A Truthful Auction Mechanism for Cumulative Resource Allocation in Mobile Edge Computing
Xutao Yang, Xuejie Zhang, Weidong Li, Jixian Zhang · 2020
Task offloading is a major problem in edge computing. In existing research, tasks are generally portrayed as requiring specific resources and time, and the task owner provides the value that he is willing to pay. The goal of the resource provider is to obtain the maximum social welfare and profit. However, this approach cannot cover all task offloading scenarios. 1) This paper innovatively considers a continuous task offloading problem in mobile edge computing in which the task can be partially executed and the task owner provides a nonlinear value function to pay for the executed task. The resource provider needs to decide which tasks to execute at each moment in order to obtain the maximum social welfare and profit. We represent the problem as a nonlinear integer programming model with multiple resource constraints. 2). We design an auction mechanism to solve the continuous task offloading problem in a competitive environment. Specifically, we propose a resource allocation algorithm based on the remaining value strategy and a payment price algorithm based on the critical value theory to guarantee truthful task information. Our approach is experimentally compared with existing research in terms of execution time, social welfare, and resource utilization.