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Enabling a Mobility Prediction-Aware Follow-Me Cloud Model

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Author: Sousa, B. · Zhao, Z. · Karimzadeh, M. · Palma, D. · Fonseca, V. · Simoes, P. · Braun, T. · Berg, J.H. van den · Pras, A. · Cordeiro, L.
Type:article
Date:2016
Publisher: IEEE Computer Society
Source:41st IEEE Conference on Local Computer Networks, LCN 2016, 7-10 November 2016, Dubai, UAE, 486-494
Identifier: 745358
ISBN: 9781509020546
Article number: 7796824
Keywords: Follow-me cloud · Content migration · Mobility prediction as a service · Information centric networking · Mobile cloud networking · Nano Technology · NI - Nano Instrumentation · TS - Technical Sciences

Abstract

The location of data centres is crucial when mobile network operators are moving towards cloudified mobile networks to optimize resource utilization and to improve performance of services. Quality of Experience (QoE) can be enhanced in terms of content access latency, by placing user content at locations where they will be present in the future. The Follow-Me Cloud (FMC) concept aims at optimising operations of moving Mobile Network Operators Services towards cloudified environments, where Information Centric Networking (ICN) and the appropriate content migration policies are of paramount importance. However, several factors need to be considered, including user movements and mobility prediction (MP), content popularity, and migration. This paper addresses all these aspects by implementing a fully integrated multi-criteria FMC and mobility prediction mechanisms (MP-FMC) on a cloud infrastructure. Experimental evaluation shows that MP-FMC can be orchestrated on-demand within a reasonable time frame, and it could deliver ≈ 33% improvement of content retrieval time.