Fractional lion optimization for cluster head-based routing protocol in wireless sensor network

•Fractional lion (FLION) is developed for finding the energy efficient routing path.•A new fitness function is developed based on the five different objectives.•Comparative discussion is presented with LEACH, PSO, ABC and FABC algorithms.•Proved that the life time of networks is maximized by the pro...

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Bibliographic Details
Published in:Journal of the Franklin Institute Vol. 354; no. 11; pp. 4457 - 4480
Main Authors: Sirdeshpande, Nandakishor, Udupi, Vishwanath
Format: Journal Article
Language:English
Published: Elmsford Elsevier Ltd 01.07.2017
Elsevier Science Ltd
Subjects:
Adaptive algorithms
Algorithms
Clustering
Clusters
Design optimization
Fitness
Multiple objective analysis
Optimization
Particle swarm optimization
Position sensing
Protocol (computers)
Route planning
Routing
Wireless networks
Wireless sensor networks
ISSN:0016-0032, 1879-2693, 0016-0032
Online Access:Get full text
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Summary:•Fractional lion (FLION) is developed for finding the energy efficient routing path.•A new fitness function is developed based on the five different objectives.•Comparative discussion is presented with LEACH, PSO, ABC and FABC algorithms.•Proved that the life time of networks is maximized by the proposed FLION algorithm. Due to the hopeful application of gathering information from unreachable position, wireless sensor network creates an immense challenge for data routing to maximize the communication with more energy efficiency. In order to design the energy efficient routing, the optimization based clustering protocols are more preferred in wireless sensor network. In this paper, we have proposed competent optimization based algorithm called Fractional lion (FLION) clustering algorithm for creating the energy efficient routing path. Here, the proposed clustering algorithm is used to increase the energy and lifetime of the network nodes by selecting the rapid cluster head. In addition, we have proposed multi-objective FLION clustering algorithm to develop the new fitness function based on the five objectives like intra-cluster distance, inter-cluster distance, cluster head energy, normal nodes energy and delay. Here, the proposed fitness function is used to find the rapid cluster centroid for an efficient routing path. Finally, the performance of the proposed clustering algorithm is compared with the existing clustering algorithms such as low energy adaptive clustering hierarchy (LEACH), particle swarm optimization (PSO), artificial bee colony (ABC) and Fractional ABC clustering algorithm. The results proved that the lifetime of the wireless sensor nodes is maximized by the proposed FLION based multi-objective clustering algorithm as compared with existing protocols.
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ISSN:0016-0032
1879-2693
0016-0032
DOI:10.1016/j.jfranklin.2017.04.005