Case Study on Web Service Composition Based on Multi-Agent System

Transcription

1 900 JOURNAL OF SOFTWARE, VOL. 8, NO. 4, APRIL 2013 Case Sudy on Web Servce Composon Based on Mul-Agen Sysem Shanlang Pan Deparmen of Compuer Scence and Technology, Nngbo Unversy, Chna QnJao Mao Deparmen of Compuer Scence and Technology, X an Jaoong Unversy, Chna maoqnjao@su.xju.edu.cn Absrac Rapd developmen of he Inerne and ncreasng number of avalable Web servces has generaed a need for ools and envronmens faclang auomaed composon of aomc Web servces no more complex Web processes. However,reasonng opmzaon and ulzaon n such AI relaed soluons s sll an open problem.in hs paper, we proposed a novel mul-agen based semanc web servce composon model(swscpa whch explos he relaonshps among dfferen servce consumers and provders, ogeher wh he correspondng opmzaon approach o srenghen he effecveness of Web servce composon. We argue ha agens and web servces are dsnc. In our work, agens provde a dsncve addonal capably n medang user goals o deermne servce nvocaons. Through he model, an opmzaon mehod was proposed based on he subsue relaonshp and he dependency relaonshp. The case sudy and expermenal analyss demonsraes he capably of he proposed approach. Index Terms Web Servce, Servce Composon,Agen I. INTRODUCTION As an archecural syle for buldng sofware applcaons usng servce componens avalable n a nework, servces-orened archecure(soa has made a major mpac on dsrbued compung research. SOA s usually realzed hrough Web servces, whch s defned as he self-conaned, self-descrbng, modular applcaon ha provdes busness funconaly across he Web. Accordngly, he ably o effcenly and effecvely negrae an approprae se of servce componens o realze a new servce ha fulflls he users reques s he essenal feaure of Web servces. In he pas decade, subsanal research effor has been devoed o auomaed Web servces composon sysems. Mos exsng research work falls no he caegores of cross-enerprse workflow composon or AI plannng. In hs conex plannng has proved o be one of he mos promsng echnques for he auomaed composon of Web servces. Several works n plannng have addressed dfferen aspecs of hs problem, see, e.g., [1,2]. In hese works, auomaed composon s descrbed as a plannng problem: servces ha are avalable and publshed on he Web, he componen servces, are used o consruc he plannng doman, composon requremens can be formalzed as plannng goals, and plannng algorhms can be used o generae composed servces. These works share he concepon of servces as saeless enes, whch enac smple query response proocols. An even more dffcul challenge for plannng s he auomaed composon of Web servces a he process level, he composon of componen servces ha conss of saeful busness processes, capable o esablsh complex mul-phase neracons wh her parners. In he large majory of real cases, servces canno be consdered smply as aomc componens, whch, gven some npus, reurn some oupus. On he conrary, n mos applcaon domans, hey need o be represened as saeful processes ha realze neracon proocols whch may nvolve dfferen sequenal, condonal, and erave seps. For nsance, we canno n general nerac wh a flgh bookng servce n an aomc sep. The servce may requre a sequence of dfferen operaons ncludng an auhencaon, a submsson of a specfc reques for a flgh, he possbly o subm eravely dfferen requess, accepance (or refusal of he offer, and a paymen procedure. However, alhough hese applcaons work appropraely, has been denfed ha many of hem are no capable o jonly face several problems relaed o Web servce compose conex, such as: ( I canno be expeced o have all relevan nformaon on he sysem local knowledge base; for ha reason, he planner, when havng ncomplee nformaon, wll need o collec some nformaon wh he purpose of solvng composon problem; ( Web servces possess a few lmaons, hese lmaons nclude nably o perform effecve Transacon Managemen, auomac Servce Composon and lack of Scalably and Robusness. and ( The composon servce only can fnd one soluon for he goal, bu may be no he bes one. do: /jsw

