Swarm Based Distributed Search in the AMIGOS Environment

29 Pages·2011·0.72 MB·English

Otto Wittner
Poul E. Heegaard
Bjarne E. Helvik
Swarm Based Distributed Search in
the AMIGOS Environment
AVANTEL Technical Report
DEPARTMENTOFTELEMATICS,NTNU
ISSN1503-4097

NTNU
NorwegianUniversityof DepartmentofTelematics
ScienceandTechnology
AVANTELTECHNICALREPORT
1/2002
ISSN-no:
1503-4097
TITLE DATE
Swarm Based Distributed Search in the AMIGOS 2002-12-09
Environment
-
NO.OFPAGES/APPENDICES
23(excl.titleandpreface)
AUTHOR(S)
Otto Wittner,PoulE.HeegaardandBjarneEHelvik
ABSTRACT
Futureusercontrolleddevelopment oftelecommunicationservicescombinedwithpowerfulterminal
equipment resultsinmanyheterogeneousservicesrunninginapeer-to-peerexecutionenvironment.In
suchasystemlocatingadesiredserviceischallenging.Inthispaperaswarmbasedoptimization
algorithmispresentedcapableoffindingpathsofresourcesinacomplexnetworkenvironment.The
algorithmisfullydistributedandmaybeimplementedusingsimpleant-likemobileagents.Onthe
contraryto existinglocalizationmechanismsforpeer-to-peersystemsthealgorithmconsidersall
accessedresourcesbetween(andincluding)theclient sideandserversidewhenaresourcepathis
evaluated.Scalabilityisachievedbyenablingagentsto cooperateduringsearchwhentheyhave
overlappingsearchprofiles.Resultsfromsimulationsarepromising.Theexpectedcooperative
behaviorisshownto bepresent,i.e.aset ofnearoptimalresourcepathsconformingto aset of
different but overlappingsearchprofilesmaybefoundwithout performancedegradation.
KEYWORDS
SwarmIntelligence
DistributedSearch
MulticriteriaCombinatorialOptimization
Peer-to-Peer
Amigos

Preface
Thistechnicalreport describesresultsfromresearchactivitieswithintheAVANTELproject. Thefirst
authorofthisreport,Otto Wittner,wasengagedasresearcherfortheproject foraperiodof8months,
ref.contract titled“Sverm-intelligensforoptimalkonfigurasjonavdistribuerteteletjenester”signed
byItem,NTNU2001-01-07andTelenor2001-01-09.Adescriptionofthemajorresultsfromthe
engagement followsthispreface.Thedescriptionispresentedintheformat ofapapersuitablefor
publishinginaconferenceorajournal.OthercontributionsintheAVANTELproject madebythefirst
authorareasfollows:
• Development ofexampleuserscenariosforAMIGOS(seeAMIGOSdocument repository)
• Development ofexampleprofiledescriptionsinXML.Profilesuggestionsforusers,services
andterminalsweredeveloped(seeAMIGOSdocument repository).
• Participationinmisc.meetinganddiscussionswherebasicconceptsandprincipleofthe
AMIGOSserviceweretreated.
Themajorresults,i.e.thepaperfollowingthispreface,isintendedto besubmittedto asuitable
conferencebeforeendofJanuary2003.

Swarm Based Distributed Search in the AMIGOS
Environment
OttoWittner,PoulE.HeegaardandBjarneE.Helvik
December9,2002
Abstract
Futureusercontrolleddevelopmentoftelecommunicationservicescombinedwithpowerfulterminal
equipmentresultsinmanyheterogenousservicesrunninginapeer-to-peerexecutionenvironment. Lo-
catingadesiredserviceinsuchanenvironmentischallenging.Inthispaperaswarmbasedoptimization
algorithmispresentedcapableoffindingpathsofresourcesinacomplexnetworkenvironment.Thealgo-
rithmisfullydistributedandmaybeimplementedusingsimpleant-likemobileagents.Onthecontraryto
existinglocalizationmechanismsforpeer-to-peersystemsthealgorithmconsidersallaccessedresources
between(andincluding)theclientsideandserversidewhenaresourcepathisevaluated. Scalability
isachievedbyenablingagentstocooperateduringsearchwhentheyhaveoverlappingsearchprofiles.
