NDLI: Approximation Algorithms for Mobile Data Caching in Small Cell Networks

Content Provider	IEEE Xplore Digital Library
Author	Poularakis, K. Iosifidis, G. Tassiulas, L.
Copyright Year	1972
Abstract	Small cells constitute a promising solution for managing the mobile data growth that has overwhelmed network operators. Local caching of popular content items at the small cell base stations (SBSs) has been proposed to decrease the costly transmissions from the macrocell base stations without requiring high capacity backhaul links for connecting the SBSs with the core network. However, the caching policy design is a challenging problem especially if one considers realistic parameters such as the bandwidth capacity constraints of the SBSs that can be reached in congested urban areas. We consider such a scenario and formulate the joint routing and caching problem aiming to maximize the fraction of content requests served locally by the deployed SBSs. This is an NP-hard problem and, hence, we cannot obtain an optimal solution. Thus, we present a novel reduction to a variant of the facility location problem, which allows us to exploit the rich literature of it, to establish algorithms with approximation guarantees for our problem. Although the reduction does not ensure tight enough bounds in general, extensive numerical results reveal a near-optimal performance that is even up to 38% better compared to conventional caching schemes using realistic system settings.
Starting Page	3665
Ending Page	3677
Page Count	13
File Size	1083716
File Format	PDF
ISSN	00906778
Volume Number	62
Issue Number	10
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2014-01-01
Publisher Place	U.S.A.
Access Restriction	One Nation One Subscription (ONOS)
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Base stations Scattering Approximation algorithms Routing Approximation methods Bandwidth Computer architecture small cell networks Caching and routing algorithms network optimization facility location problems
Content Type	Text
Resource Type	Article
Subject	Electrical and Electronic Engineering

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