2 JOURNAL OF SOFTWARE, VOL. 8, NO. 4, APRIL Ths paper proposes a Semanc Web Servce Composon Planner Agen (SWSCPA, whch fall n he realm of AI plannng. In order o overcome he curren servce composon s shorcomngs, SWSCPA mplemened n JADE, looks he process of servce compose as a plannng problem, and he process model underlyng he compose servce denfes he funconales requred by he servces o be composed and her neracons, componen servces ha are able o provde he requred funconales are hen assocaed o he ndvdual asks of he compose servces. Fnally, SWSCPA oban an opmzed plan based on servce qualy model. The remander of hs paper s organzed as follows. Secon 2 llusraes brefly our approach o he negraon of Agen and Semanc Web servces. Secon 3 hen dscusses our web servce qualy model for web servce. Aferwards, he man dea of web servce composon as a plannng problem s dscussed (Secon 4. Secon 5 dscusses he archecure of SWSCPA, whch negrae of semanc web servces no agen sysems, followed by a concree example n Secon 6. II. THE MAPPING BETWEEN AGENTS AND WEB SERVICES Agens and web servces are compable. For example, Web servce consss of a WSDL fle ha descrbes ha servce, SOAP whch specfes he messagng proocol and UDDI enables dscovery. Agen has a model of s envronmen, can communcae wh peers and ake approprae acons, can look for oher suable agens. When combng agens and servces, BPEL and oher WS- Polcy specfcaon provdes a model, UDDI provdes a mechansm for dscovery, SOAP offers a sandardzed mechansm of message exchange. Fnally WSDL allows agen o nvoke mehods of servce [4]. As he mos mporan elemen n agen, he agen acon s responsble for changng he agen s sae, and can be mplemened logcally or hrough procedural code. In general, he agen acon can be logcally formalzed n he form of acon:objec. For example, Sar:Reasoner means he acon of sarng he reasoner, and Send:Message means he acon of sendng a message. For he specfcaon of acon, each agen acon mus have specfcaon of he precondons ha mus be sasfed for he acon o be execuable, and specfcaon of he effecs ha wll be sasfed afer he acon s appled on he agen s sae. JADE (Java Agen Developmen Envronmen s a FIPA complan agen developmen envronmen whch faclaes he mplemenaon of mul-agen sysems. Snce Web servces mddleware has been negraed no JADE, agens mplemened n JADE can explo Web servces as compuaonal resources. A Web servce can be publshed as a JADE agen servce and an agen servce can be symmercally publshed as a Web servce endpon. Invokng a Web servce s jus lke nvokng a normal agen servce. In addon, Web servces clens can also search for and nvoke agen servces hosed whn JADE conaners. So, Our work s focus on he work process of he compose servce agen based on JADE. We proposed an servce composon agen, whch allow an auomaed Web servce composon o consruc powerful, robus servce nework by bndng ogeher a number of collaboraed agen-based Web servces. In hs paper, SWSCPA wll generae an opmzed servce composon plan, whch s based on he servce qualy model. We descrbed an exensble muldmensonal web servce qualy model below frs. III. THE MODEL OF WEB SERVICE QUALITY In a Web envronmen, mulple web servces may provde smlar funconales wh dfferen nonfunconal propery values. Such web servces wll ypcally be grouped ogeher n a sngle communy. To dfferenae he members of a communy durng servce selecon, her non-funconal properes need o be consdered. For hs purpose, we adop a web servces qualy model based on a se of qualy crera. An exensble QoS model s used o deal wh dynamc QoS values and varous knds of QoS n web servce profle. The exensble QoS model, QoS = { q1, q2,..., qn}, represens he se of QoS crera, where q presens sngle QoS nformaon [5]. QoS n crera for dfferen domans may be dfferen. To be more generc and precse, we consder 6 crera: performance, cos, relably, avalably, repuaon and fdely, can be represened by usng he exensble QoS model as follows: QoS ( S = { q per, qcos, qrel, qaval, qrep, q fd } : Performance: The performance q per s he me duraon (urn round me from a reques beng sen, o when he resuls are receved. Cos: I refers o he amoun of money ha he consumer pays for usng a servce, q cos. Relably: The relably q rel s he probably ha he requesed servce s workng whou a falure whn a specfed me frame [6]. Avalably: The avalably q aval s he qualy aspec of wheher he servce s presen or ready for mmedae use [6]. Repuaon: The repuaon q rep s he creron n measurng oal rusworhness of a servce. Fdely: The fdely q fd s he average marks ha are gven by dfferen consumers o he same QoS creron. There are many approaches o collec values of qualy mercs, for nsance, we can ge drecly from he servce descrpons, calculaon of a qualy value based on he defnng expresson n he servce descrpon, or Collecon hrough acve monorng. we ge values of hese quales from he OWL-S profle.

