Reliability and Latency Aware Code-Partitioning Offloading in Mobile Edge Computing

A variety of emerging use cases, e.g. virtual reality, autonomous vehicle, etc., require to reliably complete computation-intensive tasks within stringent latency. Mobile edge computing (MEC) is one of the promising solutions to provide computation capacity with low latency. However, it may cause extra communication cost to offload task to MEC via wireless channel. It is challenging to optimize the offloading decision considering the finite resource that is available at edge node for a user. In this paper, we study the code-partitioning offloading strategy where the computational task of the user is modeled by a directed acyclic graph. The reliability and latency of offloading are analyzed comprehensively. An optimization problem is formulated to minimize the offloading failure probability, subject to the latency constraint. Due to the non-convexity, we propose a heuristic algorithm to solve the problem with low complexity. The numerical results show that the proposed algorithm significantly improves the probability to reach the targeted reliability. The heuristic algorithm doubles the performance compared with the naive scheme, in particular, when the latency constraint is stringent. Furthermore, the proposed algorithm is applicable in various network conditions.