User Allocation for Real-Time Applications with State Sharing in Fog Computing Networks

Abstract

Applications in which multiple users share the states in real-time over a network have been rapidly spreading, but network latency degrades their quality of service (QoS) and quality of experience (QoE). Although Fog computing effectively mitigates this problem, user allocation methods suitable for these applications with strict latency requirements have not yet been studied. Therefore, this paper proposes both offline and online methods that assume state sharing for user allocation in Fog environments. These methods not only reduce the mean of delays within each group composed of users who share the same states but also guarantee fairness among the users. The simulations demonstrate that our methods complete the allocation in a realistic time and outperform the baseline methods and architectures.