ABSTRACT
Internet of Things (IoT) interconnects billions of devices by establishing a network that adheres to International Organization of Standardization (ISO) standards. These devices communicate with each other by sharing data regulated by the application. This is performed to accomplish a task or service that the application demands. The social or human-like behaviors are adapted in the IoT environment forming the Social IoT (SIoT). The SIoT integrates social networks in IoT-connected devices, making them unique and identifiable. Recent advancements in networking, intelligent network management, battery management, remote sensing, sensors, and other related technologies convinced users and designers to adopt IoT even for large-scale applications where the data involved is enormous. Leveraging the advancements in medical IoT, which focuses on healthcare to patients, can improve its service by removing redundant manual processes, long wait times, and providing other automated services. The advancements in real-time healthcare IoT devices and wearables make a strong case for implementing SIoT in the healthcare domain. SIoT in the healthcare domain has the potential to benefit users on a large scale. This chapter comprehends the challenges and solutions of using SIoT in medical and healthcare solutions from a networking quality of service (QoS) perspective. In addition, this chapter compares the intelligent algorithm, which can be used to improve the QoS of SIoT. Achieving higher QoS is necessary for healthcare services, especially while handling data from emergency and intensive care units. These data cannot tolerate errors and delays. Intelligent network management has become unavoidable in the health and medical services to achieve a higher degree of QoS system, which indirectly decreases data transfer time. The data from the sensor devices sent across the network leads to data loss and delay in data transmission due to congestion in the network and gateway devices. The optimized algorithms incorporated with the delay-based algorithm improves the QoS predominantly and reduces the delay in data transfer. Similarly, the particle swarm optimization algorithm allocates resources over the network and dynamically makes the network adapt to increased and reduced data flow, which reduces the delay and improves the QoS. Intelligent optimized delay algorithm (IODA) is proposed to improve the network performance by reducing the delay and using available bandwidth for data transfer in SIoT.
