ABSTRACT Serviceability is the ability of a network to serve user equipments (UEs) within desired requirements (e.g., throughput, delay, and packet loss). High serviceability is considered as one of the key foundational criteria toward a successful fog radio access infrastructure satisfying the Internet of Things paradigm in the 5G era. In this paper, we propose an adaptive resource balancing (ARB) scheme for serviceability maximization in fog radio access networks wherein the resource block (RB) utilization among remote radio heads (RRHs) are balanced using the backpressure algorithm with respect to a time-varying network topology issued by potential RRH mobilities. The optimal UE selection for service migration from a high-RB-utilization RRH to its neighboring low-RB-utilization RRHs is determined by the Hungarian method to minimize RB occupation after moving the service. Analytical results reveal that the proposed ARB scheme provides substantial gains compared with the standalone capacity-aware, max-rate, and cacheaware UE association approaches in terms of serviceability, availability, and throughput. INDEX TERMS Fog radio access network (F-RAN), mobile remote radio head (RRH), resource balancing, serviceability maximization, Hungarian method, backpressure algorithm.
In REF , Dao et al. proposed an adaptive balancing scheme (ARB) to distribute tasks among edge servers in the remote radio heads in order to improve the serviceability of the network, especially in terms of task execution latency.
Adaptive Resource Balancing for Serviceability Maximization in Fog Radio Access Networks
IEEE Access
IEEE Access
Computer Science