h Swarm intelligence-based topology maintenance protocol for wireless sensor networks

被引:12
|
作者
Krishna, M. Bala [1 ]
Doja, M. N. [2 ]
机构
[1] GGS Indraprastha Univ, Univ Sch Informat Technol, New Delhi, India
[2] JMI Cent Univ, Dept Comp Engn, New Delhi, India
关键词
D O I
10.1049/iet-wss.2011.0068
中图分类号
TN [电子技术、通信技术];
学科分类号
0809 ;
摘要
Wireless sensor networks (WSNs) function with constraints in energy, computation and storage. The real-time monitored sensor data are transmitted to the base station through intermediate nodes. Application-specific protocols are being developed to enhance the functionality and performance of WSNs. WSN topology is classified into three phases: (i) topology construction; (ii) topology control and (iii) topology maintenance. The authors propose Swarm Intelligence (SI)-based topology maintenance for link failure and congestion control in WSN. SI-based models like Particle Swarm Optimisation (PSO) and Ant Colony Optimisation (ACO) are used in topology maintenance. The proposed model is compared with the existing distributed topology control techniques based on neighbour, location and direction attributes for WSNs. SI-based techniques indicate performance improvement in topology as compared to the existing techniques. The proposed SI model for topology maintenance evaluates WSN attributes based on (i) particle position and particle velocity in PSO; (ii) pheromone cost and (iii) forage success rate in ACO. SI-based topology maintenance is based on finding global and local minima during the search process. Simulation results indicate performance improvement in throughput, data transmission rate and average power efficiency in SI techniques as compared to the existing topology maintenance techniques.
引用
收藏
页码:181 / 190
页数:10
相关论文
共 50 条
  • [1] Swarm intelligence-based energy efficient clustering with multihop routing protocol for sustainable wireless sensor networks
    Elhoseny, Mohamed
    Rajan, R. Sundar
    Hammoudeh, Mohammad
    Shankar, K.
    Aldabbas, Omar
    INTERNATIONAL JOURNAL OF DISTRIBUTED SENSOR NETWORKS, 2020, 16 (09):
  • [2] A Comprehensive Review on Swarm Intelligence-Based Routing Protocols in Wireless Multimedia Sensor Networks
    Fazilet Lemya Benmansour
    Nabila Labraoui
    International Journal of Wireless Information Networks, 2021, 28 : 175 - 198
  • [3] A Comprehensive Review on Swarm Intelligence-Based Routing Protocols in Wireless Multimedia Sensor Networks
    Benmansour, Fazilet Lemya
    Labraoui, Nabila
    INTERNATIONAL JOURNAL OF WIRELESS INFORMATION NETWORKS, 2021, 28 (02) : 175 - 198
  • [4] Swarm intelligence based fuzzy routing protocol for clustered wireless sensor networks
    Zahedi, Zeynab Molay
    Akbari, Reza
    Shokouhifar, Mohammad
    Safaei, Farshad
    Jalali, Ali
    EXPERT SYSTEMS WITH APPLICATIONS, 2016, 55 : 313 - 328
  • [5] Swarm intelligence-based anycast routing protocol in ubiquitous networks
    Hwang, Ren-Hung
    Hoh, Cheng-Chang
    Wang, Chiung-Ying
    WIRELESS COMMUNICATIONS & MOBILE COMPUTING, 2010, 10 (07): : 875 - 887
  • [6] A ROUTING PROTOCOL WITH DISTRIBUTED TOPOLOGY MAINTENANCE IN WIRELESS SENSOR NETWORKS
    Michalski, Andrzej
    Makowski, Lukasz
    XIX IMEKO WORLD CONGRESS: FUNDAMENTAL AND APPLIED METROLOGY, PROCEEDINGS, 2009, : 1469 - 1474
  • [7] Swarm intelligence based routing protocol for wireless sensor networks: Survey and future directions
    Saleem, Muhammad
    Di Caro, Gianni A.
    Farooq, Muddassar
    INFORMATION SCIENCES, 2011, 181 (20) : 4597 - 4624
  • [8] SWARM INTELLIGENCE BASED CLUSTERING IN WIRELESS SENSOR NETWORKS
    Mehrjoo, Saeed
    Shanbehzadeh, Jamshid
    Sarrafzadeh, Abdolhossein
    IAENG TRANSACTIONS ON ENGINEERING TECHNOLOGIES, VOL 7, 2012, : 389 - 402
  • [9] Swarm Intelligence based Localization in Wireless Sensor Networks
    Akram, Junaid
    Javed, Arslan
    Khan, Sikander
    Akram, Awais
    Munawar, Hafiz Suliman
    Ahmad, Waqas
    36TH ANNUAL ACM SYMPOSIUM ON APPLIED COMPUTING, SAC 2021, 2021, : 1906 - 1914
  • [10] Swarm Intelligence Based Localization in Wireless Sensor Networks
    Lavanya, Dama
    Udgata, Siba K.
    MULTI-DISCIPLINARY TRENDS IN ARTIFICIAL INTELLIGENCE, 2011, 7080 : 317 - 328