hPSO-SA: hybrid particle swarm optimization-simulated annealing algorithm for relay node selection in wireless body area networks

In the modern world, wireless body area networks (WBANs) play an essential role in psychological and biomedical applications. The use of WBANs in medical applications is limited due to various issues related to the sensors, viz., irregularity in data production, replacement and recharging of their b...

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Bibliographic Details
Published in:Applied intelligence (Dordrecht, Netherlands) Netherlands), 2021-03, Vol.51 (3), p.1410-1438
Main Authors: Bilandi, Naveen, Verma, Harsh K., Dhir, Renu
Format: Article
Language:English
Subjects:
Algorithms
Artificial Intelligence
Biomedical materials
Body area networks
Computer Science
Design engineering
Energy consumption
Heuristic methods
Machines
Manufacturing
Mechanical Engineering
Optimization
Particle swarm optimization
Power consumption
Processes
Rechargeable batteries
Relay
Routing (telecommunications)
Search algorithms
Simulated annealing
Wireless networks
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Summary:In the modern world, wireless body area networks (WBANs) play an essential role in psychological and biomedical applications. The use of WBANs in medical applications is limited due to various issues related to the sensors, viz., irregularity in data production, replacement and recharging of their batteries and the energy consumed by the networks. This manuscript addresses how these problems can be solved along with optimization of the energy consumption through efficient design of the system by applying routing protocols and heuristic-based optimization algorithms. In this paper, the particle swarm optimization (PSO) algorithm is a heuristic search algorithm that relies on an upgrade mechanism of the velocity and position of swarms. Although PSO has excellent exploration capability in global search, it becomes quickly stuck in local minima. To enhance the local search function of the current PSO algorithm, a simulated annealing (SA) algorithm has been incorporated in the exploitation phase. The newly developed hybrid PSO-SA (hPSO-SA) algorithm is validated with other state-of-the-art nature-inspired algorithms on eighteen benchmarks and five real engineering design problems. The statistical results of the proposed hPSO-SA algorithm are promising and indicate very good efficiency. The paper also aims at the application of the proposed algorithm to the WBAN design problem for minimization of the energy consumption through better selection of the relay node. The proposed hPSO-SA algorithm outperforms twelve other metaheuristic algorithms, taking hybrid variants for comparison.
ISSN:0924-669X
1573-7497
DOI:10.1007/s10489-020-01834-w