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The Cognitive Internet of Things: A Unified Perspective

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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.

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Notes

  1. Notice that the analysis is general and is not affected by considering the uplink of the primary cellular network.

  2. In this paper, we consider the Slotted-ALOHA type access strategy for a CIoT network. However, the spectral access probability computed here, can be effectively mapped to the carrier sensing threshold for a CSMA/CA type protocol.

  3. This follows from the Slivnyak’s theorem and the palm distribution of HPPPs [11].

  4. With a slight abuse of notation, \(\mathbf {x}\in \mathbb {R}^{2}\) is employed to refer to the node’s location as well as the node itself.

  5. Notice that the model remains same for the indoor setting except for the fact that the output power is attenuated by a factor of 10-100. This is because, indoor panels cannot harvest the direct component of a solar energy field and must rely on the diffuse component.

  6. For medium to average size cities, variations in longitude and latitude are not significant. Thus neglecting the environmental randomness, the ET irradiance does not vary significantly over the spatial scale of neighborhood.

  7. This is because of the independence of the point processes \({\Pi }_{p}\left (\lambda _{p}\right )\) and \({\Pi }_{c}\left (\lambda _{c}\right )\).

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Authors and Affiliations

  1. Department of Electronic and Electrical Engineering, University of Leeds, Leeds, LS2 9JT, UK

    Asma Afzal, Syed Ali Raza Zaidi, Mounir Ghogho & Desmond C. McLernon

  2. Texas A, M University, Doha, Qatar

    Muhammad Zeeshan Shakir & Khalid Qaraqe

  3. University of Surrey, Guildford, UK

    Muhammad Ali Imran

  4. Kuwait University, Kuwait City, Kuwait

    Athanasios V. Vasilakos

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  1. Asma Afzal
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  2. Syed Ali Raza Zaidi
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  3. Muhammad Zeeshan Shakir
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  5. Mounir Ghogho
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  6. Athanasios V. Vasilakos
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  7. Desmond C. McLernon
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  8. Khalid Qaraqe
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Correspondence to Asma Afzal.

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Afzal, A., Zaidi, S.A.R., Shakir, M.Z. et al. The Cognitive Internet of Things: A Unified Perspective. Mobile Netw Appl 20, 72–85 (2015). https://doi.org/10.1007/s11036-015-0583-6

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