A COMPREHENSIVE LITERATURE STUDY ON LOAD BALANCING METHODS IN CLOUD COMPUTING WITH INTERNET OF THINGS
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Abstract
Incorporating IoT devices such as smart appliances, routers, sensors, and cellphones into a singular network is the novel concept behind the Internet of Things. Cloud computing manages the storage and the processing of data produced by these IoT devices which require extensive amounts of data. The cloud also enables real time analysis of data that allows fast decision-making. In settings that require the integration of Cloud Computing and Internet of Things like Cloud-IoT, making the most out of the infrastructure with effective load balancing techniques becomes critical. These techniques serve the purpose of drowning out the faults, increasing throughput, and lowering execution and response time while also ensuring that there is fair workload distribution. With the intent of balancing the distinct and complex features of IoT, this articles aims to provide a summary on the various techniques of load balancing within a cloud environment, covering both centralized techniques as well as more advanced ones. This study digs deeper into the performance metrics and challenges, as well as application scenarios of all solutions, including energy usage, execution period, scalability, and workflow adaptability. Lastly, we present a comparison of the leading load sharing algorithm's effectiveness on a few tested IoT cloud systems..
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