Context aware clustering and meta-heuristic resource allocation for NB-IoT D2D devices in smart healthcare applications

Abstract

The utilization of Device-to-Device (D2D) communication among Narrowband Internet of Things (NB-IoT) devices offers significant potential for advancing intelligent healthcare systems due to its superior data rates, low power consumption, and spectral efficiency. In D2D communication, strategies to mitigate 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 engineering challenge. Existing studies are limited either by the inadequate integration of NB-IoT D2D communication methods for healthcare, lacking intelligent, distributed, and autonomous decision-making for reliable data transmission, or by insufficient 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. 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 efficiency, and scalability. Our system is validated through simulations on the Network Simulator version 3 (NS-3) platform, demonstrating significant advancements over existing state-of-the-art solutions in terms of data rate, power efficiency, and system adaptability. As high as improvements of 35% in utility and 50% in energy cost are demonstrated by the iRASH system compared to the benchmark, proving its effectiveness. The outcomes highlight iRASH’s potential to revolutionize D2D communications in smart healthcare settings, paving the way for more responsive and reliable IoT applications.