Clustering-based Optimized HEED protocols for WSNs using bacterial foraging optimization and fuzzy logic system

被引:21
|
作者
Gupta, Prateek [1 ]
Sharma, Ajay K. [2 ]
机构
[1] Dr BR Ambedkar Natl Inst Technol, Dept Comp Sci & Engn, Jalandhar, Punjab, India
[2] Natl Inst Technol, Dept Comp Sci & Engn, New Delhi, India
关键词
Clustering; Wireless sensor networks; Load balancing; Network lifetime; HEED; Bacterial foraging optimization algorithm; Fuzzy logic system; WIRELESS SENSOR NETWORKS; ENERGY EFFICIENCY; ALGORITHM;
D O I
10.1007/s00500-017-2837-7
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Proficient clustering method has a vital role in organizing sensor nodes in wireless sensor networks (WSNs), utilizing their energy resources efficiently and providing longevity to network. Hybrid energy-efficient distributed (HEED) protocol is one of the prominent clustering protocol in WSNs. However, it has few shortcomings, i.e., cluster heads (CHs) variation in consecutive rounds, more work load on CHs, uneven energy dissipation by sensor nodes, and formation of hot spots in network. By resolving these issues, one can enhance HEED capabilities to a greater extent. We have designed variants of Optimized HEED (OHEED) protocols named as HEED-1 Tier chaining (HEED1TC), HEED-2 Tier chaining (HEED2TC), ICHB-based OHEED-1 Tier chaining (ICOH1TC), ICHB-based OHEED-2 Tier chaining (ICOH2TC), ICHB-FL-based OHEED-1 Tier chaining (ICFLOH1TC), and ICHB-FL-based OHEED-2 Tier chaining (ICFLOH2TC) protocols. In HEED1TC and HEED2TC protocols, we have used chain-based intra-cluster and inter-cluster communication in HEED, respectively, for even load balancing among sensor nodes and to avoid more work load on CHs. Furthermore, for appropriate cluster formation, minimizing CHs variation in consecutive rounds and reducing complex uncertainties, we have used bacterial foraging optimization algorithm (BFOA)-inspired proposed intelligent CH selection based on BFOA (ICHB) algorithm for CH selection in ICOH1TC and ICOH2TC protocols. Likewise, in ICFLOH1TC and ICFLOH2TC protocols, we have used novel fuzzy set of rules additionally for CH selection to resolve the hot spots problem, proper CH selection covering whole network, and maximizing the network lifetime to a great extent. The simulation results showed that proposed OHEED protocols are able to handle above-discussed issues and provided far better results in comparison to HEED.
引用
收藏
页码:507 / 526
页数:20
相关论文
共 50 条
  • [21] Bacterial foraging based optimization design of fuzzy PID controllers
    Chen, Hung-Cheng
    [J]. ADVANCED INTELLIGENT COMPUTING THEORIES AND APPLICATIONS, PROCEEDINGS: WITH ASPECTS OF THEORETICAL AND METHODOLOGICAL ISSUES, 2008, 5226 : 841 - 849
  • [22] A Tuned Fuzzy Logic Relocation Model in WSNs Using Particle Swarm Optimization
    Rafiei, Ali
    Maali, Yashar
    Abolhasan, Mehran
    Franklin, Daniel
    Safaei, Farzad
    Smith, Stephen
    [J]. 2013 IEEE 78TH VEHICULAR TECHNOLOGY CONFERENCE (VTC FALL), 2013,
  • [23] A bacterial foraging optimization approach for tuning type-2 fuzzy logic controller
    Kiani, Mohammad
    Mohammadi, Seyed Mohammad Ali
    Gharaveisi, Ali Akbar
    [J]. TURKISH JOURNAL OF ELECTRICAL ENGINEERING AND COMPUTER SCIENCES, 2013, 21 (01) : 263 - 273
  • [24] Linear optimization and fuzzy-based clustering for WSNs assisted internet of things
    Maratha, Priti
    Gupta, Kapil
    [J]. MULTIMEDIA TOOLS AND APPLICATIONS, 2023, 82 (04) : 5161 - 5185
  • [25] Linear optimization and fuzzy-based clustering for WSNs assisted internet of things
    Priti Maratha
    Kapil Gupta
    [J]. Multimedia Tools and Applications, 2023, 82 : 5161 - 5185
  • [26] Auto-Clustering Using Particle Swarm Optimization and Bacterial Foraging
    Olesen, Jakob R.
    Cordero, Jorge H.
    Zeng, Yifeng
    [J]. AGENTS AND DATA MINING INTERACTION, 2009, 5680 : 69 - 83
  • [27] Bacterial foraging solution based fuzzy logic decision for optimal capacitor allocation in radial distribution system
    Tabatabaei, S. M.
    Vahidi, B.
    [J]. ELECTRIC POWER SYSTEMS RESEARCH, 2011, 81 (04) : 1045 - 1050
  • [28] Clustering-based performance optimization of the boiler-turbine system
    Kusiak, Andrew
    Song, Zhe
    [J]. IEEE TRANSACTIONS ON ENERGY CONVERSION, 2008, 23 (02) : 651 - 658
  • [29] Fuzzy c-means clustering-based mating restriction for multiobjective optimization
    Zhang, Yi
    Li, Zimu
    Zhang, Hu
    Yu, Zhen
    Lu, Tongtong
    [J]. INTERNATIONAL JOURNAL OF MACHINE LEARNING AND CYBERNETICS, 2018, 9 (10) : 1609 - 1621
  • [30] Monitoring defects of ceramic tiles using fuzzy subtractive clustering-based system identification method
    Mohammed T. Hayajneh
    Adel Mahmood Hassan
    Fatma Al-Wedyan
    [J]. Soft Computing, 2010, 14 : 615 - 626