Social spider optimization meta-heuristic for node localization optimization in wireless sensor networks

Zahia Lalama, Fouzi Semechedine, Nabil Giweli, Samra Boulfekhar

Research output: Chapter in Book / Conference PaperChapter

1 Citation (Scopus)

Abstract

Localization is one of the most important system parameters in Wireless Sensor Networks (WSNs). It consists of the determination of the geographical coordinates of nodes forming the network. Traditional localization algorithms suffer from the high error of localization, then they need to be enhanced. This paper proposes a new localization algorithm namely Centroid Localization Algorithm based on Social Spider Optimization Algorithm (CLA-SSO). The proposed algorithm uses the Social Spider Optimization metaheuristic (SSO) to improve the localization of the basic Centroide Localization Algorithm (CLA) which is a range free localization algorithm. In our method, the initial spiders are initialized by the locations obtained by the CLA and optimized using the SSO metaheuristic. Simulation results show that our proposed algorithm outperforms the basic CLA in terms of localization accuracy. These results are obtained by changing some factors such as transmission radius, ratio of anchor nodes and the number of unknown nodes which affect the localization accuracy.
Original languageEnglish
Title of host publicationProceedings of the Second International Conference on Innovations in Computing Research (ICR '23)
EditorsKevin Daimi, Abeer Al Sadoon
Place of PublicationSwitzerland
PublisherSpringer
Pages381-391
Number of pages11
ISBN (Electronic)9783031353086
ISBN (Print)9783031353079
DOIs
Publication statusPublished - 2023

Bibliographical note

Publisher Copyright:
© 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Fingerprint

Dive into the research topics of 'Social spider optimization meta-heuristic for node localization optimization in wireless sensor networks'. Together they form a unique fingerprint.

Cite this