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

Abstract

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.