Resultsfromsimulationsarepromising.Theexpectedcooperativebehaviorisshowntobepresent,i.e.a
setofnearoptimalresourcepathsconformingtoasetofdifferentbutoverlappingsearchprofilesmaybe
foundwithoutperformancedegradation.
Keywords Telecommunications,distributedoptimization,resourcepaths,ant-likeagents,peer-to-peer.
1 Introduction
Asthenumberofusercategoriesandterminalequipmenttypesareincreasingsteadily,telecommunication
operatorshaverecognizedapotentialforarangeofnewtelecommunicationservices.1Oneservicecategory,
whichhasquicklygainpopularity,ispeer-to-peersystemswhereusersdevelopandprovideservicestoother
userswithlittleornocentralizedmanagement. Usercontrolleddevelopmentofservicesquicklyproduce
a large rangeof services where both the number of services and service categoriesare highly dynamic.
Userswith powerfulterminalstaketheroleas serviceproviders,whileotherusersmay choseto initiate
their services on dedicated servers in the network. The combinationof a dynamicset of services and a
peer-to-peerenvironmentforserviceexecutionmakeslocatingarelevantservicechallenging.
Manydirectorysystemsforpeer-to-peerenvironmentshavebeendevelopedduringthelastdecade[3].
Commonforthesesystemsarelimitedfunctionalityforspecifyingqualityofservice(QoS)parametersin
servicelookuprequests.Inmostcasesonlysomeidentityoftheservicerequestedcanbespecifiedandvery
few(orno)parametersindicatingminimumrequirementstoresourcesneededtoaccesstheservice. The
resultisoftenanoveralluninterestingserviceoffer. Forinstancewhenrequestingamultimediastream,
access to a high quality versionof the stream may beofferedbut dueto lack of network bandwidththe
streambecomesuninteresting.
Severalbio-inspiredalgorithmhaveshownpromisingresultswhenappliedtotelecommunicationrelated
problems. A class of bio-inspired algorithms known as swarm intelligence systems [4] are potentially
robust and may scaled well due the their use of distributed autonomous components. In this paper we
presentaswarmintelligencebasedalgorithmwhichenablesimplementationofimprovedQoScontrolled
servicelookupandaccess. Relatedworkonbio-inspiredmethodsforservicecomponentmanagementcan
befoundin [5,6,7, 8,9]. Our algorithmexpectsa servicelookuprequestto containa profilewhichin
additionto indicateconstraintsandpreferencesfor theservicetypebeingrequested,indicateconstraints
andpreferencesforotherresourcesnecessarytoaccesstheservice. Thealgorithmseekstofindapathof
resourcesfromaclientterminaltoaserviceprovidingserversuchthatallresourcesinthepathconforms
(aswellaspossible)withtheconstraintsandpreferencesoftherequestprofilespecifiedbytheuser.
1Toenablerapidrealizationofnewheterogenousservices,Telenor,EricssonandNTNUhavechosentomovefromthetraditional
callcentricapproachestoamoreservicecentricapproachaswellasinvolvingusersanduserinnovationintheservicedevelopment
process[1].Peer-to-peerisadoptedasapotentialenvironmentfordistributedserviceexecution. Theoverallinitiativehasresultedin
theAVANTELproject[2].ThispaperpresentsresultsformresearchsponsoredbytheAVANTELproject.
1
Ouralgorithmisbasedontheconceptofswarmintelligencewhichinheritsbehavioraspectsfromsocial
insectsandanimals. Swarmintelligencehassuccessfullybeappliedtoarangeofoptimizationproblems
[10],sometypicalinthedomainoftelecommunications[11,12,13,14]. Swarmintelligencesystemsuse
a high number of simple autonomousagents to search for problem solutions. Groups of (or all) agents
cooperateby sharing experiencesgained duringsearch. Informationis shared by asynchronousindirect
communication,i.e.messages(pheromones)leftinshareddatabasesinthesearchenvironment.
Ouralgorithmisbasedonworkpreviouslypublishedin[15,16,17]. Scalabilityintermsofnumber
of parallel tasks handledby agentshas so far only been addressed to a limited extent. In this paper we
introducesmechanismstomanagelargescaleuseofouralgorithm.Ontheassumptionthatservicerequest
profilesinmanycaseswillbeoverlapping,i.e. containsimilarconstraintsandpreferences,weletagents
shareinformationabouttheoverlappingpartsoftheprofiles. Assumingalimitedtotalnumberofpossible
constraints and preferencesthe new sharing strategy reduces the total amount of storage space required
forpheromonestoamanageablelevel,andincreasesthesearchefficiency. Tofindadesirablerankingof
solutionscostfunctionswithimplicitconstraintsaredevelopedwhichoutputaqualitymeasureofhowwell
apathofresourcesconformwithaprofilerequest.
