Shared Cache Optimized Adaptive Load Balancing Strategy for IoT Devices - Puppala, Tirupathi; Polala, Niranjan (International Journal of Intelligent Systems and Applications in Engineering, 2023)
As the use of wireless communication expands, so does the need for more complex, easy-to-use, and low-cost solutions. The need for network solutions ranging from wireless sensor networks to wireless ad-hoc networks to the Internet of Things prompted academics to engage in the development of acceptable network solutions. Inventions made by researchers have led to an increase in the desire for additional advancements in current researchers. In the beginning, research and development focused on network protocols. IoT devices are being employed in a variety of industries and are amassing an enormous amount of data through sophisticated applications, regardless. This necessitates study into IoT network load balancing. As IoT networks become more overburdened, researchers have made many efforts to find ways to reduce the communication costs that result. In these studies, the IoT nodes were recommended to be evenly distributed in the network's load. The data gathered by IoT nodes and the applications that handle that data will eventually be moved to the cloud, but this will take time. A cloud-based load balancer meeting the needs of IoT network protocols is the difficulty here. A new technique is proposed in this study to deal with IoT network frameworks' load management. The main problem of this study is to develop a load balancer that considers the limited energy and processing capabilities of IoT nodes, yet with the goal of increasing the response time of the IoT network. Consideration has been given to the low-effort integrations with current IoT frameworks in the design of the suggested algorithm for load balancer.