Multiobjective, trust‐aware, artificial hummingbird algorithm‐based secure clustering and routing with mobile sink for wireless sensor networks

Wireless sensor networks (WSNs) are composed of numerous nodes distributed in geographical regions. Security and energy efficiency are challenging tasks due to an open environment and a restricted battery source. The multiobjective trust‐aware artificial hummingbird algorithm (M‐TAAHA) is proposed t...

Celý popis

Uložené v:
Podrobná bibliografia
Vydané v:ETRI journal Ročník 46; číslo 6; s. 950 - 964
Hlavní autori: Jemla Naik, Anil Kumar, Parameswarappa, Manjunatha, Ramachandra, Mohan Naik
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Electronics and Telecommunications Research Institute (ETRI) 01.12.2024
한국전자통신연구원
Predmet:
energy efficiency
life expectancy
multiobjective trust-aware artificial hummingbird algorithm
security
throughput
wireless sensor networks
전자/정보통신공학
ISSN:1225-6463, 2233-7326
On-line prístup:Získať plný text
Tagy: Pridať tag
Žiadne tagy, Buďte prvý, kto otaguje tento záznam!
Popis
Shrnutí:Wireless sensor networks (WSNs) are composed of numerous nodes distributed in geographical regions. Security and energy efficiency are challenging tasks due to an open environment and a restricted battery source. The multiobjective trust‐aware artificial hummingbird algorithm (M‐TAAHA) is proposed to achieve secure and reliable transmission over a WSN with a mobile sink (MS). The M‐TAAHA selects secure cluster head (SCH) nodes based on trust, energy, interspace between sensors, interspace between SCH and MS, and the CH balancing factor. A secure route is found by M‐TAAHA with trust, energy, and interspace between SCH and MS. The M‐TAAHA avoids the malicious nodes to improve data delivery and avoid unwanted energy consumption. The M‐TAAHA is analyzed using energy consumption, alive nodes, life expectancy, delay, data packets received in MS, throughput, packet delivery ratio, and packet loss ratio. Existing techniques (LEACH‐TM, EATMR, FAL, Taylor‐spotted hyena optimization [Taylor‐SHO], TBEBR, and TEDG) are used for comparison with the M‐TAAHA. Findings show that the energy consumption of the proposed M‐TAAHA for 1000 rounds is 0.56 J (1.78 × smaller than that of the Taylor‐SHO).
Bibliografia:Funding information
This research received no external funding.
https://doi.org/10.4218/etrij.2023-0330
ISSN:1225-6463
2233-7326
DOI:10.4218/etrij.2023-0330