TY - GEN
T1 - An O(1)-competitive online caching algorithm for content centric networking
AU - Gharaibeh, Ammar
AU - Khreishah, Abdallah
AU - Khalil, Issa
N1 - Publisher Copyright:
© 2016 IEEE.
PY - 2016/7/27
Y1 - 2016/7/27
N2 - Since the emergence of Content Centric Networking (CCN) as a new paradigm for content delivery in the Internet, copious of research targeted the evaluation or the enhancement of CCN caching schemes. Motivated by providing the Internet Service Providers with incentives to perform caching, the increasing deployment of in-network cloudlets, and the low cost of storage devices, we study caching in CCN from an economical point of view, where the content providers pay the Internet Service Providers in exchange for caching their content items. We propose an online caching algorithm for CCN that does not require the exact knowledge of content items' popularities to minimize the total cost paid by the content providers. The total cost here is the sum of the caching costs and the retrieval costs. Our analysis shows that the proposed algorithm achieves an O(1) competitive ratio when compared to the optimal offline caching scheme that possesses the exact knowledge of content items' popularities. We also show through simulations that the proposed algorithm can cut the cost incurred by widely used caching schemes such as Leave Copy Down (LCD) and Leave Copy Everywhere (LCE) by up to 65%.
AB - Since the emergence of Content Centric Networking (CCN) as a new paradigm for content delivery in the Internet, copious of research targeted the evaluation or the enhancement of CCN caching schemes. Motivated by providing the Internet Service Providers with incentives to perform caching, the increasing deployment of in-network cloudlets, and the low cost of storage devices, we study caching in CCN from an economical point of view, where the content providers pay the Internet Service Providers in exchange for caching their content items. We propose an online caching algorithm for CCN that does not require the exact knowledge of content items' popularities to minimize the total cost paid by the content providers. The total cost here is the sum of the caching costs and the retrieval costs. Our analysis shows that the proposed algorithm achieves an O(1) competitive ratio when compared to the optimal offline caching scheme that possesses the exact knowledge of content items' popularities. We also show through simulations that the proposed algorithm can cut the cost incurred by widely used caching schemes such as Leave Copy Down (LCD) and Leave Copy Everywhere (LCE) by up to 65%.
UR - http://www.scopus.com/inward/record.url?scp=84983317324&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84983317324&partnerID=8YFLogxK
U2 - 10.1109/INFOCOM.2016.7524444
DO - 10.1109/INFOCOM.2016.7524444
M3 - Conference contribution
AN - SCOPUS:84983317324
T3 - Proceedings - IEEE INFOCOM
BT - IEEE INFOCOM 2016 - 35th Annual IEEE International Conference on Computer Communications
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 35th Annual IEEE International Conference on Computer Communications, IEEE INFOCOM 2016
Y2 - 10 April 2016 through 14 April 2016
ER -