Distributed Caching based on Decentralized Learning Automata

被引:0
|
作者
Marini, Loris [1 ]
Li, Jun [1 ]
Li, Yonghui [1 ]
机构
[1] Univ Sydney, Sch Elect Engn, Sydney, NSW 2006, Australia
关键词
NETWORKS; DELIVERY;
D O I
暂无
中图分类号
TN [电子技术、通信技术];
学科分类号
0809 ;
摘要
In this paper we propose a novel distributed caching scheme in Heterogeneous Cellular Networks (HCN). We are interested in optimizing the content placement in order to minimize the downloading latency. We achieve this in a decentralized manner, based on a game of independent learning automata (LA). First, we propose a faster-converging discrete generalist pursuit algorithm (DGPA) for a single LA based on the concept of conditional inaction (CI), referred to as CI-DGPA. Then we develop a framework for a game of LA based on CI-DGPA defining the information exchange between learners and the environment. Within this framework, we design a reward function that approaches the performance of a greedy algorithm and show that a smart partition of the search space can double the game convergence speed, thereby halving the overhead due to signalling. Simulations show that our scheme can approach the greedy algorithm with a very small performance gap while providing a much lower computational complexity.
引用
收藏
页码:3807 / 3812
页数:6
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