An RTT-Aware Virtual Machine Placement Method

Li Quan,Zhiliang Wang,Fuji Ren

doi:10.3390/info9010004

Li Quan, Zhiliang Wang + Show 1 more

Open Access

https://doi.org/10.3390/info9010004

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Abstract

Virtualization is a key technology for mobile cloud computing (MCC) and the virtual machine (VM) is a core component of virtualization. VM provides a relatively independent running environment for different applications. Therefore, the VM placement problem focuses on how to place VMs on optimal physical machines, which ensures efficient use of resources and the quality of service, etc. Most previous work focuses on energy consumption, network traffic between VMs and so on and rarely consider the delay for end users’ requests. In contrast, the latency between requests and VMs is considered in this paper for the scenario of optimal VM placement in MCC. In order to minimize average RTT for all requests, the round-trip time (RTT) is first used as the metric for the latency of requests. Based on our proposed RTT metric, an RTT-Aware VM placement algorithm is then proposed to minimize the average RTT. Furthermore, the case in which one of the core switches does not work is considered. A VM rescheduling algorithm is proposed to keep the average RTT lower and reduce the fluctuation of the average RTT. Finally, in the simulation study, our algorithm shows its advantage over existing methods, including random placement, the traffic-aware VM placement algorithm and the remaining utilization-aware algorithm.

Highlights

With the popularization of the internet of things and cloud computing technology, a large number of smart devices are used by people [1,2,3]
The algorithms proposed in this paper run in this module, which can place the corresponding virtual machine (VM) in order to minimize the average round-trip time (RTT) for these requests
We mainly study an optimal virtual machine placement method for minimizing the average RTT for users’ requests

Summary

Introduction

With the popularization of the internet of things and cloud computing technology, a large number of smart devices are used by people [1,2,3]. A user’s specific request could be handled by one or more VMs in the cloud These VMs are placed on different physical machines (PMs) that may be geographically distributed and in different locations of the network topology. In order to meet the minimum delay requirements for requests, we take the round-trip time (RTT) [10] as the metric for placing VMs dynamically in a cloud. The dynamic VM placement is studied for minimizing average RTT of all requests. The adopted network topology of physical machines is based on fat-tree [11]. VM placement algorithm aimed at minimizing the average RTT for cloud service requests.

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