Thereminderofthispaperhasfivesection. Section2presentsbackgroundinformationandintroduces
thesearchdomainwithrelatedterminologyandformalisms.Section3introducesthebehaviorfoundations
for the agents, describes the cost functions which evaluates criteria during the search process, presents
reformulationsandadditionsrequiredtorealizeextendedpheromonesharingbetweenagents,anddescribes
thenewagentalgorithm.Section4describesourexperimentalsetupconsistingoffivesimulationscenarios,
andreportsanddiscusssimulationresults.FinallySection6summarizeandindicatefuturework.
2 Resource Paths and Profiles
Inthispaperweviewallcomponentsinanetworkenvironmentasresourceswithindividualprofiles,i.e.
servicecomponents(createdbyusersoroperators)aswellaslinksandnetworknodesfornetworktransport
areviewasresourceswitharelatedprofile.Anorderedsequenceofresourcesaredenotedaresourcepath.
2.1 Motivation
The motivation for adopting a resource view is the heterogeneity of the expected network environment
whereoneoftheAVANTELproject’srootservices,AMIGOS[1],isrunning.
2.1.1 AMIGOS
AdvancedMultimediaInGroupOrganizedServices(AMIGOS)providesthebasicfunctionalityrequired
for users to manage and visit a Meeting Place (MP). A meeting place is a user (or operator)composed
andconfiguredtelecommunicationserviceprovidingaconnectionpointbetweenaspecificsetofusers. A
meetingplacemayalsoactasarepositoryformultimediaobjectstobesharedbetweentheusersvisitingthe
meetingplace. TechnicallyameetingplaceisasoftwareprocessrunningonsomeserverintheAMIGOS
networkenvironment.
2.1.2 TheAMIGOSEnvironment
Figure 1 illustrates the expected heterogeneity of the environment where the AMIGOS service will be
running. Softwareprocesses provideMP service resourceswhich again providingaccess to multimedia
objects. Amixofterminalscontrolledbydifferentusersandamixofserversownbydifferentoperators
provide processing power. And finally a range of transmission technologies provide transmission links
interconnectingterminalsandservers.
BothterminalsandserversshowninFigure1aretypicallyconnected(bydifferenttransmissiontech-
nologies)toseveralotherterminalsand/orservers,i.e. networknodesintheAMIGOSenvironmentoften
haveaconnectiondegreegreaterthanone.Adegreegreaterthanoneenablesanodetoactasarouterora
relayinadditiontoitsothercapabilities.
Allterminals,usersandservicesintheAMIGOSenvironmentareexpectedtohaveindividualprofiles
whichdescribetheircapabilitiesandlimitationsintheformofQoSparameters.
Figure 1 does not illustrate the expected scale of the AMIGOS environment. The following rough
estimationsindicateamorerealisticscaleconsideringpotentialusersinNorwayonly:
2
n
o
siti AY MP
o L
P R
A MPEG lib
GSM P
UMTS
POTS
ISDN
PS LAN P
G S
I
Bluetooth LAN MIGOS MMMPPP Chat ADSL
Bluetooth A
Internet
WLAN LAN
Router
MP MP
Maps MP3 share
Figure1:AexamplenetworkenvironmentwhereAMIGOSisexpectedtorun.
(cid:0) Totalnumberofusers: (cid:1)(cid:3)(cid:2)(cid:5)(cid:4)(cid:7)(cid:6)(cid:9)(cid:8)(cid:11)(cid:10) (i.e.inthesameorderasthenumberofGSMsubscribers)
(cid:0) Numberofsignificantlydifferentterminal/server/routertypes:(cid:1)(cid:3)(cid:12)(cid:13)(cid:4)(cid:14)(cid:6)(cid:15)(cid:8)(cid:11)(cid:16)
(cid:0) Numberofnetworktransportservices:(cid:1)(cid:18)(cid:17)(cid:19)(cid:4)(cid:14)(cid:6)(cid:15)(cid:8)(cid:11)(cid:20)
In the following sub-sections we establish formal terms for describing componentsin the AMIGOS
environment.
