systems, Vol. 11, No. 5 (2019) pp. 613 - 623
      PubDate: 2019-09-24T23:20:50-05:00
      DOI: 10.1504/IJES.2019.102435
      Issue No: Vol. 11, No. 5 (2019)
       
  • HighPU: a high privacy-utility approach to mining frequent itemset
           with differential privacy
    • Authors: Yabin Wang, Yi Qiao, Zhaobin Liu, Zhiyi Huang
      Pages: 624 - 633
      Abstract: In the field of data mining, frequent itemset mining (FIM) is a popular technique for analysing transaction datasets and establishing the foundation of association rules. Publishing frequent itemsets, however presents privacy challenges. Differential privacy provides strong privacy assurance to users. In this paper, we study the problem of mining frequent itemsets under the rigorous differential privacy model. We propose an approach, called HighPU, which achieves both high data utility and high degree of privacy in FIM. HighPU begins by truncating transactions over the original dataset. Then HighPU directly searches for maximal frequent itemsets. And we use a consistent approach to improve the accuracy of the results. Extensive experiments using several real datasets illustrate that HighPU significantly outperforms the current state of the art.
      Keywords: differential privacy; frequent itemset mining; FIM; top-k itemsets; privacy protection
      Citation: International Journal of Embedded Systems, Vol. 11, No. 5 (2019) pp. 624 - 633
      PubDate: 2019-09-24T23:20:50-05:00
      DOI: 10.1504/IJES.2019.102436
      Issue No: Vol. 11, No. 5 (2019)
       
  • Cryptanalysis of the existing integrated PKE and PEKS schemes
    • Authors: Yang Lu, Qi Zeng
      Pages: 634 - 642
      Abstract: Public key encryption with keyword search (PEKS) is a useful cryptographic primitive which allows one to delegate to an untrusted storage server the capability of searching on publicly encrypted data without impacting the security and privacy of original data. However, due to lack of data encryption/decryption function, a PEKS scheme cannot be used alone but has to be coupled with a standard public key encryption (PKE) scheme. For this reason, a new cryptographic primitive called integrated PKE and PEKS (PKE/PEKS) was introduced by Baek et al. in 2006, which provides the functions of both PKE and PEKS. So far, several PKE/PEKS schemes have been proposed in the literature. However, none of them considers the keyword guessing attack. The first PKE/PEKS scheme proposed by Baek et al. was shown to be insecure under this attack. In this paper, we analyse the security of other PKE/PEKS schemes. We demonstrate that none of these schemes can resist the keyword guessing attack. The presented attacks show that a malicious storage server can successfully guess the keyword encoded in any keyword trapdoor produced by these schemes. Therefore, it is still an unsolved problem to devise a PKE/PEKS scheme withstanding the keyword guessing attack.
      Keywords: public key encryption; keyword search; PKE/PEKS; keyword guessing attack
      Citation: International Journal of Embedded Systems, Vol. 11, No. 5 (2019) pp. 634 - 642
      PubDate: 2019-09-24T23:20:50-05:00
      DOI: 10.1504/IJES.2019.102438
      Issue No: Vol. 11, No. 5 (2019)
       
  • A novel HHT and KS statistic approach to detect RoQ attack in wireless
           sensor network
    • Authors: Hongsong Chen, Zhongchuan Fu, Gang Wang
      Pages: 643 - 652
      Abstract: Reduction of quality (RoQ) attack is a special denial of service (DoS) attack. It is a serious threat to the security of wireless sensor network (WSN). The RoQ attack combines the attack effectiveness and the similarity to normal traffic, so it is difficult to detect by traditional methods. Hilbert-Huang transform (HHT) time frequency analysis method can be utilised to analyse the nonlinear small signal produced by RoQ attack. However, false IMF components are the challenge problems to detect the RoQ attack. Kolmogorov-Smirnov (KS) test approach is proposed to recognise the false intrinsic mode function (IMF) components. CC2530 system-on-chip is selected to build WSN experimental node. Ad hoc on-demand distance vector (AODV) routing protocol and random routing request (RREQ) flooding attack are simulated to implement RoQ attack in Zigbee wireless sensor network. Experimental results demonstrate that the novel approach is effective to detect RoQ attack in Zigbee WSN.
      Keywords: Hilbert-Huang transform; HHT; KS test; RoQ attack; WSN; intrusion detection
      Citation: International Journal of Embedded Systems, Vol. 11, No. 5 (2019) pp. 643 - 652
      PubDate: 2019-09-24T23:20:50-05:00
      DOI: 10.1504/IJES.2019.102439
      Issue No: Vol. 11, No. 5 (2019)
       
