基于收益感知的信息中心网络缓存机制

doi:10.11959/j.issn.1000-436x.2016101

Abstract

Abstract:

The in-network caching system of information-centric networking had to deal with the popularity of huge number of content chunks and make efficient usage of storage resources.A content popularity based caching gain opti-mization model aimed to get maximum reduction of content retrieve cost was established,and a gain-aware caching scheme was proposed.By utilizing filtering effect of cache to request flow is scheme achieves caching cooperation and diversity potentially while maximizing caching gain of every single node.Bloom filter based sliding window strategy captures the content chunks with high caching gain according to request arrival interval and retrieval cost from the source.Analysis shows that the method can drastically reduce memory consumption caused by popularity monitoring.The simu-lation results illuminate that this scheme is well aware of content popularity based caching gain,and gets better band-width saving and cache hit ratio when content popularity is changing dynamically.

Key words: information-centric networking, content-based routing, caching scheme, content popularity

Long CHEN,Hong-bo TANG,Xing-guo LUO,Yi BAI,Zhen ZHANG. Gain-aware caching scheme for information-centric networking[J]. Journal on Communications, 2016, 37(5): 130-142.

Figures/Tables 11

符号	含义
N	缓存节点集合
S	内容源服务器集合
K	网络中的内容块集合
$g_{n}^{k}$	节点n上内容块k的外生请求到达率
$l_{n}^{k}$	节点n上内容块k的请求到达率
l_n	节点n上内容请求总到达率
$h_{s_{i}}^{k}$	时隙s_i中内容块k的命中次数
$d_{n}^{k}$	缓存节点n上是否存储有内容块k
s(k)	内容块k的源服务器
$c_{n}^{k}$	节点n从s(k)获取内容块k所产生的代价
v_n	节点n能够缓存内容块的数量
K_n	节点n缓存内容块的集合

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缓存机制	缓存决策依据	是否需要信息交互	是否依赖流行度信息	缓存命中率
CE^2，[3]	全部缓存	否	否	低
LCD、MCD^[7]	缓存命中事件	是	否	中
RCOne^[8]	缓存节点随机选择	是	否	中
ProbCache^[9，10]	缓存容量、节点位置	否	否	中
WAVE^[11]	文件访问次数	是	否	中
Betw^[12]	节点介数	否	否	中
Age-based^[14]	内容流行度、节点位置	是	是	高
Prob-PD^[15]	内容流行度、节点位置	否	是	高
Liu's^[16]	内容的流行规律	是	是	高
MAGIC^[17]	内容流行度、节点位置	是	是	高
Badov's^[18]	内容流行度、链路状态	是	是	高

Gain-aware caching scheme for information-centric networking

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