A Stochastic Model for Performance Evaluation of Hybrid Network Architectures of IoT with an Improved Design

Abstract

Hybridisation of networks is a trend that will continue to evolve for more efficient communication solutions. Hybrid power line communication (PLC) and wireless networks deployed for the Internet of Things (IoT) applications have improved the efficiency of low-power and lossy networks (LLNs). State-of-the-art solutions on hybrid networks are mainly application specific and does not provide a mathematical model to evaluate the network performance. Furthermore, the parallel PLC and wireless networks result in more power consumption due to the additional circuitry required to support and switch between two networks. There is a need for a generalized study on hybrid network architectures. A mathematical model must be developed to evaluate the performance of hybrid networks. Unlike parallel PLC and wireless networks, some intermediate solutions must be proposed that can offer the benefits of wired and wireless networks without increasing power consumption and circuit complexity. The paper presents a generalized study on hybrid network architectures. A hybrid network has been proposed that can offer the benefits of wired and wireless networks in the best possible way. A novel Markov-based stochastic model has been developed to evaluate the reliability of hybrid network designs. The analytical results obtained from Continuous Time Markov Chains (CTMC) have been validated by simulation using MATLAB. Spectral and energy efficiency have been evaluated for the hybrid designs along with a trade-off analysis. The proposed hybrid network (with 50% jump nodes being hybridized) is 33.53% more reliable for data transmission than parallel wired and wireless networks after 100 hours of operation.