DVFS-based Energy-saving Workflow Offloading Strategy in Mobile Edge Computing Environments

Abstract

As the number and proportion of compute-intensive tasks on mobile devices increase, so does the amount of energy required to process them. Edge computing technologies provide a solution to enhance the capacity of mobile devices by offloading those tasks to edge servers. Based on dynamic voltage and frequency scaling (DVFS) technology, this paper proposed a new energy saving offloading strategy for mobile devices. On the premise that the task completion time meets the task deadline, the energy consumption problem of mobile devices is formulated as a minimum problem and solved by the genetic algorithm. In this strategy, priority is allocated to each task of workflow, and corresponding offloading resources are allocated according to the result of classification. DVFS technology is applied to the CPU of the terminal device to further reduce energy consumption while the task-resource mapping is performed. Experimental results show that for the same workflow and the same offloading resources and communication environment, in meet the delay constraints of tasks, the proposed algorithm is compared with the existing fine-grained task migration energy-saving algorithm based on genetic algorithm and the task scheduling algorithm based on energy consumption perception, can effectively improve the high energy consumption of mobile devices.