Information Analytics in Wireless Systems and Internet of Things

Submission Deadline: 30 May 2022 (closed)

Guest Editors

Dr. Sathishkumar Karupusamy, Bharathiar University, India.
Dr. M. Ramalingam, Bharathiar University, India.


The use of Online Social Networks is developing each day in millions with the presentation of remote frameworks and Internet of Things. The development of shrewd devises assists with making new age information sharing stage. Information Analytics has a significant task to carry out in the development and accomplishment of remote and IoT applications. The development of information has gotten exponential and it is hard to examine. Numerous scientists rely upon the information accessible on Wireless Systems and IoT for growing new age administrations and applications. This Special issue hopes to examine and address the issues and difficulties of Data Analytics in remote frameworks and IoT The editors will look for articles that address various parts of Data Analytics comprises of novel procedures dependent on remote frameworks and IoT including AI, streamlining, control, measurements, and the social registering and so on.


Models of Wireless Systems and IoT
Data perception and investigation
Privacy, trust and notoriety in remote frameworks and IoT
Applications on complex correspondence organizations
Trust in Social Networks
Big Data Analytics and IoT
Mobile Cloud and Data Analytics
Data Analytics in Health, Business and Education Services
QoS and QoE Models and Architectures
Context Aware Services and Models
Mobile Edge Computing
Software-characterized remote organizations
Network security

Published Papers

  • Open Access


    Improving the Transmission Efficiency of a WSN with the IACO Algorithm

    Wen-Tsai Sung, Sung-Jung Hsiao
    Computer Systems Science and Engineering, Vol.47, No.1, pp. 1061-1076, 2023, DOI:10.32604/csse.2023.032700
    (This article belongs to this Special Issue: Information Analytics in Wireless Systems and Internet of Things)
    Abstract The goal of this study is to reduce the energy consumption of the sensing network and enhance the overall life cycle of the network. This study proposes a data fusion algorithm for wireless sensor networks based on improved ant colony optimization (IACO) to reduce the amount of data transmitted by wireless sensor networks (WSN). This study updates pheromones for multiple optimal routes to improve the global optimal route in search function. The algorithm proposed in this study can reduce node energy consumption, improve network load balancing and prolong network life cycle. Through data fusion, regression analysis model and information processing… More >

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