Optimizing Task Allocation for Edge Micro-Clusters in Smart Cities

Alhaizaey, Y., Singer, J. and Michala, A. L. (2021) Optimizing Task Allocation for Edge Micro-Clusters in Smart Cities. 2nd IEEE International Workshop on Smart Computing for Smart Cities (SC2), 07 Jun 2021. pp. 341-347. ISBN 9781665446525 (doi: 10.1109/WoWMoM51794.2021.00062)

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Current urban technology trends like Internet-of-Things and 5G require ultra low latency compute resource to be distributed liberally at the network edge. We characterize and advocate the need for heterogeneous edge micro-clusters; these are pragmatic, low-power, low-cost, minimal footprint units that can provide sufficient resource for typical edge compute applications in smart cities. However, to make best use of heterogeneous edge micro-clusters, we require resource management techniques that are both efficient and effective. In this paper, we report on an empirical study to demonstrate that mathematical optimization (in particular, mixed integer programming) for resource management is appropriate in terms of overhead, also highly effective for executing batch-arrival workloads in smart city use cases.

Item Type:Conference or Workshop Item
Additional Information:This work is partly supported and funded by King Khalid University, Saudi Arabia and the Saudi Arabian Cultural Bureau in the UK.
Keywords:Resource management, task allocation, internet of things, edge computing, edge cluster.
Glasgow Author(s) Enlighten ID:Alhaizaey, Yousef Hassan A and Michala, Dr Lito and Singer, Dr Jeremy
Authors: Alhaizaey, Y., Singer, J., and Michala, A. L.
College/School:College of Science and Engineering > School of Computing Science
Copyright Holders:Copyright © 2021 IEEE
First Published:First published in Proceedings of the 2021 IEEE 22nd International Symposium on a World of Wireless, Mobile and Multimedia Networks (WoWMoM), 341-347
Publisher Policy:Reproduced in accordance with the copyright policy of the publisher
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