2.2 ResourcePaths
WeviewtheAMIGOSenvironmentasacompositionoftelecommunicationresources. Aresourceisde-
noted (cid:21) . In a real instance of the environment,resources we consider will be only those which can be
accessed,configuredandcontrolled(seeSection5fordetailsonimplementationissues).
Whenusersareactiveinthenetworkenvironmenttheywillaccessasetofresources. Wedenotesuch
anorderedsetofresourcesaresourcepath
(cid:22)(cid:24)(cid:23)(cid:14)(cid:25) (cid:21)(cid:27)(cid:26)(cid:29)(cid:28)(cid:30)(cid:21)(cid:13)(cid:31)(cid:15)(cid:28)! ! ! "(cid:28)#(cid:21)%$%&(’ (cid:20) (cid:28)#(cid:21))$(cid:27)&(cid:11)’*(cid:31)(cid:15)+
(cid:1)(cid:3),
where isthenumberofresourcesinthepath.
Wehavechosentodividetheindividualresourcesfoundinapathintothreecategories:Client,Transport
andPeripheralresources.
Aclientresources, thefirst resource(cid:21))(cid:26).-0/21 in apath, enablesa userto access otherresourcesin the
environmentby providinga suitable interface.Typicalclient resourcesare terminalsrunningclient
applications(e.g.abrowser)./ 1 isthesetofallclientresources.
Atransportresource, anintermediateresource(cid:21)(cid:13)3)-4/ (cid:12) where5 (cid:23) (cid:6)76!6869(cid:1) ,2:<; ,providesatransportser-
viceofsomequality.Typicaltransportresourcesareinternalandexternaltransmissionlinks(clouds
(cid:12)
inFigure1)andnetworknodesactingasroutersorswitches. / isthesetofalltransportresources.
Aperipheralresource thelastresource(cid:21)(cid:13)$%&=’*(cid:31)>-4/@? inapath,providessomevalueaddedservice.Users
willnormallydesiretoaccessaspecifictypeofperipheralresource.Typicalperipheralresourcesare
AMIGOSmeetingplaces,multimedialibraries,processingpower,multimediasensors,positioning
sensorsetc. />? isthesetofallperipheralresources.
3
In our view access to minimum two resource will be required for any user activity, at least one client
resourceandoneperipheralresource.Thus
(cid:0)(cid:2)(cid:1)(cid:4)(cid:3)(cid:6)(cid:5)(cid:8)(cid:7)(cid:10)(cid:9)(cid:12)(cid:11)(cid:14)(cid:13)(cid:16)(cid:15)(cid:17)(cid:9)(cid:19)(cid:18)(cid:21)(cid:20)(cid:23)(cid:22)(cid:25)(cid:24)(cid:26)(cid:20)(cid:28)(cid:27)(cid:30)(cid:29) where(cid:20)(cid:31)(cid:22)! #"!$ and(cid:20)(cid:28)(cid:27)% #"’&
Ingeneralaresourcepathwillonlycontainasingleclientandasingleperipheralresource,butmaycontain
asequenceoftransportresources.Thus(cid:15) (cid:17)( where
()(cid:9)*(cid:18)(cid:25)(cid:18)+(cid:20)(cid:23)(cid:22),(cid:24)-(cid:20).(cid:27)/(cid:24)10(cid:21)0+02(cid:24)(cid:26)(cid:20).3(cid:23)46527,(cid:24)(cid:26)(cid:20)(cid:31)3(cid:23)4658(cid:27)+(cid:29):9.(cid:20)(cid:23)(cid:22)! (cid:6)"!$(cid:21)(cid:24);(cid:20)(cid:28)(cid:27)=<<<3(cid:31)465>7? #"%@A(cid:24);(cid:20)(cid:31)3(cid:23)4B52(cid:27)% (cid:6)"C&D(cid:29)
isthesetofallresourcepaths.(cid:5) (cid:7)E (cid:18)/(cid:11) (cid:24)DFD(cid:24);GH(cid:24)1I1I(cid:21)I(cid:29) isthetotalnumberofresourcesinapath.
