TY - GEN
T1 - Collaborative caching for multicell-coordinated systems
AU - Khreishah, Abdallah
AU - Chakareski, Jacob
N1 - Publisher Copyright:
© 2015 IEEE.
PY - 2015/8/4
Y1 - 2015/8/4
N2 - Cellular networks have become a major Internet gateway over which online video is increasingly accessed. Data caching in cellular networks brings the accessed content closer to the requesting clients, thus enhancing simultaneously the performance of the video application and the operational efficiency of the cellular network. State-of-the-art caching schemes for cellular networks either employ traditional approaches such as Least Recently Used (LRU) caching or optimize the cache placement at each base station independently. We study the problem of collaborative content caching among base stations such that their aggregate operational cost is minimized or the profit earned by the service provider is maximized, given their caching capacity constraints. We distinguish between two cases: (i) non-coded data in which a content item is either stored at a base station or not, and (ii) coded data, where segments of the fountain or network coded content item are stored at multiple base stations. For the non-coded case, we derive an integer programming formulation and prove its NP-completeness. We also design a fully polynomial-time approximation algorithm for solving the problem of interest. For the coded case, we derive a linear program formulation that can be solved in polynomial time. Our simulation results show that the proposed collaborative caching schemes provide considerable advances over non-collaborative competitors.
AB - Cellular networks have become a major Internet gateway over which online video is increasingly accessed. Data caching in cellular networks brings the accessed content closer to the requesting clients, thus enhancing simultaneously the performance of the video application and the operational efficiency of the cellular network. State-of-the-art caching schemes for cellular networks either employ traditional approaches such as Least Recently Used (LRU) caching or optimize the cache placement at each base station independently. We study the problem of collaborative content caching among base stations such that their aggregate operational cost is minimized or the profit earned by the service provider is maximized, given their caching capacity constraints. We distinguish between two cases: (i) non-coded data in which a content item is either stored at a base station or not, and (ii) coded data, where segments of the fountain or network coded content item are stored at multiple base stations. For the non-coded case, we derive an integer programming formulation and prove its NP-completeness. We also design a fully polynomial-time approximation algorithm for solving the problem of interest. For the coded case, we derive a linear program formulation that can be solved in polynomial time. Our simulation results show that the proposed collaborative caching schemes provide considerable advances over non-collaborative competitors.
KW - Multicell-coordinated systems
KW - caching
KW - cellular networks
KW - collaborative caching
KW - heterogeneous networks
UR - http://www.scopus.com/inward/record.url?scp=84943273736&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84943273736&partnerID=8YFLogxK
U2 - 10.1109/INFCOMW.2015.7179394
DO - 10.1109/INFCOMW.2015.7179394
M3 - Conference contribution
AN - SCOPUS:84943273736
T3 - Proceedings - IEEE INFOCOM
SP - 257
EP - 262
BT - 2015 IEEE Conference on Computer Communications Workshops, INFOCOM WKSHPS 2015
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - IEEE Conference on Computer Communications Workshops, INFOCOM WKSHPS 2015
Y2 - 26 April 2015 through 1 May 2015
ER -