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Information centric sensor-cloud integration: An efficient model to improve wireless sensor networks' lifetime

机译：以信息为中心的传感器-云集成：提高无线传感器网络寿命的有效模型

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摘要

This paper proposes an efficient decoupling model for information producer (IPD) (i.e., physical sensor) and information provider (IPV) toward a semantic sensor-cloud integration to improve Wireless Sensor Networks' (WSN) lifetime. In particular, while IPDs produce sensing information, their IPVs, which are designed as virtual sensors on sensor-cloud based on network function virtualization, are responsible for providing sensing services to information consumers. By decoupling, IPVs can make sensing data available to applications (consumers) while allowing most of IPDs to sleep. Based on applications' requirement, IPVs are globally grouped into information correlated communities (ICC). An external information correlation based prediction scheme is then established on top of the ICC to enable an IPV to predict its IPD data accurately and controllably without requiring the IPD to wake up frequently. The model requires only one IPD within an ICC to be active in a round to maintain the prediction quality, thus minimizing 1) the number of sensors required to be active and 2) their traffic load while satisfying the requirement of applications. Obtained results show that the proposed system improves WSNs' energy efficiency and service availability significantly compared to the state-of-the-art schemes.
机译：本文针对信息产生者（IPD）（即物理传感器）和信息提供者（IPV）提出了一种有效的去耦模型，以实现语义传感器与云的集成，以提高无线传感器网络（WSN）的寿命。特别是，在IPD产生传感信息的同时，其IPV被设计为基于网络功能虚拟化的传感器云上的虚拟传感器，它们负责为信息消费者提供传感服务。通过解耦，IPV可以使传感数据可供应用程序（消费者）使用，同时允许大多数IPD进入睡眠状态。根据应用程序的要求，IPV会在全球范围内分组为信息相关社区（ICC）。然后，在ICC之上建立基于外部信息相关性的预测方案，以使IPV能够准确，可控地预测其IPD数据，而无需IPD频繁唤醒。该模型只需要一个ICC内的一个IPD即可全面激活以保持预测质量，从而在满足应用程序要求的同时将1）需要激活的传感器数量和2）流量负荷最小化。获得的结果表明，与最新方案相比，该系统显着提高了无线传感器网络的能源效率和服务可用性。

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