1. GSAF: A Grid-based Services Transfer Framework Chunyan Miao, Wang Wei, Zhiqi Shen, Tan Tin Wee

2. Motivation Grid provides an integrated computing environment, facilitating maintenance and control of information and other kinds of resources e.g. services. However, –Existing services are still tied with definite containers. –When new services are deployed, they come to function only after container is restarted.

3. Objective Execute services dynamically to break the tight coupling between services and computers

4. Grid Resource Allocation Grid resource allocation has attracted a lot of attention in recent years: –Globus focuses on providing uniform and scalable mechanisms for naming and locating computational and communication resources on remote systems. –GRASP [1] supports some features for user-friendly resource allocation such as resource brokering, scheduling, monitoring, and so forth. –Nassif et al. [2] presented a Multi-Agent System that chooses the best place to run a grid job by making use of negotiation.

5. GSAF Existing work mainly focuses on how to find, locate, select and schedule existing static services. GSAF (A Grid-based Services Allocation Framework) is proposed to: –dynamically extend and adjust computing ability of nodes in grid systems. –balance the total weight by fully utilizing free or idle computing resources. –and provide a form of resource management to improve the flexibility of Systems

6. GSAF—Resource View Service components viewed as explicitly manageable resources GSAF partitions resources into: –Service Components Repository (SCR): logical pool gathering all the available service components –Computing Nodes Repository (CNR): hardware pool gathering available computers –Data Sources Repository (DSR): logical pool gathering all the data related to service components.

7. GSAF—R-language R-language: a resource-oriented workflow description language Three logical elements –Action: a definite resource processing behavior –Scenario: a finite series of actions –Task: scenario which has definite and meaningful purpose according to user request. A task is basically a running script

8. GSAF—R-language Example The first example defines an action to transfer a DBSCAN [9] service component in SCR from local computer to remote computer named OEM-MICRO. The second example selects computing node named DMGROUP in CNR for service executing. The third example defines the action to find the address of a certain data source named DBSCANinput in DSR.

9. GSAF Architecture Computers are categorized into two different kinds of nodes: –central nodes: responsible for central management and scheduling such as resource managing and task scheduling –and computing nodes: contribute computing ability to run services, i.e. the resources in CNR Each node is controlled by an agent. The whole system is thus a multi-agent system (MAS).

10. GSAF Architecture (cont’d) Architecture of Central Node Agent

11. GSAF Architecture (cont’d) Architecture of Computing Node Agent

12. GSAF Architecture (cont’d)

13. GSAF Strategies Use service cache to deal with the service components swapping: a distinct feature of GSAF. –LRU (Least Recently Used): The least recently used service component in buffer is recorded. If replacement is needed, swat it out. –NRU (Not Recently Used): The service component which hasn't been used in a certain period is recorded. If replacement is needed, swat it out. –FIFO (First-In First-Out): The service components are organized in a queue according to the order of arrival. If replacement is needed, swat out the service at the head of queue.

14. GSAF—Strategies (cont’d) Although the best solution is to select the most powerful computer, it may not be practical in real use because of the changings on-the-fly, for example the CPU usage. A heuristic selection strategy is used in GSAF, namely, weighted ranking.

15. Prototype An application of GSAF is implemented in the field of bio data mining system. –Use Globus Toolkit 3.2 to provide grid environment. –The modules of central node and computing node are implemented as grid services in Java supported by Globus grid service container.

16. Conclusion GSAF is proposed to dynamically allocate services –Swap and execute services dynamically to break the tight coupling between services and computers. –All the resources are categorized and managed in corresponding repository. –Dynamic binding among different kinds of resources provides a flexible pattern to execute services On going and Future work: –Applications of GSAF to Bio Applications. –Mobile Service Flow on WWW –Trusted Service Grid

17. Thank You!

18. References [1] OGSA(Open Grid Services Architecture) Documents:http://www.globus.org/ogsa [2] Globus: Research in Resource Management, http://www.globus.org/research/ http://www.globus.org/research/ [3] L. Nassif, J. M. Nogueira, M. Ahmed, R. Impey, A. Karmouch. Agent-based Negotiation for Resource Allocation in Grid. Workshop on Computational Grids and Applications, 2005 [4] R. Parra-Hernandez, D. Vanderster and N. J. Dimopoulos. Resource Management and Knapsack Formulations on the Grid. IEEE/ACM International Workshop on Grid Computing (GRID'04), 2004