Surrogate-assisted sine Phasmatodea population evolution algorithm applied to 3D coverage of mobile nodes

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F24%3A10257038" target="_blank" >RIV/61989100:27240/24:10257038 - isvavai.cz</a>

Result on the web

<a href="https://link.springer.com/article/10.1007/s40747-024-01460-w" target="_blank" >https://link.springer.com/article/10.1007/s40747-024-01460-w</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/s40747-024-01460-w" target="_blank" >10.1007/s40747-024-01460-w</a>

Result language

angličtina

Original language name

Surrogate-assisted sine Phasmatodea population evolution algorithm applied to 3D coverage of mobile nodes

Original language description

Deploying static wireless sensor nodes is prone to network coverage gaps, resulting in poor network coverage. In this paper, an attempt is made to improve the network coverage by moving the locations of the nodes. A surrogate-assisted sine Phasmatodea population evolution algorithm (SASPPE) is used to evaluate the network coverage. A 50×50 hill simulation environment was tested for the number of nodes of 30 and 40 and radii of 3, 5 and 7, respectively. The results show that the SASPPE algorithm has the highest coverage, which can be up to 23.624% higher than the PPE algorithm, and up to 5.196% higher than the PPE algorithm, ceteris paribus. The SASPPE algorithm mixes the GSAM with LSAMs, which balances the computational cost of the algorithm and the algorithm’s ability to find optimal results. The use of hierarchical clustering enhances the stable type of the LSAMs. In addition, LSAMs are easy to fall into local optimality when they are modeled with local data, and the use of sine Phasmatodea population evolution algorithm (Sine-PPE) for searching in LSAMs alleviates the time for the algorithm to fall into local optimality. On 30D, 50D, and 100D, the proposed algorithm was tested by 7 test functions. The results show that the algorithm has significant advantages on most functions. © The Author(s) 2024.

Czech name

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Czech description

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Type

J_imp - Article in a specialist periodical, which is included in the Web of Science database

CEP classification

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OECD FORD branch

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Project

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Continuities

S - Specificky vyzkum na vysokych skolach

Publication year

2024

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical

Complex &amp; Intelligent Systems

ISSN

2199-4536

e-ISSN

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Volume of the periodical

10

Issue of the periodical within the volume

4

Country of publishing house

US - UNITED STATES

Number of pages

10

Pages from-to

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UT code for WoS article

001220435700001

EID of the result in the Scopus database

2-s2.0-85192834714