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Abstract

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.

Details

Business indexing term
Title
BESIEC: An Adaptive Optimized Model for Task Scheduling & Offloading
Author
Mohanty, Jayashree 1 ; Sobhanayak, Srichandan 1 

 International Institute of Information Technology (IIIT), Department of Computer Science and Engineering, Bhubaneswar, India 
Publication title
Volume
5
Issue
8
Pages
1099
Publication year
2024
Publication date
Dec 2024
Publisher
Springer Nature B.V.
Place of publication
Kolkata
Country of publication
Netherlands
Publication subject
ISSN
2662995X
e-ISSN
26618907
Source type
Scholarly Journal
Language of publication
English
Document type
Journal Article
Publication history
 
 
Online publication date
2024-11-28
Milestone dates
2024-10-26 (Registration); 2024-06-25 (Received); 2024-10-26 (Accepted)
Publication history
 
 
   First posting date
28 Nov 2024
ProQuest document ID
3133929229
Document URL
https://www.proquest.com/scholarly-journals/besiec-adaptive-optimized-model-task-scheduling/docview/3133929229/se-2?accountid=208611
Copyright
© The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd. 2024. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
Last updated
2024-11-29
Database
ProQuest One Academic