To support emerging real-time monitoring and control applications, the timeliness of computation results is of critical importance to mobile-edge computing (MEC) systems. We propose a performance metric called age of task (AoT) based on the concept of age of information (AoI), to evaluate the temporal value of computation tasks. In this paper, we consider a system consisting of a single MEC server and one mobile device running several applications. We study an age minimization problem by jointly considering task scheduling, computation offloading and energy consumption. To solve the problem efficiently, we propose a light-weight task scheduling and computation offloading algorithm. Through performance evaluation, we show that our proposed age-based solution is competitive when compared with traditional strategies. Index Terms-Mobile-edge computing (MEC), age of task (AoT), task scheduling, computation offloading.
In REF , the authors proposed a performance metric called age of task (AoT) to evaluate the temporal value of computation tasks.
Age Based Task Scheduling and Computation Offloading in Mobile-Edge Computing Systems
2019 IEEE Wireless Communications and Networking Conference Workshop (WCNCW)
2019 IEEE Wireless Communications and Networking Conference Workshop (WCNCW)
Engineering Computer Science