Reduce energy consumption in sensors using a smartphone, smartwatch, and the use of SFLA algorithms (REC-SSS)

Mohammadhosseini, Mohammad Reza; Najafzadeh, Sara; Mahdipour, Ebrahim

doi:10.1007/s11227-020-03202-4

Cited by 2 publications

(1 citation statement)

References 30 publications

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“…A BAN consists of distributed autonomous sensor nodes, and each sensing unit consists of sensing boards, processor, short-range radio transmitter unit, and battery. Each node is a small and compact device to sense the healthy data and send to the base station [9][10][11].…”

Section: Introductionmentioning

confidence: 99%

A Biologically Inspired Algorithm for Low Energy Clustering Problem in Body Area Network

Zhou

2021

Journal of Sensors

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The growing application of body area networks (BANs) in different fields makes the low energy clustering a paramount issue. A clustering optimization algorithm in BANs is a fundamental scheme to guarantee that the essential collected data can be forwarded in a reliable path and improve the lifetime of BANs. Low energy clustering is a technique, which provides a method that shows how to reduce network communication costs in BANs. A careful low energy clustering scheme is one of the most critical means in the research of BANs, which has attracted considerable attention, comprising monitoring capability constraints. However, the classical clustering method leads to high cost when constraints such as large overall energy consumption are undertaken. Hence, a binary immune hybrid artificial bee colony algorithm (BIHABCA), a randomized swarm intelligent scheme applied in BANs, motivated by immune theory and hybrid scheme is introduced. Furthermore, we designed the formulation that considers both distances between two nodes and the length of bits. Finally, we have compared the energy cost optimized by BIHABCA with a shuffled frog leaping algorithm, ant colony optimization, and simulated annealing in the simulation with different quantity of nodes in terms of energy cost. Results show that the energy cost of the network optimized by the proposed BIHABCA method decreased compared to those by the other three methods which mean that the proposed BIHABCA finds the global optima and reduces the energy cost of transmitting and receiving data in BANs.

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Section: Introductionmentioning

confidence: 99%

A Biologically Inspired Algorithm for Low Energy Clustering Problem in Body Area Network

Zhou

2021

Journal of Sensors

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Current Studies and Applications of Shuffled Frog Leaping Algorithm: A Review

Maaroof

Rashid

Abdulla

et al. 2022

Arch Computat Methods Eng

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Shuffled Frog Leaping Algorithm (SFLA) is one of the most widespread algorithms. It was developed by Eusuff and Lansey in 2006. SFLA is a population-based metaheuristic algorithm that combines the benefits of memetics with particle swarm optimization. It has been used in various areas, especially in engineering problems due to its implementation easiness and limited variables. Many improvements have been made to the algorithm to alleviate its drawbacks, whether they were achieved through modifications or hybridizations with other well-known algorithms. This paper reviews the most relevant works on this algorithm. An overview of the SFLA is first conducted, followed by the algorithm's most recent modifications and hybridizations. Next, recent applications of the algorithm are discussed. Then, an operational framework of SLFA and its variants is proposed to analyze their uses on different cohorts of applications. Finally, future improvements to the algorithm are suggested. The main incentive to conduct this survey to provide useful information about the SFLA to researchers interested in working on the algorithm's enhancement or application.

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Reduce energy consumption in sensors using a smartphone, smartwatch, and the use of SFLA algorithms (REC-SSS)

Cited by 2 publications

References 30 publications

A Biologically Inspired Algorithm for Low Energy Clustering Problem in Body Area Network

A Biologically Inspired Algorithm for Low Energy Clustering Problem in Body Area Network

Current Studies and Applications of Shuffled Frog Leaping Algorithm: A Review

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