A MULTI CLOUD SERVICE CO-DEPLOYMENT MECHANISM Yu Kang, Zibin Zheng, and Michael R. Lyu {ykang,...

A MULTI CLOUD SERVICE CO-

DEPLOYMENT MECHANISM

Yu Kang, Zibin Zheng, and Michael R. Lyu{ykang, zbzheng, lyu}@cse.cuhk.edu.hk

Department of Computer Science & EngineeringThe Chinese University of Hong Kong

Hong Kong, China

Back Ground

Independent Deployment of Single Service

Co-deployment of Multi-service

Experiment and Discussion

Conclusion and Future Work

CLOUD 2012, Hawaii, USA, June 24 - 29, 2012

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BACK GROUND

Rapid growing of cloud-based services

Different cloud-based services may cooperate YouTube & Facebook Google Doc & Gmail Taobao & Alipay

Necessary to deploy together Interactions between services Independent deployment is not enough Critical to make global decisionCLOUD 2012, Hawaii, USA, June 24 - 29, 2012

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MOTIVATION EXAMPLE


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MULTI-SERVICE CO-DEPLOYMENT PROBLEM

Independent services with different target users (may overlap)

Interactions between services Deployed in different data centers even

different clouds for users One company to host and deploy


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Back Ground






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INDEPENDENT DEPLOYMENT OF SINGLE SERVICE


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SINGLE SERVICE DEPLOYMENT

Indicator whether VM j is used

Indicator whether user i is

connected to VM j

Times of user i call service

Distance between user i

and VM j

Minimize total distance for all user requests

Every user i can only connect to

one VM

Can only connect to open VMs

Open at most k VMs


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INDEPENDENT DEPLOYMENT OF SINGLE SERVICE

yj = 1

xij = 1

Every user i can only connect to

one VM

×


×

Open at most k VMs


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Back Ground






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MULTI CLOUD SERVICE CO-DEPLOYMENT

Times of user i call service h

connect at most one VM

Times of interaction between service q

service s for request of user i

Limit number of instances every

serviceboth VMs should be selected

at most one connection

indicator whether interaction between services q and s go

through VM p to r for requests of user i

indicator whether VM j

for service h is used

indicator whether user i would use VM j

for service h


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MULTI CLOUD SERVICE CO-DEPLOYMENT

Open at most kh VMs for service h

xhij = 1

yipqrs = 1

zhj = 1

connect at most one VM


×

First VM is chosen by user i

for service h, next is open


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ITERATIVE SEQUENTIAL CO-DEPLOYMENT ALGORITHM

First Generate Random

Deployment

Sequentially improve the deployment of

each service

Treat requests from other services the same

as these from users

Record the best till now

Disturb and do local search


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Back Ground






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OBTAIN THE DATASET

1. Conduct the experiment on 597 planetlab instances

2. Ping 2,213 web-services and all other planetlab peers in random order

3. Delete records of several instances and web-services to obtain two non-negative matrices, finally 307 * 1,881 remains

4. Mapping: Planetlab nodes -> available data centers Web-services -> users


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DATASET STATISTICS


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EXPERIMENT SETTING

Above 106 decision variables Use the tool Ilog CPLEX to solve the MIP

problems Randomly generate user log and calling

sequences as: User id -> service si1 -> service si2 -> … ->

service sim


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DEFAULT EXPERIMENT SETTING

1881 users 10 services Deploy10 service VMs among a candidate set

in 100 data centers A user of service would have 5 request logs𝑠 One request of a service would involve on

average 5 requests of other services


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EXPERIMENT (ALGORITHM SPECIFICS)

Convergence of Iterative Sequential Procedure

Number of Disturbs


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EXPERIMENT (NUMBER OF SERVICES)


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EXPERIMENT (NUMBER OF SERVICE VMS)

Size of Candidate Set of Service VMs

Number of Service VMs to Deploy


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EXPERIMENT (SERVICES LOGS)

Number of Service Users

Average Call Length of Service


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EXPERIMENT (SERVICES LOGS)

Number of Logs


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Back Ground






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CONCLUSION AND FUTURE WORK

Conclusion Model the latency-aware cloud-based multiple

services co-deployment problem Give a new iterative algorithm to solve the

problem Conduct experiments on real world data set

Limitation of model No limitation on requests to one service VM Computation time is not constant in real world Possible solution: add a term of computational

time in the model


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Q & A


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A MULTI CLOUD SERVICE CO-DEPLOYMENT MECHANISM Yu Kang, Zibin Zheng, and Michael R. Lyu {ykang,...

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