Our work on optimal cache allocation in CCN has been accepted to appear in IEEE Trans. on Computers


Content-Centric Networking (CCN) is a promising framework to rebuild the Internetís forwarding substrate around the concept of content. CCN advocates ubiquitous in-network caching to enhance content delivery, and thus each router has storage space to cache frequently requested content. In this work, we focus on the cache allocation problem, namely, how to distribute the cache capacity across routers under a constrained total storage budget for the network. We first formulate this problem as a content placement problem and obtain the optimal solution by a two-step method. We then propose a suboptimal heuristic method based on node centrality, which is more practical in dynamic networks with frequent content publishing. We investigate through simulations the factors that affect the optimal cache allocation, and perhaps more importantly we use a real-life Internet topology and video access logs from a large scale Internet video provider to evaluate the performance of various cache allocation methods. We observe that network topology and content popularity are two important factors that affect where exactly should cache capacity be placed. Further, the heuristic method comes with only a very limited performance penalty compared to the optimal allocation. Finally, using our findings, we provide recommendations for network operators on the best deployment of CCN caches capacity over routers.



Yonggong Wang, Zhenyu Li, Gareth Tyson, Steve Uhlig and Gaogang Xie. Design and Evaluation of the Optimal Cache Allocation for Content-Centric Networking. To appear in IEEE Transactions on Computers, 2015

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