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

机译:大规模智能空间中有效订阅控制参数的研究

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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:由于许多参与者参与分布式计算,因此智能空间(物联网)环境(IOT)环境的开发符合可扩展性挑战。特别是,许多传感器不断提供数据,许多推理员分析了所谓的数据来构建服务,并且许多移动客户端定期加入并留下智能空间来消耗服务。使用语义信息代理,网络交互是信息驱动的,它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派给订阅者时,我们继续研究主动控制策略。如果订阅通知丢失,则客户端乘法减少其检查间隔,并且否则会增加间隔。我们研究了策略参数的作用:客户可以选择初步并保持固定的值,或者客户可以根据最近的情况动态改变它们。目的我们提供数学模型,该模型表示作为策略参数的函数的重要绩效度量。通过实验评估验证分析结果。此外,我们的仿真实验可根据参与者的数量评估可扩展性。

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