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Sensors 2014, 14(1), 299-345; doi:10.3390/s140100299
Review

Bio-Mimic Optimization Strategies in Wireless Sensor Networks: A Survey

1,* , 1
, 2
 and 1
Received: 7 October 2013; in revised form: 6 December 2013 / Accepted: 9 December 2013 / Published: 24 December 2013
(This article belongs to the Section Physical Sensors)
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Abstract: For the past 20 years, many authors have focused their investigations on wireless sensor networks. Various issues related to wireless sensor networks such as energy minimization (optimization), compression schemes, self-organizing network algorithms, routing protocols, quality of service management, security, energy harvesting, etc., have been extensively explored. The three most important issues among these are energy efficiency, quality of service and security management. To get the best possible results in one or more of these issues in wireless sensor networks optimization is necessary. Furthermore, in number of applications (e.g., body area sensor networks, vehicular ad hoc networks) these issues might conflict and require a trade-off amongst them. Due to the high energy consumption and data processing requirements, the use of classical algorithms has historically been disregarded. In this context contemporary researchers started using bio-mimetic strategy-based optimization techniques in the field of wireless sensor networks. These techniques are diverse and involve many different optimization algorithms. As far as we know, most existing works tend to focus only on optimization of one specific issue of the three mentioned above. It is high time that these individual efforts are put into perspective and a more holistic view is taken. In this paper we take a step in that direction by presenting a survey of the literature in the area of wireless sensor network optimization concentrating especially on the three most widely used bio-mimetic algorithms, namely, particle swarm optimization, ant colony optimization and genetic algorithm. In addition, to stimulate new research and development interests in this field, open research issues, challenges and future research directions are highlighted.
Keywords: wireless sensor networks; optimization; bio-mimetic algorithms; particle swarm optimization; ant colony optimization; genetic algorithm wireless sensor networks; optimization; bio-mimetic algorithms; particle swarm optimization; ant colony optimization; genetic algorithm
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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MDPI and ACS Style

Adnan, M.A.; Razzaque, M.A.; Ahmed, I.; Isnin, I.F. Bio-Mimic Optimization Strategies in Wireless Sensor Networks: A Survey. Sensors 2014, 14, 299-345.

AMA Style

Adnan MA, Razzaque MA, Ahmed I, Isnin IF. Bio-Mimic Optimization Strategies in Wireless Sensor Networks: A Survey. Sensors. 2014; 14(1):299-345.

Chicago/Turabian Style

Adnan, Md. A.; Razzaque, Mohammd A.; Ahmed, Ishtiaque; Isnin, Ismail F. 2014. "Bio-Mimic Optimization Strategies in Wireless Sensor Networks: A Survey." Sensors 14, no. 1: 299-345.



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