Published Paper Details:

The tremendous issues of handling the large flood of data have been brought about by the cloud computing field's fast development. By 2020, 247 EB will be achieved by data analytics and IoT-based applications, according to Cisco's Global Cloud Index. Load Managing strategies are critical in tackling cloud environments' data overflow. The study promotes Round Robin Load Managing and highlights how well it manages data overflow. Based on set policies, load managing techniques such IP hash, weighted round-robin, least connections, and round-robin allow the effective allocation of incoming traffic across active targets. One important remedy that is emphasized is cloud load management, which uses software-based techniques to keep an eye on the target's health inside a cluster. In order to avoid data loss and service outages, it foresees and manages unexpected increases in traffic, rerouting it to servers that aren't as busy. The book offers explanations on how the load distribution techniques are used, and a Pythonexample of the Round Robin algorithm.