A new localization mechanism in IoT using grasshopper optimization algorithm and DVHOP algorithm
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Tarih
2023
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Springer
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
Nowadays, different types of computer networks such as Wireless sensor networks (WSNs), the Internet of things (IoT), and wireless body area networks (WBANs) transfer information, share resources, and process information. The IoT is a novel network which interconnects various smart devices and can consist of heterogeneous components such as WSNs for monitoring and collecting information. Characterized by specific advantages, the IoT contains different types of nodes, each with few sensors to collect environmental information on agriculture, ecosystem, search and rescue, conflagrations, etc. Despite extensive applications and high flexibility in the modern world, the IoT faces specific challenges, the most important of which include routing, energy consumption and localization. Localization leads to other network challenges and thus can be considered the most important challenge in the IoT. Localization refers to a process aiming at determining the positions and locations of objects lacking global positioning system (GPS) and needing to use the information of network sensors and topology to estimate their own positions and locations. The distance vector hop (DV-Hop) algorithm is a range-free localization technique, in which the major challenge is that the number of hops between two nodes is multiplied by a number that is the same for all nodes leading to a significant reduction in the localization accuracy. In the method proposed in this paper, a network node with no GPS determines the hops from three anchor nodes with GPS. The location of smart objects can be then estimated according to distances from those anchor nodes. Thereafter, a few positions can be created nearby to mitigate the error. Then each position can be regarded as a member of the grasshopper optimization algorithm (GOA) to minimize the localization error. According to the results obtained from implementation of the proposed algorithm, it is characterized by a lower localization error than grasshopper optimization, butterfly optimization, firefly and swarm optimization algorithms.
Açıklama
Anahtar Kelimeler
DV-Hop localization algorithm, Grasshopper optimization algorithm (GOA), Internet of things (IoT), Localization
Kaynak
Wireless Networks
WoS Q Değeri
Q3
Scopus Q Değeri
Q1
Cilt
Sayı
Künye
Janabi, S. M. A., & Kurnaz, S. (2023). A new localization mechanism in IoT using grasshopper optimization algorithm and DVHOP algorithm. Wireless Networks.