Acommonlimitationoftoday’slookupservicesforpeer-to-peersystemsisthatthecompleteresource
pathrequiredtoaccessaperipheralresourceisnottakenintoaccountduringsearch. Informaltermsthis
meansignoringthe sub-path (cid:18) (cid:20)(cid:31)(cid:22)6(cid:24)(cid:26)(cid:20)(cid:28)(cid:27)+(cid:24)1010108(cid:24)-(cid:20)(cid:31)3(cid:23)4(cid:25)5 7 (cid:29) or parts of it. Our algorithmin this paper takes into
accountthecompletepathofresources,i.e. (cid:18) (cid:20).(cid:22),(cid:24)-(cid:20)(cid:28)(cid:27)(cid:30)(cid:24)+0(cid:21)0102(cid:24)(cid:26)(cid:20)(cid:31)3(cid:31)4B5 7 (cid:24)(cid:26)(cid:20).3(cid:23)4652(cid:27)(cid:30)(cid:29) .
2.3 ProfilesandQoSObjectives
IntheAMIGOSenvironment,users, terminalsandservicesareexpectedtohaveindividualprofilescon-
MON(cid:25)P
tainingQoSparameters. Whenauser J initiatesarequestsK foraservice,auserrequestprofile L J;Q is
generated. Foraresource(cid:20)(cid:28)R intheenvironmentwedenote MHL P(cid:20)(cid:31)R Q theprofileoftheresource. Thusthere
aretoclassesofprofiles:
S ProfilesoftheuserrequestclasscontainQoSparametersspecifyingconstraintsandpreferencesin
therequest,i.e.QoSobjectives.
S Profiles of the resource class contain QoS parameters specifying limitations and capabilities of a
resource(cid:20) R .
2.3.1 UserRequestProfile
Ingeneral,auserrequestprofilemayincludealargesetofQoSparameters. Tomaintainscalability,we
have defined a finite and ordered set T of QoS objectives from which a specific request profile may be
constructed.EachelementU+V inT ,whereW (cid:9)YX (cid:24)+IZIZI(cid:4)(cid:24)+[T [,isaspecificQoSrequirement,e.g.
S U1\ (cid:24) I(cid:21)I1I (cid:24) UO] maybearangeofmaximumendtoenddelaysof(cid:18)(cid:30)^ \ (cid:24) I(cid:21)I+I (cid:24) ^ ] (cid:29) seconds,
S U N (cid:24)1I1I1I(cid:21)(cid:24) U1_ maybearangeofminimumbandwidthof(cid:18)(cid:30)‘ N (cid:24)+I(cid:21)I1I(cid:21)(cid:24) ‘ _ (cid:29) bits/s,
S U1a (cid:24)1I1I(cid:21)I1(cid:24) U(cid:21)b maybespecifictypesofresources(cid:18)(cid:30)c a (cid:24)(cid:21)I1I1I1(cid:24) c b (cid:29) ,e.g.typesofperipheralequipment.
AuserrequestprofilemaynowbeexpressedasMLN PJ;Q (cid:9)d(cid:18)(cid:30)e (cid:27)/(cid:24) I(cid:21)I1I (cid:24) egfhif(cid:29) .Inthisinvestigation,abinaryuser
requestprofileisused,i.e.,
e (cid:9)kj Xl9 whenrequirementW shouldbemet
V m 9 otherwise
howeverin general(Section 3.3)arbitrary values e V(cid:8)n m may be used to balancetheimportanceof the
variousrequirements.
InthecaseswherewehavearangeofQoSparametersofthesamekindtochoosefrom,e.g.thedelays
andbandwidthsabove,onlyonevalueintherangeshouldbeset.
2.3.2 ResourceProfile
When used, a resource (cid:20) R may introduce QoS impairments with respect to the QoS requirements of a
userrequestK(cid:30)\ . Theseimpairmentsmayforinstancebeexcessivedelays,limitedbandwidth,processing
or storage capacity, or lack of required peripheralequipment, services or information. Impairments are
denotedtheloss o V P(cid:20) R Q introducedbyresource(cid:20) R withrespecttoaQoSparameterW intheuserrequest
profile.Hence,theresourceprofileMHL P(cid:20) R Q associatedwithresource^ isrepresentedasalossvector
M;P(cid:20) R P(cid:20) R (cid:9)d(cid:18) (cid:27) P(cid:20) R (cid:24) 7 P(cid:20) R (cid:24) I(cid:21)I+I (cid:24) fhifP(cid:20) R (cid:29)
L QqproL Q o Q o Q o Q
4