Approximation Algorithms for Mobile Data Caching in Small Cell Networks

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 requir...

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Bibliographic Details
Published in:IEEE transactions on communications Vol. 62; no. 10; pp. 3665 - 3677
Main Authors: Poularakis, Konstantinos, Iosifidis, George, Tassiulas, Leandros
Format: Journal Article
Language:English
Published: New York IEEE 01.10.2014
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:
Algorithms
Approximation algorithms
Approximation methods
Bandwidth
Base stations
Caching
Computer architecture
Heuristic
Mathematical analysis
Mathematical models
Networks
Product introduction
Radio equipment
Reduction
Routing
Scattering
Stations
Telecommunications industry
Caching and routing algorithms
small cell networks
facility location problems
network optimization
ISSN:0090-6778, 1558-0857
Online Access:Get full text
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Summary: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.
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ISSN:0090-6778
1558-0857
DOI:10.1109/TCOMM.2014.2351796