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BESIEC: An Adaptive Optimized Model for Task Scheduling & Offloading

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Publié dans:SN Computer Science vol. 5, no. 8 (Dec 2024), p. 1099
Auteur principal: Mohanty, Jayashree
Autres auteurs: Sobhanayak, Srichandan
Publié:
Springer Nature B.V.
Sujets:
Computer program integrity
Scheduling
Power sources
Data integrity
Task scheduling
Data processing
Internet of Things
Computer architecture
Edge computing
Security management
Network reliability
Cloud computing
Blockchain
Traffic control
Network latency
Resource scheduling
Computation offloading
Algorithms
Energy consumption
Heterogeneity
Resource management
Efficiency
Floodlighting
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Résumé:The rapid change in computational strategy and delay-sensitive applications require intense power sources of computational resources. This creates a challenge of precise latency requirements in 5G network services. Task scheduling and offloading can be promising solutions to achieve high-performance optimized output with heterogeneity, handling of tasks, conservation of energy, and reliable latency factor. Blockchain (BC), Software defined networks (SDN) and the Internet of Things(IoT) are the most promising significant technologies researched in this article, and the fusion of the three has the potential to reinvent the relationship of trust in the networks and promote the integration of confidentiality and reliability in the respective use cases. Cloud infrastructure is used to provide clients with powerful computing and storage environments. A kind of expansion of cloud computing architecture, edge computing, has been trending. Now, it is used to build distributed secure architecture to promote the safety and integrity of data throughout its lifetime and bring much-needed efficiency to IoT data processing. This paper considers a Blockchain-Enabled Software-defined network-based IoT Edge Cloud(BESIEC) scenario for data integrity during task scheduling and offloading processes while achieving optimal computational resources and minimizing end-to-end delays. The strategy shows that it is better to implement the BESIEC model than the Traditional Floodlight implementation. The BESIEC model shows better time consumption performance regarding the number of tasks completed compared to local processing, cloud offloading, and edge offloading.
ISSN:2662-995X
2661-8907
DOI:10.1007/s42979-024-03461-5
Source:Advanced Technologies & Aerospace Database