Towards fairness and QoE-based edge allocation for multiplayer virtual reality applications in edge computing

Edge computing has emerged as the next big thing in distributed computing, by extending the cloud paradigm and offering efficient ways to engage with latency-intolerant applications, such as Virtual Reality (VR) multiplayer games. In edge computing, the service providers can benefit from existing cellular infrastructure to deploy services on edge servers that reside in close proximity to the users. Given the limited available budget for edge resource investment, one fundamental problem that manifests is the discovery of a prudent edge allocation strategy, that will efficiently prescribe which users are assigned to which edge servers, in order to tackle application-specific requirements, like minimizing system deployment costs. In this paper, considering the frequent interactions and view inconsistencies occurring among multiple users immersed in the same VR game, we address the problem from the users' perspective, focusing on improving their edge admission rate, resource provisioning and overall fairness, in order to subsequently maximize the average Quality of Experience (QoE). We call this the "Fairness and QoE-Based Edge Allocation" (FQEA) problem, formally formulating its properties and theoretically proving its complexity. However, discovering optimal solutions to the NP-hard FQEA in large-scale VR scenarios is challenging. Hence, we propose FQEA-H, a heuristic algorithm to generate allocation strategies in reasonable time. Comprehensive simulations, conducted on a real-world topological trace, demonstrate how FQEA-H can tackle the problem effectively, generally outperforming both the baseline and state-of-the-art alternatives.