  • Research on user acceptance behaviour of mobile group intelligent sensing
           applications based on UTAUT
    • Authors: Xiaolong Ma, Yonghui Dai, Weining Tang, Guowei Li, Shengqi Lu
      Pages: 653 - 660
      Abstract: In the era of rapid development of the internet of things, group intelligence perception technology is widely used in various mobile APPs such as QQ, Alipay, Baidu map, etc. User's participation behaviour is a key factor in the system service quality and development. According to the analysis of the characteristics of group intelligence perception and the application development of mobile group intelligent sensing applications, we add the perceived trust, user acceptance and task technology matching to construct the UTAUT seven-factor model. Through the empirical test of 341 valid questionnaires collected in the survey, the results show that convenience conditions, perceived trust, performance expectations, effort expectations and task technology matching have a significant impact on users' willingness to adopt. Finally, based on the experimental results, we propose effective countermeasures and suggestions for the development of mobile group intelligent sensing applications.
      Keywords: group intelligence perception; mobile group intelligent sensing applications; unified theory of acceptance and use of technology; UTAUT; structural equation model
      Citation: International Journal of Embedded Systems, Vol. 11, No. 5 (2019) pp. 653 - 660
      PubDate: 2019-09-24T23:20:50-05:00
      DOI: 10.1504/IJES.2019.102431
      Issue No: Vol. 11, No. 5 (2019)
       
  • A design methodology for mobile and embedded applications on FPGA-based
           dynamic reconfigurable hardware
    • Authors: Darshika G. Perera, Kin Fun Li
      Pages: 661 - 677
      Abstract: With the proliferation of mobile/embedded devices, multiple running applications are becoming a necessity on these devices. Thus, state-of-the-art techniques are needed to support complex applications running on mobile systems. We envision in the near future, many mobile devices will be implemented/delivered on FPGA-based reconfigurable chips. Previous analysis illustrated that FPGA-based dynamic-reconfigurable-hardware is currently the best option to deliver embedded applications that have stringent requirements. However, computation models and application characteristics play significant roles in determining whether this hardware is indeed a good match for specific embedded applications. Furthermore, selecting a specific dynamic reconfiguration method (out of many) and designing the corresponding hardware architectures for an application are important and challenging tasks. This paper proposes a design methodology for FPGA-based dynamic-reconfigurable-hardware that provides guidelines in mapping application's computation models and characteristics to the most suitable reconfiguration methods. Pipelined and functional-parallel models are used as case studies to illustrate the design methodology.
      Keywords: design methodology; mobile applications; embedded applications; FPGA-based dynamic reconfigurable hardware; FPGAs; mobile devices; embedded systems; dynamic reconfiguration; mapping pipelined computation model to FPGAs; mapping functional paralle
      Citation: International Journal of Embedded Systems, Vol. 11, No. 5 (2019) pp. 661 - 677
      PubDate: 2019-09-24T23:20:50-05:00
      DOI: 10.1504/IJES.2019.102416
      Issue No: Vol. 11, No. 5 (2019)
       
  • Research on modelling and scheduling strategy for mine transportation
           control system based on CPS

         This is an Open Access Article Open Access Article

    • Authors: Jingzhao Li, Dayu Yang, Xiaoming Zhang
      Pages: 678 - 686
      Abstract: Cyber-physical systems (CPS) have made great strides in industrial control, intelligent transportation, remote medical and other fields. Coal mine transportation control system is a representative multi-subsystem of CPS. In this study, for the sake of optimising the scheduling mechanism for event response and precise control of tramcar behaviour in the system, we propose an event-orient scheduling algorithm (EOSA) to achieve a rapid response based on building a no-memory continuous time model. Therefore, the control system can match tasks in the queue according to the real-time load situation, and each physical entity can accurately execute the instruction under discrete event environment. Simulation results have shown that the proposed algorithm has a higher execution speed compared with the hybrid genetic algorithm and fuzzy clustering scheduling algorithm. Our approach realises the load balancing of global task scheduling and is more suitable for mine transportation scenario.
      Keywords: cyber-physical systems; CPS; mathematical model construction; scheduling strategy; priority queuing; mine transportation
      Citation: International Journal of Embedded Systems, Vol. 11, No. 5 (2019) pp. 678 - 686
      PubDate: 2019-09-24T23:20:50-05:00
      DOI: 10.1504/IJES.2019.102437
      Issue No: Vol. 11, No. 5 (2019)
       
 
 
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