PHD thesis: enhancing the performance of using improved scheduling algorithms for large scale distributed systems of multi users network

This project aims to optimize cloud resource management using a hybrid Bat and Whale Optimization Algorithm (BA-WOA) in CloudSim. The Bat Algorithm ensures effective exploration, while the Whale Optimization Algorithm enhances exploitation for better resource allocation. The hybrid approach aims to reduce execution time, improve load balancing, and maximize resource utilization, offering an efficient solution for cloud environments. Objectives : To implement a hybrid Bat and Whale Optimization Algorithm (BA-WOA) for cloud resource management. To optimize resource allocation in cloud computing by improving load balancing and reducing execution time. To enhance cost-effectiveness by minimizing operational costs in resource scheduling. To evaluate the performance of the hybrid algorithm using metrics such as resource utilization, response time, and makespan. To compare the hybrid approach with existing optimization algorithms to assess its effectiveness in cloud environments. Note : This you can use any cloud provider for this project but it should be completed within the providers free tier . Time : 2 weeks maximum , the faster the very better