SmartGRIDOngoing research work in Univ. Fribourg and Univ. Applied Sciences of

Western Switzerland (HES-SO)

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

Ye HUANG

PhD Student, ye.huang@unifr.ch

http://diuf.unifr.ch/people/huangyPervasive Artificial Intelligence Group, Dept of Informatics, University of Fribourg, Switzerland

Grid Group, Dept of Information and Communication Technologies, HES-SO (FR), Switzerland

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Outline

Introduction Smart Resource Management Layer Smart Signaling Layer Future Work

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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)

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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

?

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SmartGRID layered architecture

Loosely coupled layered architecture. Two layers and one internal interface.

Smart Resource Management Layer

Data Warehouse Interface

Smart Signaling Layer

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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

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SRML (2) – MaGate Scheduler

SRML is comprised by a set of fully decentralized MaGate schedulers (original and implemented)

Remote MaGate

LRM

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.)

Grid Applications

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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)

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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

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Smart Signaling Layer (SSL)

Done by Amos BROCO (amos.brocco@unifr.ch) Goals

Connect nodes togetherOverlay management middleware / algorithm

Provide information to the upper layerInformation 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

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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

Thank you!

Questions?