A Novel Federated Fog Architecture Embedding Intelligent Formation

Hala Shamseddine, Jana Nizam, Ahmad Hammoud, Azzam Mourad, Hadi Otrok, Haidar Harmanani, Zbigniew Dziong

Research output: Contribution to journalArticlepeer-review

31 Scopus citations

Abstract

Network delays cause disturbance and reduction in the Quality-of-Service (QoS) for Internet-of-Things (IoT) while end-users are running critical real-time services. In parallel, federated fogs are not effective when formed without considering the performance perceived by the end-users. This article presents a novel architecture for the federated fog concept and proposes an adaptive and intelligent federation formation approach using Genetic Algorithm and Machine Learning models. Fog federations serve as a solution for fog providers to offer the required QoS they serve. Such a concept allows efficient distribution of load among multiple fog providers that share their resources. Throughout this process, the issue of QoS deterioration, due to local overloads, is relatively solved. Hence, the end users can enjoy a delay-free experience when using real-time applications. Real data is used to evaluate the proposed architecture and formation mechanism. The results show a notable improvement in the throughput as well as a decrease in the response time for the services requested.

Original languageBritish English
Article number9220179
Pages (from-to)198-204
Number of pages7
JournalIEEE Network
Volume35
Issue number3
DOIs
StatePublished - 1 May 2021

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