3 902 JOURNAL OF SOFTWARE, VOL. 8, NO. 4, APRIL 2013 Qualy of servce (QoS s ofen used o compue rankng values for comparng Web servces havng smlar funconales. A Web servce rankng mehod s bascally based on wo facors: a QoS model and a rankng algorhm, we wll dscuss hs rankng mehod n deal n 5.4 Nex, we wll descrbe he man dea of he paper, whch s look web servce composon as a plannng problem. IV. WEB SERVICE COMPOSITION AS A PLANNING PROBLEM A. Web Servce Composon usng AI Plannng In general, a plannng problem can be descrbed as a fve-uple < S, S 0, G, A, τ >, where S s he se of all possble saes of he world, S 0 S denoes he nal sae of he world, G S denoes he goal sae of he world he plannng sysem aemps o reach, A s he se of acons he planner can perform n aempng o change one sae o anoher sae n he world, and he ranslaon relaon τ S A S defnes he precondon and effecs for he execuon of each acon. In order o employ plannng, a web servce composon problem mus be refleced o a plannng problem. The desred oucome of he complex servce s descrbed as a goal sae, whle smple web servces play he role of plannng operaors, or acons. The planner hen wll be responsble for fndng an approprae plan,.e. an approprae sequence of smple web servce nvocaons, o acheve he goal sae [7]. The produced plan wll evenually consue he descrpon of he complex servce. An mporan benef of he plannng approach n general s he exploaon of knowledge ha has been accumulaed over years of research on he feld of plannng. Therefore, well known plannng algorhms, echnques and ools can be used o he advanage of effcen and seamless web servce composon. The represenaon of plannng problems has been a concern snce 1971 when Fkes and Nlsson developed he STRIPS language. From hs me on, oher researchers have proposed plannng problem represenaon languages based on STRIPS amng a developng a more expressve language for real plannng problems. In 1998, he Arfcal Inellgenge Plannng groups made an aemp o sandardze a language for real plannng problem descrpon proposng PDDL Plannng Doman Descrpon Language. PDDL has been used as he sandard language n nernaonal plannng compeons allowng plannng problems o be represened n a comparable noaon and planner performance o be evaluaed. In s verson 2.2, PDDL currenly allows plannng problem modellers o specfy acons wh duraon and deermnsc uncondonal exogenous evens, whch are facs ha wll become rue or false a me pons ha are known o he planner n advance, ndependenly of he acons ha he planner chooses o execue. A srong neres o Web servce composon from AI plannng communy could be explaned roughly by smlary beween OWL-S and PDDL represenaons. Moreover, snce OWL-S has been srongly nfluenced by PDDL language, mappng from one represenaon o anoher s sraghforward (as long as only declarave nformaon s consdered. When plannng for servce composon s needed, OWL-S descrpons could be ranslaed o PDDL forma [8]. Then dfferen planners could be exploed for furher servce synhess. B. Translang OWL onologes o PDDL Web servce onologes, nal and goal onologes abou sae world are ranslaed o a doman and a problem under Arfcal Inellgence Plannng approach; hs requres ransferrng specfcaons of onologes o PDDL language. The Class mappng (Class and properes (Propery ncluded n OWL onologes of he nal and fnal sae of PDDL ypes (Type and Predcaes (Predcae are necessary. Web servces are mapped ono PDDL acons, n whch he model of an acon represens a Web servce. Thus he man relaons of converson among (OWL-S specfcaons and her correspondng represenaon n PDDL are summarzed n Fg 1[8]. SWSCPA convers he doman onology and servce descrpons n OWL and OWL-S, respecvely, o equvalen PDDL problem and doman descrpons usng s OWLS2PDDL converer mddleware. C. The AI planner Xplan Xplan s a heursc hybrd FF planner based on he FF planner developed by Hoffmann and Nebel [9]. I combnes guded local search wh relaxed graph plannng, and a smple form of herarchcal ask neworks o produce a plan sequence of acons ha solves a gven problem. If equpped wh mehods, XPlan uses only hose pars of mehods for decomposon ha are requred o reach he goal sae wh a sequence of composed servces. To use Xplan for semanc Web-Servce composon, Xplan s complemened by a converson ool ha

