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학술지 Adaptive Resource Balancing for Serviceability Maximization in Fog Radio Access Networks
Cited 34 time in scopus Download 2 time Share share facebook twitter linkedin kakaostory
저자
NHU-NGOC DAO, 이정욱, DUC-NGHIA VU, 백정엽, 감중헌, 조성래, 정기숙, 금창섭
발행일
201706
출처
IEEE Access, v.5, pp.14548-14559
ISSN
2169-3536
출판사
IEEE
DOI
https://dx.doi.org/10.1109/ACCESS.2017.2712138
협약과제
17ZH1500, 단말 근접 실시간 스마트 서비스추천플랫폼 기술 개발, 정기숙
초록
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 cache-aware UE association approaches in terms of serviceability, availability, and throughput.
키워드
backpressure algorithm, Fog radio access network (F-RAN), Hungarian method, mobile remote radio head (RRH), resource balancing, serviceability maximization
KSP 제안 키워드
Adaptive resource, Backpressure Algorithm, Cache-aware, F-RAN, Fog radio access networks, Hungarian method, Internet of thing(IoT), Network topology, Remote Radio Head(RRH), Resource Block(RB), Resource balancing