Quality of Service Aware Data Delivery Protocol in Narrow Band Internet of Things Enabled Healthcare Systems

Abstract

The need for establishing smart hospitals is becoming increasingly evident due to a number of reasons driven by modern healthcare and technological breakthroughs. Internet of Things (IoT), Medical Sensors, Low Power Wide Area Network Technol ogy (LPWAN), Artificial intelligence (AI), Digital technologies, and Reliable Data Transmission Techniques are used by smart hospitals to improve patient care, opti mize resource management and streamline hospital operations. In order to handle the increasing complexity of healthcare delivery, smart hospitals are essential for various purposes. They improve automation in patient demand, increase oper ational effectiveness, lower the costs, and increase accessibility to healthcare by leveraging advanced technologies. In this dissertation, a suitable licensed LPWAN technology, namely Narrow band Internet of Things (NB-IoT) is chosen as a promising technology for health care applications since it reduces end to end latency. Due to the interference, limited bandwidth, and heterogeneity of generated data packets, developing a data transmission framework that offers differentiated Quality of Services (QoS) to the critical and non-critical data packets is challenging. The existing literature studies suffer from insufficient access scheduling considering heterogeneous data packets and relationship among them in healthcare applications. The first contribution of i Abstract ii this thesis is to develop an optimal resource allocation framework for NB-IoT that maximizes a user’s utility through event prioritization, rate enhancement, and in terference mitigation. The proposed Priority Aware Utility Maximization (PAUM) system ensures weighted fair access to resources. In second contribution, the utilization of Device-to-Device (D2D) communi cation among Narrowband Internet of Things (NB-IoT) devices offers significant potential for advancing intelligent healthcare systems by extending its superior data rates, low power consumption. In D2D communication, strategies to miti gate interference and ensure coexistence with cellular networks are crucial. These strategies are aimed at enhancing user data rates by optimally allocating spectrum and managing the transmission power of D2D devices, presenting a complex engi neering challenge. Existing studies are limited either by the inadequate integration of NB-IoT D2D communication methods for healthcare, lacking intelligent, dis tributed, and autonomous decision-making for reliable data transmission, or by in sufficient healthcare event management policies during resource allocation in smart healthcare systems. In this work, we introduce an Intelligent Resource Allocation for Smart Healthcare (iRASH) system, designed to optimize D2D communication within NB-IoT environments. The iRASH innovatively integrates the Density based Spatial Clustering of Applications with Noise (DBSCAN) and Ant Colony Optimization (ACO) algorithms to effectively address the unique requirements of healthcare applications. The proposed system utilizes Belief-Desire-Intention (BDI) agents for dynamic and intelligent clustering of D2D devices, facilitating autonomous decision-making and efficient resource allocation. This approach not only enhances data transmission rates but also reduces power consumption, and is formulated as a Multi-objective Integer Linear Programming (MILP) problem. Abstract iii Given the NP-hard nature of this problem, iRASH incorporates a polynomial-time meta-heuristic-based ACO algorithm, which provides a suboptimal solution. This algorithm adheres to the principles of distributed D2D communication, promoting equitable resource distribution and substantial improvements in utility, energy effi ciency, and scalability. Finally, its performances are validated through simulations on the Network Simulator version 3 (NS-3) platform, demonstrating significant ad vancements over state-of-the-art solutions in terms of utility, delay, fair resource distribution, data rate, power efficiency,and system adaptability. As high as im provements of 65% in utility, 45% in fair sharing of resources, 25% in delay, 15% in packet delivery ratio observed by PAUM system and 35% in utility cost and 50% in energy cost are demonstrated by the iRASH system compared to the benchmark, proving their effectiveness