Agent teams in grid resource brokering and management preliminary considerations
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Agent Teams in Grid Resource Brokering and Management (preliminary considerations). Introduction. The Grid what? why? Local Grid  in a laboratory / company Global Grid  the P2P nightmare nodes appear and disappear node load can change radically no problem for [email protected]

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Agent teams in grid resource brokering and management preliminary considerations
Agent Teams in Grid Resource Brokering and Management (preliminary considerations)


Introduction
Introduction

  • The Grid

    • what?

    • why?

  • Local Grid  in a laboratory / company

  • Global Grid  the P2P nightmare

    • nodes appear and disappear

    • node load can change radically

    • no problem for [email protected]

    • problem when you need

      • QoS

      • SLA


Agents in grids today
Agents in grids today

  • B. Di Martino and O. Rana

    • static and mobile agents in the system (MAGDA)

    • agents visit sites to find resources (services)

      • visits based on exchanges of messages with nodes

      • executes a task or a part of it

    • AGLETS-based / no economic model

  • S. Manvi et. al.

    • attempt at adding economic model

    • single agent moves, negotiates, executes

    • heavily based on mobility


Comments reminders
Comments / reminders

  • Mobility can be costly

    • there is no free lunch

  • Single resource provider  difficult to assure QOS / SLA

  • Economic model is “necessary” (Buyya, 2000)

  • Proposed solution  agent teams

    • “one for all and all for one”


Assumptions
Assumptions

  • Agents work in teams

  • Each team has a team leader (local master – Lmaster)

  • Incoming Workers can join any team based on their criteria of joining

  • Teams can accept workers based on their own criteria of acceptance

  • Each Worker can (if needed) play role of Lmaster

  • Decisions about joining and accepting will utilize contract net protocol and multi-criterial analysis

  • Yellow-page method for matchmaking (provided by the CIC agent)  other approaches possible



Structure of a work team
Structure of a work-team

  • Each team has an Lmaster and a mirror Lmaster (LMirror)

    • if only one agent Lmaster

    • next incoming agent becomes Lmirror

    • LMirror becomes Lmaster if Lmaster fails

  • Lmaster keeps its role as long as it can handle the workload

  • If LMirror “disappears” Lmaster appoints one of slaves to be a mirror

  • Lmaster and LMirror check each other existence in regular intervals

  • Each subsequent agent becomes a worker


Finding team to
Finding team to ...

  • Lagent checks with the CIC who

    • it can join

    • does the work it needs

  • Lagent sends representatives to negotiate

  • Lagent makes decision

    • which team to join

    • which team will do the job

  • Lagent collects data to be used (in the future) in MCDM


Cic architecture 1
CIC architecture:#1

  • task-per-thread paradigm

  • CICAgent picks requests from the JADE-provided message queue and enqueues them into the request queue


Cic architecture 2
CIC architecture #2

  • local CICDbAgents

  • the CIC agent picks requests form the JADE message queue and enqueues them into the internal request queue

  • each CICDbAgent completes one task (request) at a time

  • upon completion, results are sent back to the CICAgent


Cic architecture 3
CIC architecture #3

  • database agents are located on remote machines contributing additional computational power and allowing CICDbAgents to work without stealing resources from the CICAgent


About experiments
About experiments

  • 4 Querying Agents (QA), requesting the CIC to perform SPARQL resource queries

  • Each QA was running concurrently on separate machine, and was sending 2,500 requests and receiving query-results

  • All experimental runs were coordinated by the Test Coordinator Agent (TCA). Before each test, remote JADE agent containers were restarted to provide equal environment conditions

  • 11 AMD Athlon 2500+, 512MB RAM machines running Gentoo Linux and JVM 1.4.2. Computers were interconnected with a 100Mbit LAN


Experimental results different cic architectures
Experimental results – different CIC architectures

  • multi-threaded (pull)

  • multi-agent with local CICDbAgents (push)

  • multi-agent with distributed CICDbAgents (push)

  • 10,000 queries



Final comparisons
Final comparisons

  • Left panel – remote agents with and without CICIA – throughput

  • Right panel – remote agents vs. threads – processing time


Resource ontology

:hasMemory

:a owl:DatatypeProperty;

rdfs:comment "in MB";

rdfs:range xsd:float;

rdfs:domain :Computer.

:hasUserDiskQuota

:a owl:DatatypeProperty;

rdfs:comment "in MB";

rdfs:range xsd:float;

rdfs:domain :Computer.

:LMaster

:a owl:Class;

:hasContactAID

:a owl:ObjectProperty;

rdfs:range xsd:string;

rdfs:domain :LMaster.

:hasUserDiskQuota

:a owl:DatatypeProperty;

rdfs:comment "in MB";

rdfs:range xsd:float;

rdfs:domain :Computer.

Resource ontology

:Computer

:a owl:Class.

:hasCPU

:a owl:ObjectProperty;

rdfs:range :CPU;

rdfs:domain :Computer.

:CPU

:a owl:Class.

:hasCPUFrequency

:a owl:DataProperty;

rdfs:comment "in GHz";

rdfs:range xsd:float;

rdfs:domain :CPU.

:hasCPUType

:a owl:ObjectProperty;

rdfs:range :CPUType;

rdfs:domain :CPU.

:CPUType

:a owl:Class.

Intel :a :CPUType.

AMDAthlon :a :CPUType.


Sample resource description
Sample resource description

:LMaster3

:hasContactAID

"[email protected]:1099/JADE";

:hasWorker :PC2929.

:PC2929

:a :Computer;

:hasCPU

[

a :CPU;

:hasCPUType :Intel;

:hasCPUFrequency "3.7";

] ;

:hasUserDiskQuota "400";

:hasMemory "512".


Sparql query
SPARQL query

PREFIX : <http://www.ibspan.waw.pl/mgrid#>

SELECT ?contact

WHERE

{

?lmaster

:hasContactAID ?contact;

:a :LMaster;

:hasWorker

[

:a :Computer;

:hasCPU

[ a :CPU;

:hasCPUType :Intel;

:hasCPUFrequency ?freq;

];

:hasUserDiskQuota ?quota;

:hasMemory ?mem;

].

FILTER (?freq >= 3.2)

FILTER (?quota >= 350)

FILTER (?mem >= 256)

}


Lmaster cic interactions
LMaster  CIC interactions


End of agents in grid part

End of Agents in Grid Part

QUESTIONS?

Looking for collaborators  papers available at:

http://agentlab.swps.edu.pl


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