Efficient Resource Management in IoTs Using Evolutionary and Swarm Intelligence Algorithms

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dc.contributor.authorGupta, K.D.
dc.contributor.authorCengiz, K.
dc.contributor.authorAwasthi, C.
dc.contributor.authorRamini, S.A.
dc.contributor.authorChatterjee, S.
dc.contributor.authorPavithra, M.
dc.date.accessioned2024-05-19T14:33:56Z
dc.date.available2024-05-19T14:33:56Z
dc.date.issued2023
dc.departmentİstinye Üniversitesien_US
dc.description7th International Symposium on Innovative Approaches in Smart Technologies, ISAS 2023 -- 23 November 2023 through 25 November 2023 -- -- 196776en_US
dc.description.abstractThe proliferation of the Internet of Things (IoT) has ushered in a transformative era of connected devices, emphasizing the critical need for effective resource management. This study introduces an innovative approach that harnesses Evolutionary and Swarm Intelligence algorithms for IoT Task Scheduling, addressing resource optimization challenges. The approach offers superior resource utilization through advanced optimization techniques, reducing energy consumption and enhancing efficiency. Furthermore, it significantly reduces task scheduling execution time, enabling prompt decision-making in dynamic IoT environments. This results in improved task allocation quality, meeting application-specific requirements, and prioritizing critical tasks. Notably, the approach excels in minimizing completion time, making it particularly advantageous for real-time IoT applications. This research contributes to the advancement of IoT resource management, offering an adaptive, efficient, and intelligent solution with broad applicability. In the evolving landscape of IoT, the findings presented here lay a solid foundation for future research and practical implementations, ultimately promoting more responsive, sustainable, and intelligent IoT ecosystems. © 2023 IEEE.en_US
dc.identifier.doi10.1109/ISAS60782.2023.10391722
dc.identifier.isbn9798350383065
dc.identifier.scopus2-s2.0-85184800947en_US
dc.identifier.scopusqualityN/Aen_US
dc.identifier.urihttps://doi.org/10.1109/ISAS60782.2023.10391722
dc.identifier.urihttps://hdl.handle.net/20.500.12713/4374
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherInstitute of Electrical and Electronics Engineers Inc.en_US
dc.relation.ispartofISAS 2023 - 7th International Symposium on Innovative Approaches in Smart Technologies, Proceedingsen_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.snmz20240519_kaen_US
dc.subjectEvolutionary Algorithmsen_US
dc.subjectInternet Of Things (Iot)en_US
dc.subjectResource Managementen_US
dc.subjectResource Utilizationen_US
dc.subjectSwarm Intelligenceen_US
dc.subjectTask Schedulingen_US
dc.titleEfficient Resource Management in IoTs Using Evolutionary and Swarm Intelligence Algorithmsen_US
dc.typeConference Objecten_US

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