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.

The fog balancing: Load distribution for small cell cloud computing / Oueis, Jessica; Calvanese Strinati, Emilio; Barbarossa, Sergio. - 2015:(2015), pp. 1-6. (Intervento presentato al convegno 81st IEEE Vehicular Technology Conference, VTC Spring 2015 tenutosi a Glasgow, UK) [10.1109/VTCSpring.2015.7146129].

The fog balancing: Load distribution for small cell cloud computing

Sergio Barbarossa
2015

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.
2015
81st IEEE Vehicular Technology Conference, VTC Spring 2015
Computer science applications1707 computer vision and pattern recognition; electrical and electronic engineering; applied mathematics
04 Pubblicazione in atti di convegno::04b Atto di convegno in volume
The fog balancing: Load distribution for small cell cloud computing / Oueis, Jessica; Calvanese Strinati, Emilio; Barbarossa, Sergio. - 2015:(2015), pp. 1-6. (Intervento presentato al convegno 81st IEEE Vehicular Technology Conference, VTC Spring 2015 tenutosi a Glasgow, UK) [10.1109/VTCSpring.2015.7146129].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/1164119
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