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Providing Context as a Service Using Service-Oriented Mobile Indie Fog and Opportunistic Computing

机译:使用面向服务的移动独立雾和机会计算提供上下文即服务

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The increasing number of sensor-embedded mobile devices has motivated the research of mobile Sensing as a Service in which mobile devices can host Web servers to serve sensory data to the Internet of Things systems, urban crowd sensing systems and big data acquisition systems. Further, the improved processing power of modern mobile devices indicates the mobile devices are not only capable of serving sensory data but also capable of providing Context as a Service (CaaS) based on requesters' own interpretation algorithms. In order to demonstrate mobile CaaS, this paper proposes a service-oriented mobile Indie Fog server architecture, which enables dynamic algorithm execution and also supports distributed CaaS processing among mobile devices. Moreover, in order to optimise the process distribution, the proposed framework also encompasses a resource-aware process assignment scheme known as MIRA. Finally, the authors have implemented and evaluated the proposed framework on a number of real devices. Accordingly, the evaluation results show that the MIRA scheme can improve the process assignment in the collaborative mobile CaaS environment.
机译:越来越多的传感器嵌入式移动设备推动了移动传感即服务的研究,在该服务中,移动设备可以托管Web服务器,以将传感数据提供给物联网系统,城市人群传感系统和大数据采集系统。此外,现代移动设备的改进的处理能力表明,移动设备不仅能够提供感觉数据,而且能够基于请求者自己的解释算法来提供上下文即服务(CaaS)。为了演示移动CaaS,本文提出了一种面向服务的移动独立雾服务器架构,该架构支持动态算法执行并支持移动设备之间的分布式CaaS处理。此外,为了优化过程分配,所提出的框架还包含一种称为MIRA的资源感知过程分配方案。最后,作者已经在许多实际设备上实现并评估了所提出的框架。因此,评估结果表明,MIRA方案可以改善协作移动CaaS环境中的流程分配。

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