Segment routing for WSN using hybrid optimization with energy-efficient game theory-based clustering technique

被引:0
|
作者
Sangeetha, S. [1 ]
Victoire, T. Aruldoss Albert [2 ]
Premkumar, M. [3 ]
Sowmya, R. [4 ]
机构
[1] Karpagam Coll Engn, Comp Sci & Engn, Coimbatore, India
[2] Anna Univ Reg Campus, Elect & Elect Engn, Coimbatore, India
[3] Dayananda Sagar Coll Engn, Dept Elect & Elect Engn, Bengaluru, India
[4] Manipal Acad Higher Educ, Manipal Inst Technol, Dept Elect & Elect Engn, Manipal 576104, Karnataka, India
关键词
Segment routing; game theory-based clustering; hybrid optimization; improved pelican algorithm; wireless sensor networks;
D O I
10.1080/00051144.2024.2431750
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
This research focuses on Wireless Sensor Networks (WSNs) and proposes a three-phase approach to achieve energy-efficient routing. The approach consists of node deployment using Voronoi diagrams, clustering, and Cluster Head (CH) selection using energy-efficient game theory, and a routing strategy based on Improved Pelican Optimization (ImPe) segment routing. Random deployment of sensor nodes in WSNs can lead to coverage issues, and hence, in order to address this, Voronoi-based node deployment is employed to ensure uniform and balanced coverage of the monitoring area. An energy-efficient game theory-based approach is used for CH selection by considering the energy levels to select CHs for enhancing network longevity. The proposed routing mechanism utilizes segment routing, which provides deterministic routing paths from CHs to the sink (Base Station). Segment routing eliminates the need for route discovery and maintenance, making it energy-efficient. The ImPe algorithm that works on the characteristics of pelican search agents is employed to choose the optimal segment path for information sharing. The assessment based on delay, network lifetime, packet delivery ratio, residual energy, throughput, communication overhead, and energy utilization acquired the values of 2.57, 98.59, 98.29, 0.98, 238.51, 7.71, and 0.02 respectively.
引用
收藏
页码:24 / 42
页数:19
相关论文
共 50 条
  • [21] Energy-efficient Clustering Routing Protocol Based on Weight
    Sun, Yanjing
    Chen, Wei
    Zhang, Bei
    Liu, Xue
    Gu, Xiangping
    2009 INTERNATIONAL CONFERENCE ON WIRELESS COMMUNICATIONS AND SIGNAL PROCESSING (WCSP 2009), 2009, : 1089 - 1093
  • [22] Energy-efficient resource optimization using game theory in hybrid NOMA assisted cognitive radio networks
    Kumar, Ashok
    Kumar, Krishan
    PHYSICAL COMMUNICATION, 2021, 47
  • [23] A Markov game theory-based energy balance routing algorithm
    Guangxi Key Laboratory of Trusted Software , Guilin, Guangxi 541004, China
    不详
    不详
    Jisuanji Xuebao, 2013, 7 (1500-1508):
  • [24] An Density-based Energy-efficient Routing Algorithm in Wireless Sensor Networks Using Game Theory
    Xu, Zhanyang
    Yin, Yue
    Wang, Jin
    INTERNATIONAL JOURNAL OF FUTURE GENERATION COMMUNICATION AND NETWORKING, 2012, 5 (04): : 99 - 112
  • [25] Energy-efficient clustering protocol for WSN based on improved black widow optimization and fuzzy logic
    Sheriba, S. T.
    Rajesh, D. Hevin
    TELECOMMUNICATION SYSTEMS, 2021, 77 (01) : 213 - 230
  • [26] Energy-efficient clustering protocol for WSN based on improved black widow optimization and fuzzy logic
    S. T. Sheriba
    D. Hevin Rajesh
    Telecommunication Systems, 2021, 77 : 213 - 230
  • [27] Energy-efficient routing protocol and optimized passive clustering in WSN for SMART grid applications
    Vinodha, Ramalingam
    Durairaj, Sundarraj
    Padmavathi, Sakkarai
    INTERNATIONAL JOURNAL OF COMMUNICATION SYSTEMS, 2022, 35 (01)
  • [28] Ring-Based Security Energy-Efficient Routing Protocol for WSN
    Liu Mengyao
    Zhang Yanyan
    Xia Li
    26TH CHINESE CONTROL AND DECISION CONFERENCE (2014 CCDC), 2014, : 1892 - 1897
  • [29] Energy Efficient Networks Using Ant Colony Optimization with Game Theory Clustering
    Gunigari, Harish
    Chitra, S.
    INTELLIGENT AUTOMATION AND SOFT COMPUTING, 2023, 35 (03): : 3557 - 3571
  • [30] A Hybrid Mayfly-Aquila Optimization Algorithm Based Energy-Efficient Clustering Routing Protocol for Wireless Sensor Networks
    Natesan, Gobi
    Konda, Srinivas
    Perez de Prado, Rocio
    Wozniak, Marcin
    SENSORS, 2022, 22 (17)