A User Experience-based Cloud Service Redeployment Mechanism KANG Yu Yu Kang, Yangfan Zhou, Zibin Zheng, and Michael R. Lyu {ykang,yfzhou, zbzheng,lyu}@cse.cuhk.edu.hk Department of Computer Science & Engineering The Chinese University of Hong Kong Hong Kong, China School of Computer Science National University of Defence Technology Changsha, China
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A User Experience-based Cloud Service Redeployment Mechanism KANG Yu Yu Kang, Yangfan Zhou, Zibin Zheng, and Michael R. Lyu {ykang,yfzhou, zbzheng,lyu}@cse.cuhk.edu.hk.
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A User Experience-based Cloud Service Redeployment
Mechanism
KANG Yu
Yu Kang, Yangfan Zhou, Zibin Zheng, and Michael R. Lyu{ykang,yfzhou,
zbzheng,lyu}@cse.cuhk.edu.hk
Department of Computer Science & Engineering
The Chinese University of Hong KongHong Kong, China
School of Computer ScienceNational University of Defence Technology
Changsha, China
Introduction
Overview of Cloud-based Services
Redeploying Service Instances
Experiment
Obtaining User Experience
Conclusion and Future Work
2CLOUD 2011, Washington DC, USA, July 4 - 9, 2011
Introduction
Cloud Computing Systems–Auto scaling
Dynamic allocation of computing resources
–Elastic load balanceDistributes and balances the incoming traffic
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Introduction
• Typical approach of auto scaling and load balance (Amazon EC2)
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Introduction
Current approaches are not optimized for users–Auto scaling
Do not consider distributions of the end users
–Elastic load balance Do not take the user specifics (e.g.,
user location) into considerations
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Introduction
• Our contribution:–User experience model in cloud –A new service redeployment method
• Two advantages:1)Improve auto scaling techniques
Launch best set of service instances
2)Extend elastic load balance Directs user request to a nearby one.
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Introduction
Overview of Cloud-based Services
Redeploying Service Instances
Experiment
Obtaining User Experience
Conclusion and Future Work
7CLOUD 2011, Washington DC, USA, July 4 - 9, 2011
Framework of Cloud-Based Services
• Data centers• Instances• Users
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Framework of Cloud-Based Services
• Round Trip Time (RTT) can be kept by the cloud provider.
• User experience contains three elements:1. Internet delay between a user and a
cloud data center (This is the most significant part)
2. Delay inside the data center3. Time to process the service request
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Framework of Cloud-Based Services
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Challenges of Hosting the Cloud Services
• Difficult to foresee user experience
• Delay can be measured (should take advantage of it)
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Introduction
Overview of Cloud-based Services
Redeploying Service Instances
Experiment
Obtaining User Experience
Conclusion and Future Work
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Obtaining User Experience
• Measuring Internet delay–RTT can be recorded
• Predict the Internet Delay–Not every data center is visited–Find similar users and predict the
connection.
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Obtaining User Experience
14CLOUD 2011, Washington DC, USA, July 4 - 9, 2011
Introduction
Overview of Cloud-based Services
Redeploying Service Instances
Experiment
Obtaining User Experience
Conclusion and Future Work
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Minimize Average Cost
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Given:Z = the set of data centersC = the set of usersdij = distance between every pair (i,j) ∈ C╳Z
Minimize:
Subject to:𝑍′ ⊂ 𝑍, ∣𝑍′∣ = 𝑘
N
1i'
min ijZjd
CLOUD 2011, Washington DC, USA, July 4 - 9, 2011
Minimize Average Cost
17CLOUD 2011, Washington DC, USA, July 4 - 9, 2011
Minimize Average Cost
• k-median problem • NP-hard• W[2]-hard with k as parameter• W[1]-hard with capacity l as
parameter• In FPT with both as parameter
algorithm: O(f(k,l)no(1)) time
18CLOUD 2011, Washington DC, USA, July 4 - 9, 2011