Edgeoriented Collaborative Caching in InformationCentric Networking Innetwork caching is a key feature of informationcentric networking (ICN), in which routers take charge of caching passing contents. Such cache design enables efficient content distribution, but the benefit comes at a nontrivial cost, given adding workload to routers. With the emergence of edge computing, more edge devices with large storages are available, which is a good opportunity for new caching design. To this end, we propose a novel Edgeoriented Collaborative Caching (ECC) in ICN. In ECC, edge devices (such as edge server, micro datacenter, etc.) cache contents while routers only maintain cache indexes which are used to redirect subsequent requests towards the cached content. This enables ECC to work in a lightweight and collaborative fashion. We propose an optimization method to properly create cache indexes, considering both content popularity and cache benefit. Moreover, we also present a failure recovery mechanism to ensure system robustness. Simulation results show when deploying the same total cache capacity, ECC outperforms typical ICN caching schemes in terms of response latency, server load and bandwidth consumption of links.

An adaptive cache management approach in ICN with prefilter queues Abstract   In InformationCentric Networking (ICN), transmission does not depend on the ends of communication, but on the content itself. Innetwork cache plays an important role in ICN, it empowers nodes in ICN better mobility. It also shortens serving path, lightens load of server, reduces traffic and time delay, its efficiency seriously affects performance of entire network, and thus cache management in ICN draws much attention of researchers recently. Although there are a lot approaches have been proposed, a cache management scheme with better adaptability and less cost remains to be studied. To this end, we propose StatevalueandCacherateMethod (SCMethod) to manage cache resources in ICN, which comprises cache deployment policy and cache replacement policy. In cache level, we add prefilter queues in front of cache queue to filter out popular content to store in cache. In the perspective of node, according to factors that nodexe2x80x99s state and relative location on data forwarding path, we define node state and cache rate to select nodes with maximum of state value or minimum cache rate to cache content, and effectively mitigate data redundancy. In order to increase dynamics and adaptive of system for mobility of nodes, we employ cache hit ratio as feedback to dynamically adjust the number of prefilter queues in every node. With prefilter queues, we improve Least Recently Used (LRU) cache replacement method. We conduct extensive experiments in simulator Icarus (Saino et al., 2014 1) with both tree topology and realistic internet topologies, define four metrics to quantitatively evaluate performance of SCMethod and verify its efficacy of reducing latency and load. Simulation results demonstrate that SCMethod we proposed outperform several classic cache schemes of ICN.