  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.
