A Multi-Objective QoS-Driven Dynamic Resource Allocation Framework for Self-Organizing Networks in Society of Things (SoT)

The exponential increase in the number of participants in the Society of Things (SoT), which encompasses various smart devices and systems, means new problems in orchestrating the Internet of Things (IoT). The delivery of quality of service variables across the different application types, such as multimedia, and achieving optimal coordination across self-organizing networks is paramount, mainly because these devices run independently of any centralized control. These networks’ dynamic and restricted character introduces additional challenges to reach approximately optimal performance. This work provides a new multi-objective, dynamic resource allocation model to tackle the QoS issues related to SoNs in the SoT environment. The proposed framework aims to manage many quality of services (QoS) parameters simultaneously, including latency time, throughput, resource allocation, and energy consumption. This work introduces a dynamic multiobjective resource allocation model to address QoS challenges in self-organizing networks (SoNs) within the Society of Things (SoT) environment. In addition, performance evaluations show that the proposed resource allocation scheme has better delay constraints, throughput, and energy efficiency than the existing schemes. The proposed framework is highly scalable and reliable for handling the issues of SoT networks, making it more suitable and adaptable to meet the demands of dynamic and share-constrained SoT applications.