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Distributed Multi-agent Schemes for Predictable QoS on Heterogenous Wireless Networks

机译:异构无线网络上可预测QoS的分布式多主体方案

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In realizing cyber-physical systems, research on developing network supported with predictable Quality of Service (QoS) is extremely important. This study exploits heterogeneous networking as communication medium of cyber physical application using a distributed multi-agent scheme (DMAS). The DMAS is based on the concept of cooperation and the awareness algorithm. The proposed scheme is developed for supporting QoS management which consists of a collection of problem-solving agents with three modules: the knowledge source, the in-cloud blackboard system, and the control engine built into the scheme. A set of problem-solving agents autonomously process local tasks and cooperatively interoperate via an in-cloud blackboard system to guarantee QoS. An awareness algorithm, called the Q-learning algorithm, calculates the exceptive rewards of a handoff to all access networks. These rewards are then used by these problem solving agents to determine what to do. Through operations and cooperation among the active agents, a policy is selected and a user-accepted schedule that meets the specified QoS is generated. In addition, to realize actual results, an integrated test-bed emulation network based on NetFPGA-OpenFlow platform is purposed in this paper.
机译:在实现网络物理系统中,研究开发具有可预测的服务质量(QoS)的网络非常重要。这项研究利用分布式多代理方案(DMAS)将异构网络用作网络物理应用程序的通信介质。 DMAS基于合作和认知算法的概念。提出的方案是为支持QoS管理而开发的,该方案由具有三个模块的问题解决代理组成:知识源,云中黑板系统和方案中内置的控制引擎。一组解决问题的代理可以自主处理本地任务,并通过云中黑板系统协作进行互操作,以确保QoS。一种称为Q学习算法的感知算法可计算向所有接入网进行切换的例外奖励。然后,这些问题解决代理将使用这些奖励来确定该做什么。通过活动代理之间的操作和协作,选择策略,并生成满足指定QoS的用户接受的计划。此外,为了实现实际结果,本文旨在基于NetFPGA-OpenFlow平台的集成测试平台仿真网络。

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