Cognitive Edge Computing based Resource Allocation Framework for Internet of Things

Amjad, Anas and Rabby, Fazle and Sadia, Shaima and Patwary, Mohammad and Benkhelifa, E. (2017) Cognitive Edge Computing based Resource Allocation Framework for Internet of Things. In: Proceedings of 2017 Second International Conference on Fog and Mobile Edge Computing (FMEC). IEEE, pp. 194-200.

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Abstract

Due to the inherent property of the processing resource request from mobile active or passive devices as part of internet of things (IoT), processing capacity as well as latency become major optimization criteria. To achieve overall optimized uses of cloud resources - having dynamic tracking, monitoring as well as orchestration framework is one of the key challenges
to overcome. In the same context, enhanced uses of computing devices at distributed location is predicted to facilitate the success of IoT; subsequently the success of fifth generation (5G) of Wireless technologies. This opens enormous potential to integrate the unused resources of such distributed computed devices within the conventional cloudlet or cloud federation. However, this requires an efficient micro-level distributed computing resource
tracking, monitoring and orchestration; where resources are distributed in geo-location as well as the availability of unused resources are time variant in nature. In this paper, we have proposed a cognitive edge-computing based framework solution for these requirements in order to achieve an efficient use of these distributed resources. This provides the end-user with a dynamic soft extension of computing facilities of cloudlet and cloud federation, as well as a revenue generation avenue to enduser. The simulation results show that such extension can be an exponential function of the number of local processing platforms agreed to participate in the proposed cognitive resource sharing.

Item Type:	Book Section
Dates:	Date Event 2017 Published
Uncontrolled Keywords:	Distributed computing, edge computing, internet of things, merchant mode, resource sharing.
Subjects:	CAH11 - computing > CAH11-01 - computing > CAH11-01-01 - computer science
Divisions:	Faculty of Computing, Engineering and the Built Environment Faculty of Computing, Engineering and the Built Environment > School of Computing and Digital Technology
Depositing User:	Ian Mcdonald
Date Deposited:	01 Sep 2017 10:50
Last Modified:	22 Mar 2023 12:01
URI:	https://www.open-access.bcu.ac.uk/id/eprint/5114

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