Service-oriented Resource Broker for QoS-Guaranteed in Grid Computing System Yichao Yang, Jin Wu,...
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Service-oriented Resource Broker for QoS-Guaranteed in Grid Computing System
Yichao Yang, Jin Wu, Lei Lang, Yanbo Zhou and Zhili Sun
Centre for communication systems researchUniversity of SurreyGuildford, United Kingdom
Grid Computing What is Grid Computing?
A type of parallel and distributed system that enables the sharing, selection, and aggregation of geographically distributed resources depending on their availability, capability, cost, and user Quality of Service requirements for solving large-scale problems/applications.
Challenges of Grid Computing To deliver quality of service:
• The grid system performance efficiency depend on the how good QoS is provided for different user’s different requirement based on the factor of functions, cost, deadline, budget etc.
• Enhance real-time & QoS capability in grid middleware to meet the demand of scientific applications.
Coordinate resources:• It is necessary to have a resource scheduling that provides
matching users’ need and resource availability.
Problems of Grid QoS
How to provide guaranteed bulk data transmission for user’s QoS requirement.
The existing grid computing solution does not consider networks as a key resource to provide efficient services for grid apps.
Grid QoS Problem Solution
Propose an end-to-end QoS framework to satisfy grid user’s QoS requirements.
Introduce a service-oriented resource broker which can provide guaranteed QoS for grid application over large-scale grid network and optimal resource selection for resource sharing.
Implement cost-based resource selection algorithm which can effectively utilize potential combined resources and achieve high user request success rate in dynamic service-oriented Grid.
End-to-End QoS Framework
Data Resource
Data Resource
Trans Service
Data Service
Data Service
Trans Service
Trans Service
Broker
End-to-End QoS
Grid Message Flow
Data Flow
User User submit application request
Display all resources Grid
User access resources data
Broker makes resource reservation
Broker architecture
Grid information
service
Resource Requirement Interpreter
Resource discovering unit
User resource requirements
Resource coupler
Resource reservation unit
Network resource index
update
update
List of resource combination
Resource Gatekeeper A
...
Reservation
Reservation confirmation
Service-oriented resource broker
Abstract resourcerepresentation
Resource availability info
Index services
Resource combination ranker
Topology discoverer
Resource priority list
Resouces
discovering
register
Internal call
External call
Existing component
Internal unit
Existing machanism
Discovery interface
Reservation interface
Simulation Network Topology
Resource 3
Resource 2
Resource 1
Broker
User
Grid Information
Service (GIS)
R1
R2
R3
R4
R51Mbps
1Mbps
Conclusion End-to-End QoS framework has
been defined Fully utilize combined resource to support user’s
requirements Implement cost-based resource selection
algorithm in Grid Resource Broker Discussion of Simulation Result
The higher number of the task, the more processing time saved.
The broker reservation scheduling has reduced the total processing time by 15-30% and reduced the average cost of processing by 4% when compared to non broker reservation scheduling.