4 JOURNAL OF SOFTWARE, VOL. 8, NO. 4, APRIL convers OWLS servce descrpons o correspondng PDDL descrpons ha are used by Xplan as npu o plan a servce composon ha sasfes a gven goal [10]. In conras o HTN planners, Xplan always fnds a soluon f exss n he acon/sae space over he space of possble plans, hough he problem s NP-complee. Xplan also ncludes a re-plannng componen o flexbly reac o changes n he world sae durng he composon plannng process. Togeher he mplemenaons of Xplan and OWLS2PDDL converer make up our Semanc Web Servce Composon Planner Agen(SWSCPA. V. THE ARCHITECTURE OF THE SEMANTIC WEB SERVICE PLANNING AGENT Snce we can look servce composon problem as a plannng problem, Plannng problems nvolve a se of nal saes, a se of goals and he correspondng acons ha conrbue o acheve hese goals. A planner agen s an agen responsble for solvng plannng problems. Proposed plannng agen s characerscs are follow he followng desgn prncples: ( concurrence: Several processes, such as envronmen monorng, execuon, and plannng are carred ou n a concurren way; ( Reacvy of he sysem s favored by an archecure organzed by levels, n whch hghes levels show a more complex behavor and represen nformaon wh a hgher absracon level. The SWSCPA (Plannng agen archecure consss of four man modules (see Fgure 2: ( A ranslaor of OWL-S [11]specfcaon o PDDL [12], whch ranslaes nal doman and goal sae onologes, ogeher wh servce descrpons respecvely mplemened n OWL and OWL-S, n a doman specfcaon and s correspondng plannng problem n PDDL; ( an envronmen model, whch allows planner o have a ceran knowledge abou exernal envronmen. Ths knowledge s expressed hrough facs and numercal varables; ( Xplan, whch res o fnd ou a plan o reach objecves; (v Opmzaon module, whch akes nal plan fle as npu and produce a opmzed plan based on he QoS selecon algorhm. Inal saes Goal Problem Descrpon Fle Targe Servce OWL-S Conver o PDDL Acons: precondons effec OWL-S Fles XPlan Plan Doman Descrpon Fle Inal Plan Servce Communy Model Envromen Opmzaon module Plan OWL-S has been chosen for descrbng Web servces. To descrbe nal and goal sae, he agen use OWL onologes. As mos classcal planners, proposed plannng agen needs a descrpon of boh doman and problem hrough a modelng language. For ha purpose, PDDL language has been chosen as s currenly a plannng doman descrpon sandard. SWSCPA akes a se of avalable OWL-S 1.1 servces, relaed OWL onologes, and a plannng reques (goal as npu, and reurns a plannng sequence of relevan OWL- S servces ha sasfes he goa, for hs purpose, frs convers a gven doman onology and servce descrpons n OWL and OWL-S 1.1, respecvely, o equvalen PDDL problem and doman descrpons usng an negraed OWLS2PDDL converer[17]. The doman descrpon conans he defnon of all ypes, predcaes and acons, whereas he problem descrpon ncludes all objecs, he nal sae, and he goal sae. Boh descrpons are hen used by he AI planner XPlan o creae a plan n PDDL ha solves he gven problem n he acual doman. An operaor of he plannng doman corresponds o a servce profle n OWL-S, whle a mehod s a specal ype of operaor for fxed complex servces ha SWSCPA may use durng s plannng process. B. Generaor An Inal Plan by Xplan We use Xplan,as descrbed n [10], o creae a plan. Xplan use he Mcrosof MSXML Parser for readng PDDXML defnons and generang plans n XML forma. The Xplan sysem consss of one XML parsng module, and followng preprocessng modules. Frs, requred daa srucures for plannng are creaed and flled, followed by he generaon of he nal connecvy graph and goal agenda. The core plannng modules concern he heurscally relaxed graph-plan generaon and enforced