Generic placeholder image

International Journal of Sensors, Wireless Communications and Control

Editor-in-Chief

ISSN (Print): 2210-3279
ISSN (Online): 2210-3287

Research Article

Presenting the Hybrid Algorithm of Honeybee - Harmony in Clustering and Routing of Wireless Sensor Networks

Author(s): Mohammad Sedighimanesh*, Hesam Zandhesami and Ali Sedighimanesh

Volume 9, Issue 3, 2019

Page: [357 - 371] Pages: 15

DOI: 10.2174/2210327908666181029094346

Price: $65

Abstract

Background: Wireless sensor networks are considered as one of the 21st century's most important technologies. Sensors in wireless sensor networks usually have limited and sometimes non-rechargeable batteries, which they are supposed to be preserved for months or even years. That's why the energy consumption in these networks is of a great importance.

Objective: One way to improve energy consumption in a wireless sensor network is to use clustering. In clustered networks, one node is known as the cluster head and other nodes as normal members, which normal nodes send the collected data to the cluster head, and the cluster head sends the information to the base station either by a single step or by multiple steps.

Method: Using clustering simplifies resource management and increases scalability, reliability, and the network lifetime. Although the cluster formation involves a time- overhead and how to choose the cluster head is another problem, but its advantages are more than its disadvantages.

The primary aim of this study is to offer a solution to reduce energy consumption in the sensor network. In this study, during the selection of cluster heads, Honeybee Algorithm is used and also for routing, Harmonic Search Algorithm is used. In this paper, the simulation is performed by using MATLAB software and the proposed method is compared with the Low Energy Adaptive Clustering Hierarchy (LEACH) and the multi-objective fuzzy clustering algorithm (MOFCA).

Result and Conclusion: By simulations of this study, we conclude that this research has remarkably increased the network lifetime with respect to EECS, LEACH, and MOFCA algorithms. In view of the energy constraints of the wireless sensor network and the non-rechargeable batteries in most cases, providing such solutions and using metaheuristic algorithms can result in a significant reduction in energy consumption and, consequently, increase in the network lifetime.

Keywords: Meta- heuristic algorithms, routing protocols, sensor network clustering, wireless sensor networks, MEMS, MOFCA, clustering.

Graphical Abstract
[1]
Azharuddin M, Kuila P, Jana PK. Energy efficient fault tolerant clustering and routing algorithms for wireless sensor networks. Comput Electr Eng 2015; 41: 177-90.
[2]
Sedighimanesh M, Baqeri J, Sedighimanesh A. Increasing wireless sensor networks lifetime with new method. Int J Wirel Mob Netw 2016; 8(4): 65-80.
[3]
Sedighimanesh M, Sedighimanesh A. Reducing energy consumption of the seech algorithm in wireless sensor networks using a mobile sink and honey bee colony algorithm. Revista de Direito. Estado e Telecomun 2018; 10(1): 1-15.
[4]
Jadhav P, Satao R. A survey on opportunistic routing protocols for wireless sensor networks. Procedia Comput Sci 2016; 79: 603-9.
[5]
Velmani R, Kaarthick B. An efficient cluster-tree based data collection scheme for large mobile wireless sensor networks. IEEE Sens J 2014; 15(4): 2377-90.
[6]
Sabet M, Naji HR. A decentralized energy efficient hierarchical cluster-based routing algorithm for wireless sensor networks. AEU Int J Electron Commun 2015; 69(5): 790-9.
[7]
Chakchouk N. A survey on opportunistic routing in wireless communication networks. IEEE Comm Surv and Tutor 2015; 17(4): 2214-41.
[8]
Barekatain B, Dehghani S, Pourzaferani M. An energy-aware routing protocol for wireless sensor networks based on new combination of genetic algorithm and k-means. Proc Comp Sci 2015; 72: 552-60.
[9]
Akkari W, Bouhdid B, Belghith A. LEATCH: Low energy adaptive tier clustering hierarchy. Proc Comp Sci 2015; 52: 365-72.
[10]
Mottaghi S, Zahabi MR. Optimizing LEACH clustering algorithm with mobile sink and rendezvous nodes. AEU Int J Electron Commun 2015; 69(2): 507-14.
[11]
Heinzelman WR, Chandrakasan A, Balakrishnan H. Energy-efficient communication protocol for wireless microsensor networks. In: Proceedings of the 33rd annual Hawaii International Conference on System Sciences. 2000; p. Jan 4; IEEE: U S A, . 10.
[12]
Sert SA, Bagci H, Yazici A. MOFCA: Multi-objective fuzzy clustering algorithm for wireless sensor networks. Appl Soft Comput 2015; 30: 151-65.

Rights & Permissions Print Cite
© 2024 Bentham Science Publishers | Privacy Policy