Mobility-Aware Energy Optimization in Hosts Selection for Computation Offloading in Multi-Access Edge Computing
AuthorThananjeyan, S; Chan, CA; Wong, E; Nirmalathas, A
Source TitleIEEE Open Journal of the Communications Society
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
University of Melbourne Author/sNirmalathas, Ampalavanapillai; Chan, Chien; Wong, Elaine; Shanmuganathan, Thananjeyan
AffiliationElectrical and Electronic Engineering
Document TypeJournal Article
CitationsThananjeyan, S., Chan, C. A., Wong, E. & Nirmalathas, A. (2020). Mobility-Aware Energy Optimization in Hosts Selection for Computation Offloading in Multi-Access Edge Computing. IEEE Open Journal of the Communications Society, 1, pp.1056-1065. https://doi.org/10.1109/ojcoms.2020.3008485.
Access StatusAccess this item via the Open Access location
Open Access URLhttp://doi.org/10.1109/ojcoms.2020.3008485
Multi-access edge computing (MEC) has been proposed as an approach capable of addressing latency and bandwidth issues in application computation offloading to extend the capabilities beyond the computational and storage limitations of mobile devices. However, there is a critical challenge in MEC to maintain the service continuity between the offloaded user application that is running on the MEC host and the mobile device when a user is moving from radio node to radio node. Furthermore, energy consumption of application computation offloading is an important consideration for MEC service providers in terms of operational costs. Therefore, we formulate the MEC host selection and user application migration problem as a shortest path problem of network energy minimization. We simulate the problem in a hierarchical MEC network deployment environment. We also propose the metric, computational intensity (CI), that can be used by MEC service providers to address the MEC host selection problem. Our results show that with the increment of CI, the selection of MEC hosts tends to move toward level 3 (central deployment) due to energy efficiency and then return to the deployment at level 1 (radio node level) due to latency constraint of the user application. We show that with high accuracy in predicting the user mobility and the available resources in the MEC network, latency- and mobility-aware MEC host selection and user application migration can be pre-calculated to improve response time and energy efficiency.
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