DocumentCode
2992153
Title
The Fog Balancing: Load Distribution for Small Cell Cloud Computing
Author
Oueis, Jessica ; Strinati, Emilio Calvanese ; Barbarossa, Sergio
Author_Institution
LETI, CEA, Grenoble, France
fYear
2015
fDate
11-14 May 2015
Firstpage
1
Lastpage
6
Abstract
In 5G future wireless networks, the (ultra)-dense deployment of radio access points is a key drive for satisfying the increase of traffic demand and improving perceived users´ quality. (Ultra)-dense deployment combined with capillary edge cloud, the fog, leads the way for optimization of users´ Quality of Experience (QoE) and network performance. In this paper, we focus on improving users´ QoE by addressing the issue of load balancing in fog computing. In this paper, we consider the challenging case of multiple users requiring computation offloading, where all requests should be processed by local computation clusters resources. We propose a low complexity small cell clusters establishment and resources management customizable algorithm for fog clustering. Our simulation results show that the proposed algorithm yields high users´ satisfaction percentage of a minimum of 90% for up to 4 users per small cell, moderate power consumption, and/or high latency gain.
Keywords
5G mobile communication; cellular radio; cloud computing; pattern clustering; quality of experience; radio access networks; resource allocation; telecommunication traffic; 5G future wireless networks; QoE; capillary edge cloud; fog balancing; fog clustering; load balancing; load distribution; local computation cluster resources; low complexity small cell cluster establishment; network performance; perceived user quality; power consumption; radio access points; resource management customizable algorithm; small cell cloud computing; traffic demand; user quality of experience optimization; Clustering algorithms; Measurement; Mobile communication; Optimization; Power demand; Processor scheduling; Resource management;
fLanguage
English
Publisher
ieee
Conference_Titel
Vehicular Technology Conference (VTC Spring), 2015 IEEE 81st
Conference_Location
Glasgow
Type
conf
DOI
10.1109/VTCSpring.2015.7146129
Filename
7146129
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