Quality of Service in Scalable Software Defined Internet of Things

Abstract

A significant increase is expected in Beyond 5G (B5G) networks. The inclusion of a huge number of Internet of Things (IoT) nodes in B5G networks further complicates the design of such networks. These futuristic networks are expected to deal with this increased traffic and a massive number of nodes while ensuring that network delays do not exceed a certain threshold. In such networks, Quality of Service (QoS) provisioning has become vital, not only to guarantee certain key performance indicators but also to improve user experience. This thesis makes three contributions to the field of QoS provisioning in B5G IoT networks. First, a hybrid and scalable approach for end-to-end QoS provisioning is proposed, involving both clients and Software Defined Networking (SDN) controllers to address the challenges of increased traffic and the number of nodes. Each client tries to satisfy its own access QoS requirements by choosing optimal access device(s) and makes decisions based on locally available view. SDN controllers are then responsible for finding optimal paths in the core network to satisfy client core QoS requirements. Experimental results show that the proposed approach provides better QoS guarantees than several other access device selection and routing schemes. xiii The second contribution focuses on client-based access device selection for QoS provisioning. Due to the increased availability of processing and energy resources and heterogeneous QoS requirements in modern IoT nodes, a client-centric access device selection approach for QoS provisioning in multiple Radio Access Technologies (RATs) scenario is proposed. The proposed algorithm provides the ability to specify node-specific QoS requirements at each node, a better access device selection, and improved network scalability. For experimental evaluation, a hybrid indoor network consisting of Wireless Fidelity (WiFi) and Light Fidelity (LiFi) RATs has been considered. Experimental results show that the proposed technique outperforms conventional client-based access device selection approaches by up to 32.66% in network emulation and up to 50% in hardware experimentations. The last contribution focuses on the energy efficiency aspect in addition to QoS provisioning due to power constraints on an IoT node. A client-side energy-efficient Access Point (AP) selection approach is presented for QoS provisioning in hybrid WiFi and LiFi networks. Compared to conventional WiFi and LiFi approaches, the proposed technique outperforms them in energy efficiency at any data rate and in QoS provisioning at data rates higher than 10 Mbps for a network of 50 nodes. An adaptive transmission power mechanism is also presented, which improves the IoT node’s energy efficiency by transmitting at minimal transmission power required for satisfying the throughput QoS constraint. The analyses and results imply that the proposed end-to-end QoS provisioning architecture and algorithms could be utilized in next-generation IoT networks as they outperform conventionally used QoS provisioning techniques.