Delay-tolerant sequential decision making for task offloading in mobile edge computing environments

Alghamdi, I., Anagnostopoulos, C. and Pezaros, D. P. (2019) Delay-tolerant sequential decision making for task offloading in mobile edge computing environments. Information, 10(10), 312. (doi: 10.3390/info10100312)

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In recent years, there has been a significant increase in the use of mobile devices and their applications. Meanwhile, cloud computing has been considered as the latest generation of computing infrastructure. There has also been a transformation in cloud computing ideas and their implementation so as to meet the demand for the latest applications. mobile edge computing (MEC) is a computing paradigm that provides cloud services near to the users at the edge of the network. Given the movement of mobile nodes between different MEC servers, the main aim would be the connection to the best server and at the right time in terms of the load of the server in order to optimize the quality of service (QoS) of the mobile nodes. We tackle the offloading decision making problem by adopting the principles of optimal stopping theory (OST) to minimize the execution delay in a sequential decision manner. A performance evaluation is provided using real world data sets with baseline deterministic and stochastic offloading models. The results show that our approach significantly minimizes the execution delay for task execution and the results are closer to the optimal solution than other offloading methods.

Item Type:Articles
Additional Information:This work is supported by Al-Baha University, Saudi Arabia, and the Saudi Arabian Cultural Bureau in the UK.
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
Journal Name:Information
ISSN (Online):2078-2489
Published Online:12 October 2019
Copyright Holders:Copyright © 2019 The Authors
First Published:First published in Information 10(10): 312
Publisher Policy:Reproduced under a Creative Commons License

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