Identification of the key parameters for computational offloading in Multi-access Edge computing

Raghubir Singh*, Simon M D Armour, Aftab Khan , Mahesh Sooriyabandara, George Oikonomou

*Corresponding author for this work

Research output: Contribution to conferenceConference Paperpeer-review

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Computational offloading is a strategy by which mobile device (MD) users can access the superior processing power of a Multi-Access Edge Computing (MEC) server network. This paper investigates the impact of CPU workloads (on both the user and server-side) on overall processing times and energy consumption as well as We provide a comprehensive mathematical model using two applications of varying complexity are tested on a range of cases. Our findings show that the relationship between the CPU workloads on the MD and MEC server and the link speed between them are the crucial parameters that determine the success of offloading in the MEC network. We demonstrate that a certain threshold of link speed is required for shorter completion times by offloading, and the MD CPU workload determines it. Furthermore, MD energy usage can be reduced considerably by offloading for varying complexity applications provided a sufficiently link speed is available to the MEC network.
Original languageEnglish
Number of pages6
Publication statusPublished - 22 Oct 2020
EventIEEE Cloud Summit 2020 -
Duration: 21 Oct 202022 Oct 2020


ConferenceIEEE Cloud Summit 2020


  • Computation Offloading
  • Multi-Access Edge Computing
  • CPU Workloads
  • Energy Usage

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