SwiNG Grid Day, Bern, Nov. 26th, 2009

1. SwiNG Grid Day, Bern, Nov. 26th, 2009 SmartGRIDOngoing research work in Univ. Fribourg and Univ. Applied Sciences of Western Switzerland (HES-SO) Ye HUANG PhD Student, ye.huang@unifr.ch http://diuf.unifr.ch/people/huangy Pervasive Artificial Intelligence Group, Dept of Informatics, University of Fribourg, Switzerland Grid Group, Dept of Information and Communication Technologies, HES-SO (FR), Switzerland

2. Outline Introduction Smart Resource Management Layer Smart Signaling Layer Future Work

3. SmartGRID Overview Swarm Agent-Based Scheduling framework for Dynamic, Reactive, Interoperable Grid Computing Developed in: University of Fribourg, Switzerland http://diuf.unifr.ch/pai University of Applied Sciences of Western Switzerland (HES-SO) http://gridgroup.hefr.ch Two Phd students: One is working on the grid scheduling (Ye) The other is working on swarm agent-based resource discovery (Amos)

4. SmartGRID Motivation Filling the gap between Grid applications and resources • How to achieve: • Using stable grid applications • Large scale of resources • Mixed policies • Unstable, unreliable network ?

5. SmartGRID layered architecture Loosely coupled layered architecture. Two layers and one internal interface. Smart Resource Management Layer Data Warehouse Interface Smart Signaling Layer

6. Smart Resource Management Layer (SRML) Nowadays Grids Grid nodes are well controlled by the local facilities Job sharing is generally limited within each grid node Our Vision Enabling job sharing between distributed nodes is one more step towards a universal computing infrastructure Our Goal Serving the grid as a whole, not for individual nodes Without centralized control

7. SRML (2) – MaGate Scheduler • SRML is comprised by a set of fully decentralized MaGate schedulers (original and implemented) Grid Applications • Self-management, matchmaking, behavior logging • Job submission and analysis • Agreement based negotiation for job sharing and other events • Job allocation on local resources • Adoption mechanism for external services (SSL, etc.) Remote MaGate LRM

8. SRML (3) - Interoperable scheduling Reference experiment to prove the idea of Interoperable scheduling Local suited and Local unsuited jobs are submitted to each node Objective: to increase the “Rate of successfully executed Jobs from the entire grid Community (RJC)” First results Different policies applied while adopting the SRML and SSL Different results can be obtained with same policies on grids with different scope A general guideline should give the principle of intelligent scheduling (Community-Aware Scheduling Protocol, CASP)

9. SRML Achievements We developed: A fully[1, 2] decentralized interoperable MaGate scheduler; Integrated SmartGRID prototype[3] to evaluate the idea of scheduler coordination across different nodes; Some pilot works [4, 5] leading to exploit a more proactive collaboration mechanism; A proposal of the Community-Aware Scheduling Protocol(CASP)[6] to integrate knowledge from previous work. More Info & Download: http://gridgroup.hefr.ch http://diuf.unifr.ch/people/huangy

10. Smart Signaling Layer (SSL) Done by Amos BROCO (amos.brocco@unifr.ch) Goals Connect nodes together Overlay management middleware / algorithm Provide information to the upper layer Information provisioning / monitoring middleware We developed A middleware for the development and deployment of ant algorithms A fully distributed algorithm to maintain an optimized P2P overlay An efficient resource discovery protocol exploiting local caches More Info & Download: http://diuf.unifr.ch/pai/people/broccoa

11. Future Work SRML/SSL Integration Improved Datawarehouse based internal interface Smart Signaling Layer Fine-tuning of ant algorithms (improve efficiency) Smart Resource Management Layer Refined and improved MaGate scheduler Implementation of the Community-Aware Scheduling Protocol (CASP) Integration upon real grid workload trace archive

12. Thank you! Questions?