Optimal Composition of a Virtual Sensor for Efficient Virtualization Within Sensor-cloud

The work focuses on optimal formation of virtual sensors (VSs) within a sensor-cloud infrastructure. Existing work on sensor-cloud have considered the formation of VS with the maximal set of compatible physical sensor nodes. However, as these underlying nodes are highly resource constrained, inefficient and redundant utilization of the nodes takes a toll on the entire performance of the cloud and the network. In this work, we propose algorithms for efficient virtualization of the physical sensor nodes and optimal composition of VSs - within the same geographic region (CoV-I) and spanning across multiple regions (CoV-II). Experimental results demonstrate that, compared to the existing strategy of maximal composition of VSs, CoV-I improves the cumulative energy consumption and the network lifetime by 34.9% and 61.04%, respectively, and CoV-II enhances the parameters by 68.4% and 29.59%, respectively.