Priority-aware Gray-box Placement of Virtual Machines in Cloud Platforms

TL;DR

This paper proposes a priority-aware VM placement strategy that leverages workload patterns to reduce resource contention and hot spots in cloud data centers, aiming to improve load balancing without costly migrations.

Contribution

It introduces a novel placement algorithm that considers workload patterns and VM priorities to mitigate resource contention and hot spots in cloud environments.

Findings

Workload pattern-aware placement reduces resource contention.

Prioritized placement improves application performance.

Mitigates hot spots without extensive VM migrations.

Abstract

Virtual machine (VM) placement is very important for cloud platforms. While techniques, such as live virtual machine migration, are very useful to balance the load in the data centers, they are expensive operations. In this position paper, we propose to minimize the chance of the load hot spots in the data center by applying the workload patterns of the VMs in the virtual machine placement algorithms - place VMs that require a lot of same type of resource across different physical servers. In this way, the resource competition of VMs on the same physical server is significantly mitigated. Meanwhile, we also consider the priorities of applications and VMs in our virtual machine placement algorithms.