A Distributed and Context-Aware Task Assignment Mechanism for Collaborative Mobile Edge Computing.

Mobile edge computing (MEC) is an emerging technology that leverages computing, storage, and network resources deployed at the proximity of users to offload their delay-sensitive tasks. Various existing facilities including mobile devices with idle resources, vehicles, and MEC servers deployed at base stations or road side units, could act as edges in the network. Since task offloading incurs extra transmission energy consumption and transmission latency, two key questions to be addressed in such an environment are (i) should the workload be offloaded to the edge or computed in terminals? (ii) Which edge, among the available ones, should the task be offloaded to? In this paper, we formulate the task assignment problem as a one-to-many matching game which is a powerful tool for studying the formation of a mutual beneficial relationship between two sets of agents. The main goal of our task assignment mechanism design is to reduce overall energy consumption, while satisfying task owners' heterogeneous delay requirements and supporting good scalability. An intensive simulation is conducted to evaluate the efficiency of our proposed mechanism.