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首页> 外文期刊>Wireless personal communications: An Internaional Journal >A Novel Adaptive Framework for Wireless Push Systems Based on Distributed Learning Automata
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A Novel Adaptive Framework for Wireless Push Systems Based on Distributed Learning Automata

机译：基于分布式学习自动机的无线推送系统自适应框架

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摘要

A novel adaptive scheme for wireless push systems is presented in this paper. In this wireless environment two entities play the most important role: the server side and the client side that is connected to the system. The server side is responsible to broadcast an item per transmission in order to satisfy the clients' requests. The performance of the server side depends on item selections. Hence, the server broadcasts an item and the clients are satisfied if the transmitted item was the desired one. In this work, a set of learning automata try to estimate the client demands in a distributed manner. More specifically, an autonomous learning automaton is utilized on each client group, since the clients are gathered into groups based on their location. The output of each automaton is combined in order to produce a well-performed transmission schedule. Concurrently, a round robin phase is adopted, giving the opportunity to the non-popular items to be transmitted. In this manner, the various client demands are treated fairly. The introduced technique is compared with a centralized adaptive scheme and the results indicate that the proposed scheduling framework outperforms the centralized one, in terms of response time and fairness.
机译：本文提出了一种新型的无线推送系统自适应方案。在这种无线环境中，两个实体扮演着最重要的角色：连接到系统的服务器端和客户端。服务器端负责在每次传输中广播一个项目，以满足客户的请求。服务器端的性能取决于项目的选择。因此，服务器广播一个项目，如果发送的项目是所需的项目，则客户满意。在这项工作中，一组学习自动机试图以分布式方式估计客户需求。更具体地，在每个客户组上利用自主学习自动机，因为客户是基于他们的位置被分组到组中的。组合每个自动机的输出，以生成性能良好的传输计划。同时，采用循环阶段，从而使非受欢迎的项目有机会被发送。以这种方式，各种客户需求得到公平对待。将引入的技术与集中式自适应方案进行比较，结果表明，所提出的调度框架在响应时间和公平性方面均优于集中式调度方案。

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