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Adaptive Resource Balancing for Serviceability Maximization in Fog Radio Access Networks
Author(s) -
Nhu-Ngoc Dao,
Junwook Lee,
Duc-Nghia Vu,
Jeongyeup Paek,
Joongheon Kim,
Sungrae Cho,
Ki-Sook Chung,
Changsup Keum
Publication year - 2017
Publication title -
ieee access
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.587
H-Index - 127
ISSN - 2169-3536
DOI - 10.1109/access.2017.2712138
Subject(s) - aerospace , bioengineering , communication, networking and broadcast technologies , components, circuits, devices and systems , computing and processing , engineered materials, dielectrics and plasmas , engineering profession , fields, waves and electromagnetics , general topics for engineers , geoscience , nuclear engineering , photonics and electrooptics , power, energy and industry applications , robotics and control systems , signal processing and analysis , transportation
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.

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