Time-Optimized Task Offloading Decision Making in Mobile Edge Computing

Alghamdi, I., Anagnostopoulos, C. and Pezaros, D. P. (2019) Time-Optimized Task Offloading Decision Making in Mobile Edge Computing. In: 11th Annual Wireless Days Conference, Manchester, UK, 24-26 Apr 2019, ISBN 9781728101170 (doi: 10.1109/WD.2019.8734210)

179591.pdf - Accepted Version



Mobile Edge Computing application domains such as vehicular networks, unmanned aerial vehicles, data analytics tasks at the edge and augmented reality have recently emerged. Under such domains, while mobile nodes are moving and have certain tasks to be offloaded to Edge Servers, choosing an appropriate time and an ideally suited server to guarantee the quality of service can be challenging. We tackle the offloading decision making problem by adopting the principles of Optimal Stopping Theory to minimize the execution delay in a sequential decision manner. A performance evaluation is provided by using real data sets compared with the optimal solution. The results show that our approach significantly minimizes the execution delay for task execution and the results are very close to the optimal solution.

Item Type:Conference Proceedings
Additional Information:Also funded by the European Cooperation in Science and Technology (COST) Action CA 15127: RECODIS – Resilient communication and services; by the Huawei Innovation Research Program (Grant No. 300952); and by the EU H2020 GNFUV Project RAWFIE-OC2-EXPSCI (Grant No. 645220), under the EC FIRE+ initiative.
Glasgow Author(s) Enlighten ID:Anagnostopoulos, Dr Christos and Alghamdi, Ibrahim Ahmed I and Pezaros, Professor Dimitrios
Authors: Alghamdi, I., Anagnostopoulos, C., and Pezaros, D. P.
College/School:College of Science and Engineering > School of Computing Science
Copyright Holders:Copyright © 2019 IEEE
Publisher Policy:Reproduced in accordance with the copyright policy of the publisher
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Project CodeAward NoProject NamePrincipal InvestigatorFunder's NameFunder RefLead Dept
709131Network Measurement as a Service (MaaS)Dimitrios PezarosEngineering and Physical Sciences Research Council (EPSRC)EP/N033957/1COM - COMPUTING SCIENCE
722161FRuIT: The Federated RaspberryPi Micro-Infrastructure TestbedJeremy SingerEngineering and Physical Sciences Research Council (EPSRC)EP/P004024/1COM - COMPUTING SCIENCE
300952HIRP 2017 - Distributed Intelligence for Network ControlDimitrios PezarosHuawei Technologies (CN) (HUAWE-CN)N/AComputing Science