Dynamic performance modeling framework for QoS-aware 5G-based IoT-edge systems

Dynamic performance modeling framework for QoS-aware 5G-based IoT-edge systems

연구 분야: Networking

학회: International Journal of Information Technology

The development of fifth-generation (5G) mobile networks, which enable new levels of near real-time automation of remote Internet of Things (IoT) devices. The current IoT concept will be strengthened by this advancement by broadening its potential uses, notably in the industrial and healthcare sector among others. IoT has a lot of potential for sectors like healthcare, manufacturing, mining, education, and autonomous vehicles when combined with the edge computing paradigms. To this end, Quality of service (QoS) and quality of experience (QoE) are key criteria for user satisfaction since in the majority of 5G-based IoT applications, the tolerable latency will be less than one millisecond. The usage of complex and intelligent methods between end-nodes, including edge and fog computing, is essential towards the success of 5G-driven IoT systems. A middleware, such as edge computing, can play a key role in realising the potential of IoT by allocating resources according to the QoS/QoE requirements of each service. This research proposes a theoretical framework by adopting the multi-servers queuing system for obtaining a QoS-aware implementation to favor dynamic resource allocation in IoT applications. We compare the proposed framework with some state-of-the-art benchmark strategies to validate its efficacy for IoT-Edge systems under different performance considerations. The numerical findings emphasise the model’s significance in the context of 5G mobile networks and IoT by depicting its sensitivity analysis over several QoS parameters.