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Study of active subscription control parameters in large-scale smart spaces

机译:大型智能空间中主动订购控制参数的研究

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The development of smart spaces for Internet of Things (IoT) environments meets the scalability challenge since many participants are involved into the distributed computation. In particular, many sensors continuously provide data, many reasoners analyze the sensed data to construct services, and many mobile clients regularly join and leave the smart space to consume the services. The network interaction is information- driven, using a semantic information broker, which implements a passive strategy for subscription. The strategy leads to performance bottleneck. We continue our study of the active control strategy, when a part of subscription processing is delegated to the subscribers. The client multiplicatively decreases its check interval, if subscription notifications are lost, and additively increases the interval, otherwise. We study the role of strategy parameters: the client can select their values preliminary and keep fixed, or the client can change them dynamically depending on the recent situation. With the aim we provide mathematical model which represents important performance metrics as a function of strategy parameters. Analytical result are validated by experimental evaluation. Additionally, our simulation experiments evaluate the scalability in dependence on the number of participants.
机译:物联网(IoT)环境中智能空间的开发遇到了可扩展性挑战,因为许多参与者都参与了分布式计算。特别是,许多传感器不断提供数据,许多推理者分析感测到的数据以构建服务,并且许多移动客户端定期加入并离开智能空间来使用服务。网络交互是通过使用语义信息代理的信息驱动的,该语义代理实现了用于订阅的被动策略。该策略导致性能瓶颈。当一部分订阅处理委托给订阅者时,我们将继续研究主动控制策略。如果订阅通知丢失,则客户端会成倍地减少其检查间隔,否则会增加间隔。我们研究策略参数的作用:客户可以预先选择其值并保持不变,或者客户可以根据最近的情况动态地更改它们。以此为目标,我们提供了数学模型,该数学模型表示重要的绩效指标作为策略参数的函数。通过实验评估验证了分析结果。此外,我们的仿真实验根据参与者数量评估可伸缩性。

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