FairMEC: Achieving Fair Resource Sharing in Multi-Access Edge Computing Federations

Abstract

Multi-access Edge Computing (MEC) federations allow 5G operators to pool their dispersed micro‑datacenters, ensuring that users are always served by an edge host close to their current location. Yet today’s research stays almost exclusively user‑centric: trimming latency or energy but ignores the operators’ own constraints, i.e. heterogeneous servers, hard resource budgets and, above all, the need for balanced give‑and‑take across domains. This results in a brittle reactive offloading that can overwhelm the most generous partner. We tackle the problem from the operators’ perspective, casting one scheduling epoch of a federation as an exact‑potential game that jointly captures (i) per‑application deadlines, (ii) per‑server CPU/RAM/storage heterogeneity, and (iii) a fairness objective keeping each domain’s exports and imports in line. We then reach the game's equilibrium with a lightweight best‑response approach, \name, where orchestrators exchange only bids, never raw telemetry, and need only one message per epoch. We evaluate \name on a novel open‑source MEC‑federation simulator, configurable down to link latency, bandwidth and instruction counts. Experiments show that our solution reduces response time by 37\%, and boosts overall CPU/RAM utilization by up to 20\% compared to six baselines. All simulator code, scenarios, and experiments are openly available to foster reproducibility and future research.