Optimizing Cloud Performance: A Comprehensive Study of Load Balancing Strategies and Algorithms
Keywords:
Cloud Computing, Load balancing, Scheduling AlgorithmsAbstract
Cloud computing is essentially a big system of interconnected servers that store data and run programs over the internet. As this technology grows, it's important to ensure it runs smoothly and efficiently. One way to do this is through load balancing, where tasks and data are distributed evenly across the servers to avoid overloading any one of them. However, achieving effective load balancing can be challenging due to factors like the geographical spread of servers and differences in their capabilities. In our study, we delved into various load balancing strategies used in cloud computing, including Min-Min, Max-Min, Least Connection, Source Hash, Least Bandwidth, and Round Robin. While these strategies are helpful in optimizing performance, they also come with their own set of limitations and challenges. By examining the pros and cons of different methods, our study gives us a better understanding of how load balancing works in cloud computing right now. It also helps us see how we can make things better in the future. We want to keep improving cloud computing so it can handle all the tasks it needs to in today's digital world. Our research helps us learn more about cloud computing and how we can make it stronger and more efficient in the years to come.
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