Al Ridhawi, I, Aloqaily, M, Kotb, Y, Jaraweh, Y and Baker, T (2019) A Profitable and Energy-Efficient Cooperative Fog Solution for IoT Services. IEEE Transactions on Industrial Informatics. ISSN 1941-0050
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Abstract
Fog-to-Fog (F2F) communication has been introduced to deliver services to clients with minimal reliance on the cloud through resource and capability sharing of cooperative fogs. Current solutions assume full cooperation among the fogs to deliver simple and composite services. Realistically, each fog might belong to a different network operator or service provider and thus will not participate in any form of collaboration unless self-monetary profit is incurred. In this paper, we introduce a fog collaboration approach for simple and complex multimedia service delivery to cloud subscribers while achieving shared profit gains for the cooperating fogs. The proposed work dynamically creates short-term service-level-agreements (SLA) offered to cloud subscribers for service delivery while maximizing user satisfaction and fog profit gains. The solution provides a learning mechanism that relies on online and offline simulation results to build guaranteed workflows for new service requests. The configuration parameters of the short-term SLAs are obtained using a modified tabu-based search mechanism that uses previous solutions when selecting new optimal choices. Performance evaluation results demonstrate significant gains in terms of service delivery success rate, service quality, reduced power consumption for fog and cloud datacenters, and increased fog profits.
Item Type: | Article |
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Additional Information: | © 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. |
Uncontrolled Keywords: | 08 Information and Computing Sciences, 09 Engineering, 10 Technology |
Subjects: | Q Science > QA Mathematics > QA75 Electronic computers. Computer science |
Divisions: | Computer Science & Mathematics |
Publisher: | Institute of Electrical and Electronics Engineers |
Date Deposited: | 18 Jun 2019 10:31 |
Last Modified: | 04 Sep 2021 09:16 |
DOI or ID number: | 10.1109/TII.2019.2922699 |
URI: | https://researchonline.ljmu.ac.uk/id/eprint/10909 |
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