Dynamic resource management in Cloud datacenters for Server consolidation

TL;DR

This paper presents a dynamic resource management algorithm for cloud datacenters focusing on CPU and memory, aiming to optimize resource utilization and reduce wastage through bin packing techniques.

Contribution

It introduces the DRMA algorithm that applies best fit bin packing to improve resource management in cloud datacenters, specifically targeting CPU and memory.

Findings

DRMA reduces resource underutilization.

Best fit algorithm improves resource allocation efficiency.

Potential for better service delivery in cloud datacenters.

Abstract

Cloud resource management has been a key factor for the cloud datacenters development. Many cloud datacenters have problems in understanding and implementing the techniques to manage, allocate and migrate the resources in their premises. The consequences of improper resource management may result into underutilized and wastage of resources which may also result into poor service delivery in these datacenters. Resources like, CPU, memory, Hard disk and servers need to be well identified and managed. In this Paper, Dynamic Resource Management Algorithm(DRMA) shall limit itself in the management of CPU and memory as the resources in cloud datacenters. The target is to save those resources which may be underutilized at a particular period of time. It can be achieved through Implementation of suitable algorithms. Here, Bin packing algorithm can be used whereby the best fit algorithm is deployed to obtain results and compared to select suitable algorithm for efficient use of resources.