Building security and resource optimisation techniques into dynamic Internet of Things (IoT) design processes

Abstract

Internet of Things the umbrella word for extending the internet beyond smartphones and computers to an entire range of things is an interconnection of networks that brings about societal, industrial, and business opulence. Internet of Things has seen an explosive growth rate over the years, a recent forecast by International Data Corporation suggests that there will be an estimated 41.6 billion connected devices generating over seventy-nine (79) zettabytes (ZB) of data by 2025. Internet of Things’ distributed nature with a centralised ecosystem implies it is plagued with several complexities not limited to scalability, latency, nodes’ energy dissipation, computational overhead, Quality of Service, resource optimisation, privacy, and security. Internet of Things’ resource allocation problem that hinders its efficiency requires effective resource load balancing strategies that distribute traffic across nodes. Appropriate management of the load balancing approach implies a core networking solution that improves IoT nodes’ availability and responsiveness. In addition, proper use of load balancing schemes prevents overutilisation or underutilisation of nodes within the network. Internet of Things’ increasing popularity and pertinence in daily living implies complex and dynamic connections of ubiquitous devices, besides that, Internet of Things’ heterogeneous nature infers dynamic security requirements of utmost importance to the system’s ever-increasing nomenclature. Consequently, the research aims to present a framework that is appropriate for the modelling and reasoning about Internet of Things’ resource optimisation and dynamic security requirements. The devised framework is used to simulate a model that incorporates security features from the onset of the developmental lifecycle for better prospects of securing Internet of Things. Furthermore, the simulated model aims to improve system efficiency by adequately managing Internet of Things’ multiple Objective Resource Allocation Problem. A mixed methodology with a realist and systematic view is used, the research method deployed is experimental thus aiding the modelling and simulation of the proposed solution using python programming language and the anaconda framework. The developed model is a decentralised three-tiered topology that consists of the edge node, dew, and cloud layers. These layers are structured using the edge computing paradigm and clustering techniques, the layers also make use of a hybrid algorithm as well as Blockchain technologies. The four (4) merged paradigms work together diligently to bring about the desired secure, efficient, and resource optimised IoT. Simulation results show the efficacy of the edge computing paradigm in conjunction with the hybrid algorithm in bringing about resource optimisation (chapter 4); the effects of the Particle Swarm Optimisation clustering technique on the hybrid approach of chapter 4 for resource optimisation of Internet of Things (chapter 5); and illustrate the prospects of the Hyperledger fabric Blockchain in providing the much-needed security features for IoT systems as well as further enhancing system efficiency are presented (chapter 6). Finally, the comparative analysis made across all chapters indicate the proposed solution’s superiority over the current centralised optimisation approach, Ant colony clustering technique, low-energy adaptive clustering hierarchy (LEACH), centralised architecture-based clustering algorithm for load-balancing (CLBCA), and Blockchain-Based Consumer Electronics for Data Sharing and Secure Payment platform (BC-EDSSP).