search query: @instructor Xiao, Yu / total: 11
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Author: | Chauhan, Maneesh |
Title: | Measurement And Analysis Of Networking Performance In Virtualised Environments |
Publication type: | Master's thesis |
Publication year: | 2014 |
Pages: | xi + 74 Language: eng |
Department/School: | Tietotekniikan laitos |
Main subject: | Tietokoneverkot (T-110) |
Supervisor: | Ylä-Jääski, Antti ; Hidell, Markus |
Instructor: | Xiao, Yu |
Electronic version URL: | http://urn.fi/URN:NBN:fi:aalto-201410282901 |
OEVS: | Electronic archive copy is available via Aalto Thesis Database.
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Location: | P1 Ark Aalto 2425 | Archive |
Keywords: | virtualisation kvm cloud computing network performance, measurement |
Abstract (eng): | Mobile cloud computing, having embraced the ideas like computation offloading, mandates a low latency, high speed network to satisfy the quality of service and usability assurances for mobile applications. Networking performance of clouds based on Xen and Vmw are virtualisation solutions has been extensively studied by researchers, although, they have mostly been focused on network through put and band width metrics. This work focuses on the measurement and analysis of networking performance of VMs in a small, KVM based data centre, emphasising the role of virtualisation overheads in the Host-VM latency and eventually to the overall latency experienced by remote clients. We also present some useful tools such as Drift analyser, Virto Calc and Trotter that we developed for carrying out specific measurements and analysis. Our work proves that an increase in a VM's CPU workload has direct implications on the network Round trip times. We also show that Virtualisation Overheads (VO) have significant bearing on the end to end latency and can contribute up to 70% of the round trip time between the Host and VM. Furthermore, we thoroughly study Latency due to Virtualisation Overheads as a networking performance metric and analyse the impact of CPU loads and networking workloads on it. We also analyse the resource sharing pat-terns and their effects amongst VMs of different sizes on the same Host. Finally, having observed a dependency between network performance of a VM and the Host CPU load, we suggest that in a KVM based cloud installation, work load profiling and optimum processor pinning mechanism can be effectively utilised to regulate network performance of the VMs. The findings from this research work are applicable to optimising latency oriented VM provisioning in the cloud datacentres, which would benefit most latency sensitive mobile cloud applications. |
ED: | 2014-11-02 |
INSSI record number: 49987
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