SLA_Driven Adaptive Resource Allocation for Virtualized Servers

Wei ZHANG; Li RUAN; Mingfa ZHU; Limin XIAO; Jiajun LIU; Xiaolan TANG; Yiduo MEI; Ying SONG; Yuzhong SUN

doi:10.1587/transinf.E95.D.2833

SLA_Driven Adaptive Resource Allocation for Virtualized Servers

Wei ZHANG, Li RUAN, Mingfa ZHU, Limin XIAO, Jiajun LIU, Xiaolan TANG, Yiduo MEI, Ying SONG, Yuzhong SUN

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In order to reduce cost and improve efficiency, many data centers adopt virtualization solutions. The advent of virtualization allows multiple virtual machines hosted on a single physical server. However, this poses new challenges for resource management. Web workloads which are dominant in data centers are known to vary dynamically with time. In order to meet application's service level agreement (SLA), how to allocate resources for virtual machines has become an important challenge in virtualized server environments, especially when dealing with fluctuating workloads and complex server applications. User experience is an important manifestation of SLA and attracts more attention. In this paper, the SLA is defined by server-side response time. Traditional resource allocation based on resource utilization has some drawbacks. We argue that dynamic resource allocation directly based on real-time user experience is more reasonable and also has practical significance. To address the problem, we propose a system architecture that combines response time measurements and analysis of user experience for resource allocation. An optimization model is introduced to dynamically allocate the resources among virtual machines. When resources are insufficient, we provide service differentiation and firstly guarantee resource requirements of applications that have higher priorities. We evaluate our proposal using TPC-W and Webbench. The experimental results show that our system can judiciously allocate system resources. The system helps stabilize applications' user experience. It can reduce the mean deviation of user experience from desired targets.

Publication: IEICE TRANSACTIONS on Information Vol.E95-D No.12 pp.2833-2843

Publication Date: 2012/12/01

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Online ISSN: 1745-1361

DOI: 10.1587/transinf.E95.D.2833

Type of Manuscript: Special Section PAPER (Special Section on Parallel and Distributed Computing and Networking)

Category: Computer System and Services

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Wei ZHANG, Li RUAN, Mingfa ZHU, Limin XIAO, Jiajun LIU, Xiaolan TANG, Yiduo MEI, Ying SONG, Yuzhong SUN, "SLA_Driven Adaptive Resource Allocation for Virtualized Servers" in IEICE TRANSACTIONS on Information, vol. E95-D, no. 12, pp. 2833-2843, December 2012, doi: 10.1587/transinf.E95.D.2833.
Abstract: In order to reduce cost and improve efficiency, many data centers adopt virtualization solutions. The advent of virtualization allows multiple virtual machines hosted on a single physical server. However, this poses new challenges for resource management. Web workloads which are dominant in data centers are known to vary dynamically with time. In order to meet application's service level agreement (SLA), how to allocate resources for virtual machines has become an important challenge in virtualized server environments, especially when dealing with fluctuating workloads and complex server applications. User experience is an important manifestation of SLA and attracts more attention. In this paper, the SLA is defined by server-side response time. Traditional resource allocation based on resource utilization has some drawbacks. We argue that dynamic resource allocation directly based on real-time user experience is more reasonable and also has practical significance. To address the problem, we propose a system architecture that combines response time measurements and analysis of user experience for resource allocation. An optimization model is introduced to dynamically allocate the resources among virtual machines. When resources are insufficient, we provide service differentiation and firstly guarantee resource requirements of applications that have higher priorities. We evaluate our proposal using TPC-W and Webbench. The experimental results show that our system can judiciously allocate system resources. The system helps stabilize applications' user experience. It can reduce the mean deviation of user experience from desired targets.
URL: https://globals.ieice.org/en_transactions/information/10.1587/transinf.E95.D.2833/_p

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@ARTICLE{e95-d_12_2833,
author={Wei ZHANG, Li RUAN, Mingfa ZHU, Limin XIAO, Jiajun LIU, Xiaolan TANG, Yiduo MEI, Ying SONG, Yuzhong SUN, },
journal={IEICE TRANSACTIONS on Information},
title={SLA_Driven Adaptive Resource Allocation for Virtualized Servers},
year={2012},
volume={E95-D},
number={12},
pages={2833-2843},
abstract={In order to reduce cost and improve efficiency, many data centers adopt virtualization solutions. The advent of virtualization allows multiple virtual machines hosted on a single physical server. However, this poses new challenges for resource management. Web workloads which are dominant in data centers are known to vary dynamically with time. In order to meet application's service level agreement (SLA), how to allocate resources for virtual machines has become an important challenge in virtualized server environments, especially when dealing with fluctuating workloads and complex server applications. User experience is an important manifestation of SLA and attracts more attention. In this paper, the SLA is defined by server-side response time. Traditional resource allocation based on resource utilization has some drawbacks. We argue that dynamic resource allocation directly based on real-time user experience is more reasonable and also has practical significance. To address the problem, we propose a system architecture that combines response time measurements and analysis of user experience for resource allocation. An optimization model is introduced to dynamically allocate the resources among virtual machines. When resources are insufficient, we provide service differentiation and firstly guarantee resource requirements of applications that have higher priorities. We evaluate our proposal using TPC-W and Webbench. The experimental results show that our system can judiciously allocate system resources. The system helps stabilize applications' user experience. It can reduce the mean deviation of user experience from desired targets.},
keywords={},
doi={10.1587/transinf.E95.D.2833},
ISSN={1745-1361},
month={December},}

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TY - JOUR
TI - SLA_Driven Adaptive Resource Allocation for Virtualized Servers
T2 - IEICE TRANSACTIONS on Information
SP - 2833
EP - 2843
AU - Wei ZHANG
AU - Li RUAN
AU - Mingfa ZHU
AU - Limin XIAO
AU - Jiajun LIU
AU - Xiaolan TANG
AU - Yiduo MEI
AU - Ying SONG
AU - Yuzhong SUN
PY - 2012
DO - 10.1587/transinf.E95.D.2833
JO - IEICE TRANSACTIONS on Information
SN - 1745-1361
VL - E95-D
IS - 12
JA - IEICE TRANSACTIONS on Information
Y1 - December 2012
AB - In order to reduce cost and improve efficiency, many data centers adopt virtualization solutions. The advent of virtualization allows multiple virtual machines hosted on a single physical server. However, this poses new challenges for resource management. Web workloads which are dominant in data centers are known to vary dynamically with time. In order to meet application's service level agreement (SLA), how to allocate resources for virtual machines has become an important challenge in virtualized server environments, especially when dealing with fluctuating workloads and complex server applications. User experience is an important manifestation of SLA and attracts more attention. In this paper, the SLA is defined by server-side response time. Traditional resource allocation based on resource utilization has some drawbacks. We argue that dynamic resource allocation directly based on real-time user experience is more reasonable and also has practical significance. To address the problem, we propose a system architecture that combines response time measurements and analysis of user experience for resource allocation. An optimization model is introduced to dynamically allocate the resources among virtual machines. When resources are insufficient, we provide service differentiation and firstly guarantee resource requirements of applications that have higher priorities. We evaluate our proposal using TPC-W and Webbench. The experimental results show that our system can judiciously allocate system resources. The system helps stabilize applications' user experience. It can reduce the mean deviation of user experience from desired targets.
ER -