Published Paper Details:

In the era of cloud computing, efficient Virtual Machine (VM) placement plays a pivotal role in optimizing resource utilization, improving performance, and maintaining robust security within data centers. This research paper presents an implemented algorithmic approach tailored for VM placement in Microsoft Azure cloud environments, aiming to enhance both operational features and key security aspects of modern data centers. The proposed solution focuses on dynamic resource allocation, load balancing, and minimization of latency while incorporating security constraints such as isolation, data integrity, and compliance. By mixing policy-aware scheduling and brainy placement heuristics, the algorithm enhance scalability and mitigates susceptibilities associated with multi-tenant structures. Experimental results demonstrate significant improvements in resource efficiency, response times, and adherence to security benchmarks when compared to traditional VM placement strategies with PM. This study contributes toward developing more secure, cost-effective, and performance-optimized cloud data centers using Azure's capabilities.