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Adaptive Resource Balancing for Serviceability Maximization in Fog Radio Access Networks
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- Authors
- Nhu-Ngoc Dao, Junwook Lee, Duc-Nghia Vu, Jeongyeup Paek, Joongheon Kim, Sungrae Cho, Ki-Sook Chung, Changsup Keum
- Issue Date
- 2017-06
- Citation
- IEEE Access, v.5, pp.14548-14559
- ISSN
- 2169-3536
- Publisher
- IEEE
- Language
- English
- Type
- Journal Article
- Project Code
- 17ZH1500, Development of Technologies for Proximity, Real-time, and Smart Service Recommendation Platform , Ki-Sook Chung
- 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 cache-aware UE association approaches in terms of serviceability, availability, and throughput.
- KSP Keywords
- Adaptive resource, Backpressure Algorithm, Cache-aware, Fog radio access networks, Hungarian method, Internet of thing(IoT), Network topology, Remote Radio Head(RRH), Resource Block(RB), Resource balancing, Service migration