ECCO: Cloud Energy Optimization and Load Balancing

The term “cloud computing” refers to a technique that makes computer resources, such as processing power, data storage, and application-oriented services, available on demand. This research paper focuses on optimizing load balancing and energy optimization by using virtual scheduling techniques. Before that, various scheduling algorithms were implemented for better request handling, such as random dens, heroes, dens, round-robin, and so on. However, it requires more flexible and efficient request handling, which is why we proposed an energy optimization and load-balanced scheduling approach for cloud computing (ECCO). This approach improves the performance of load balancing, energy optimization, and load-balanced scheduling (user to end server node). In the analysis part, we analyze the cloud network behavior in terms of average energy consumption, load, average delay, data received and task handling by virtual machine. Those results are compared with various scheduling approaches, i.e., round robin, random, dens, and ECCO, and we get that ECCO provides better load balancing and an energy-optimized scheduling algorithm for cloud computing.