Artificial bee colony metaheuristic for energy-efficient clustering and routing in wireless sensor networks
- 323 Downloads
Swarm intelligence (SI)-based metaheuristics are well applied to solve real-time optimization problems of efficient node clustering and energy-aware data routing in wireless sensor networks. This paper presents another superior approach for these optimization problems based on an artificial bee colony metaheuristic. The proposed clustering algorithm presents an efficient cluster formation mechanism with improved cluster head selection criteria based on a multi-objective fitness function, whereas the routing algorithm is devised to consume minimum energy with least hop-count for data transmission. Extensive evaluation and comparison of the proposed approach with existing well-known SI-based algorithms demonstrate its superiority over others in terms of packet delivery ratio, average energy consumed, average throughput and network life.
KeywordsSwarm intelligence Efficient clustering Energy-aware routing Wireless sensor networks Artificial bee colony
The authors of the study acknowledge the contribution of I. K. Gujral Punjab Technical University, Kapurthala, Punjab, India.
Compliance with ethical standards
Conflict of interest
The authors declare that they have no conflict of interest.
- Anisi MH, Abdul-Salaam G (2015) Energy harvesting and battery power based routing in wireless sensor networks. Wirel Netw 1–18. DOI: 10.1007/s11276-015-1150-6
- Ding Y, Chen R, Hao K (2016) A multi-path routing algorithm with dynamic immune clustering for event-driven wireless sensor networks. Neurocomputing 203:139–149Google Scholar
- Fatemeh Najafi MAD (2011) Formatting a novel clustering protocol based on artificial immune system algorithm for wirelesssensor networks. Int J Adv Eng Sci Technol 6(2):256–260Google Scholar
- Kong L, Pan JS (2015) A balanced power consumption algorithm based on enhanced parallel cat swarm optimization for wireless sensor network. Int J Distrib Sens Netw 2015:20Google Scholar
- Krishnan R, Starobinski D (2006) Efficient clustering algorithms for self-organizing wireless sensor networks. Ad Hoc Netw 4(1):36–59Google Scholar
- Saleem M, Farooq M (2012) Beesensor: a bee-inspired power aware routing protocol for wireless sensor networks. In: Applications of evolutionary computing. Springer, pp 81–90Google Scholar
- Song MAO, Zhao CL (2011) Unequal clustering algorithm for WSN based on fuzzy logic and improved ACO. J China Univ Posts Telecommun 18(6):89–97Google Scholar
- Wang L, Geng S, Zhang R (2009) An energy-balanced ant-based routing protocol for wireless sensor networks. In: 5th international conference on wireless communications, networking and mobile computing, 2009, IEEE, pp 1–4Google Scholar