Cloud of Things for Sensing as a Service: Sensing Resource Discovery and Virtualization

We propose Cloud of Things for Sensing as a Service: a global architecture that scales up cloud computing by exploiting the global sensing resources of the highly dynamic and growing Internet of Things (IoT) to enable remote sensing. The proposed architecture scales out by augmenting the role of edge computing platforms as cloud agents that discover and virtualize sensing resources of IoT devices. Cloud of Things enables performing in-network distributed processing of sensing data offered by the globally available IoT devices and provides a global platform for meaningful and responsive sensing data analysis and decision making. We design cloud agents algorithmic solutions bearing in mind the onerous to track dynamics of the IoT devices by centralized solutions. First, we propose a distributed sensing resource discovery algorithm based on a gossip policy that selects IoT devices with predefined sensing capabilities as fast as possible. We also propose RADV: a distributed virtualization algorithm that efficiently deploys virtual sensor networks on top of a subset of the selected IoT devices. We show, through analysis and simulations, the potential of the proposed algorithmic solutions to realize virtual sensor networks with minimal physical resources, reduced communication overhead, and low complexity.