A Multi-Hop-Aware User To Edge-Server Association Game

Nowadays, services and applications are becoming more latency-sensitive and resource-hungry. Due to their high computational complexity, they can not always be processed locally in user equipment, and have to be offloaded to a distant powerful server. Instead of resorting to remote Cloud servers with high latency and traffic bottlenecks, service providers could map their users to Multi-Access Edge Computing (MEC) servers that can run computation-intensive tasks nearby. This mapping of users to MEC distributed servers is known as the Edge User Allocation (EUA) problem, and has been widely studied in the literature from the perspective of service providers. However, users in previous works can only be allocated to a server if they are in its coverage. In reality, it may be optimal to allocate a user to a distant server (e.g., two hops away from the user) if the latency threshold and system cost are both respected. This work presents the first attempt to tackle the multi-hop aware EUA problem. We consider the static EUA problem where users have a simultaneous-batch arrival pattern, and detail the added complexity compared to the original EUA setting. Afterwards, we propose a game theory-based distributed approach for allocating users to edge servers. We finally conduct a series of experiments to evaluate the performance of our approach against other baseline approaches. The results illustrate the potential benefits of allowing multi-hop allocations in providing better overall system cost to service providers.