论文标题
无线异质网络中缓存的空间浓度
Spatial Concentration of Caching in Wireless Heterogeneous Networks
论文作者
论文摘要
我们为无线异质网络提出了一个分散的缓存策略，该策略根据缓存节点之间的成对交互做出内容放置决策。我们称我们提出的方案γ-排斥缓存位置（GEC），其中参数γ控制了一个排除半径，该半径不鼓励附近的缓存存储冗余内容。 GEC考虑了项目的受欢迎程度以及节点的缓存优先级，并利用负面依赖性，以放松经典的0-1 knapsack问题，以产生跨缓存的空间平衡采样。我们表明，GEC保证所需的高速缓存存储大小的浓度（降低的差异）比最高的状态更高，并且可以使用高概率来满足缓存尺寸约束。给定缓存命中概率目标，我们比较了三个缓存方案所需的缓存大小的95 \％置信区间：（i）独立放置，（ii）硬排除缓存（HEC）和（iii）拟议的GEC方法。对于均匀的空间流量，我们证明GEC分别超过（i）和（ii）的高速缓存大小约为3倍和2倍。对于基于城市场景中现实的高峰时段变化的非均匀空间流量，收益更大。
We propose a decentralized caching policy for wireless heterogeneous networks that makes content placement decisions based on pairwise interactions between cache nodes. We call our proposed scheme γ-exclusion cache placement (GEC), where a parameter γ controls an exclusion radius that discourages nearby caches from storing redundant content. GEC takes into account item popularity and the nodes' caching priorities and leverages negative dependence to relax the classic 0-1 knapsack problem to yield spatially balanced sampling across caches. We show that GEC guarantees a better concentration (reduced variance) of the required cache storage size than the state of the art, and that the cache size constraints can be satisfied with high probability. Given a cache hit probability target, we compare the 95\% confidence intervals of the required cache sizes for three caching schemes: (i) independent placement, (ii) hard exclusion caching (HEC), and (iii) the proposed GEC approach. For uniform spatial traffic, we demonstrate that GEC provides approximately a 3x and 2x reduction in required cache size over (i) and (ii), respectively. For non-uniform spatial traffic based on realistic peak-hour variations in urban scenarios, the gains are even greater.
