Abstract In this article, we present a unified perspective on the cognitive internet of things (CIoT). It is noted that within the CIoT design we observe the convergence of energy harvesting, cognitive spectrum access and mobile cloud computing technologies. We unify these distinct technologies into a CIoT architecture which provides a flexible, dynamic, scalable and robust network design road-map for large scale IoT deployment. Since the prime objective of the CIoT network is to ensure connectivity between things, we identify key metrics which characterize the network design space. We revisit the definition of cognition in the context of IoT networks and argue that both the energy efficiency and the spectrum efficiency are key design constraints. To this end, we define a new performance metric called the 'overall link success probability' which encapsulates these constraints. The overall link success probability is characterized by both the self-sustainablitiy of the link through energy harvesting and the availability of spectrum for transmissions. With the help of a reference scenario, we demonstrate that well-known tools from stochastic geometry can be employed to investigate both the node and the network level performance. In particular, the reference scenario considers a large scale deployment of a CIoT network empowered by solar energy harvesting deployed along with the centralized CIoT device coordinators. It is assumed that CIoT network is underlaid with a cellular network, i.e., CIoT nodes share spectrum with mobile users subject to a certain co-existence constraint. Considering the dynamics of both energy harvesting and spectrum sharing, the overall link success probability is then quantified. It is shown that both the self-sustainability of the link, and the availability of transmission opportunites, are coupled through a common parameter, i.e., the node level transmit power. Furthermore, provided the co-existence constraint is satisfied the link level success in the presence of both the inter-network and intra-network interference is an increasing function of the transmit power. We demonstrate that the overall link level success probability can be maximized by employing a certain optimal transmit power. Characterization of such an optimal operational point is presented. Finally, we highlight some of the future directions which can benefit from the analytical framework developed in this paper.
Afzal et al. REF advocate that cognition must be extended to incorporate IoT specific design challenges, like energy harvesting, cognitive spectrum access and mobile cloud computing technologies.
The Cognitive Internet of Things: A Unified Perspective
Mobile Networks and Applications
Computer Science