hll-clmbng search. Afer he doman and problem defnons have been parsed, Xplan comples he nformaon no memory effcen daa srucures. A connecvy graph s hen generaed and effcenly realzed by means of a look up able, whch conans nformaon abou connecons beween facs and nsanaed operaors, as well as nformaon abou numercal expressons whch can be conneced o facs. Xplan uses an enforced hll-clmbng search mehod o prune he search space durng plannng, and a modfed verson of relaxed graph-plannng ha allows o use (decomposon nformaon from herarchcal ask neworks durng he effcen creaon of he relaxed plannng graph. Fgure 3 shows a fragmen of he plan descrpon produced by Xplan,.e., a sequence of acons, ha s he composed sequence of correspondng OWL-S servces, ha can be execued by he agen. Fg 2: Semanc Web Servce Composon Planner Agen(SWSCPA A. OWL-S Conver o PDDL To our knowledge, here are several proposals, e.g. OWL-S [14], WSMO / WSML [15] and WSDL-S [16], o mplemen semanc Web servces. In SWSCPA,

5 904 JOURNAL OF SOFTWARE, VOL. 8, NO. 4, APRIL 2013 Afer Xplan produce a plan, wll generaor a sequence of acons, ha s he composed sequence of correspondng OWL-S servces, as Fg 4(a. SWSCPA looks he acons as asks, and every ask connec o a correspondng OWL-S servce, as Fg 4 (b. We defne a plan as below: Defnon (plan A se of pars p = { 1, s1, 2, s 2,, N, sn } s a plan ff: {, 1 2,..., N } s he se of asks. For each 2-uple <, s > n p, servce s s assgned of ask. s a drec successor of one of he ask n { 1, 2,..., 1} s no a drec successor of one of he ask n { + 1, + 2,..., N } Fg 4(b provdes aggregaon funcons for a compose servce usng plan p = {, s 1 1, 2, s 2,, N, s N } We call he plan, whch generaed by Xplan, as nal plan. As we know, maybe here s a se of canddae Web servces s ha are avalable o for each ask. So, he nal plan may be no a bes plan for he goal. In our Servce composon framework, Sysem provde a servce qualy model(descrbed a 3, and each Web servce s assocaed wh a qualy vecor. Based on hese servce qualy vecor and servce communy nformaon, he opmzaon module of he SWSCPA can adjus nal plan o a opmze plan. XPlan Inal Plan C. Web Servce Communy The concep of web servce communy addresses he ssue of composng a large and changng collecon of web servces, Servce communes provde descrpons of a desred funconaly whou of referrng o any acual servce. The se of members of a communy can be fxed when he communy s creaed, or can be deermned hrough a regsraon mechansm, hereby allowng servce provders o jon, qu, and rensae he communy a any me. When a communy receves a reques o execue an operaon, hs reques s delegaed o one of s curren members. In our Servce composon framework, every web servce agen can regser o any communes, and communy also provde a mechansm o search specal web servces. D. Opmzaon of he Plannng Inal plan(descrbed n 5.2 produce a process model of a compose servce,whch only denfes he funconales requred by he servces o be composed, and componen servces ha are able o provde he requred funconales are hen assocaed o he ndvdual ask of he compose servce. So, nal plan s a paral soluon for he goal, and may no have a complee vew of he global soluon. Assume ha a nal plan has k asks p,,..., }, { 1 2 k each ask can acheved by one web servce, here are many web servce whch have he same funcon. Thus, he opmze module selec a bes web servce for each ask. The opmze module adops he followng approach o oban an opmal plan. Gven a ask, f only one web servce can acheve he, hen he opmze module selec ha web servce for he. For example, n Fg 5, he ask 3 only have one web servce S. In hs case, 3 S s used o execue 3 3. Gven a ask here are a se of web servce ha can be used o execue. In hs case, he opmze module needs o selec one web servce from he se. Task n Inal Plan Task 1 2 n s1 s2 sn s1 s2 sn s1 s2 sn s11 s12 s21 s22 s3 sn1 sn2 (a (b Fg 4 an Inal Plan Generaed by SWSCPA s1k1 s2k2 snkm Fg 5: Servce selecon for he asks

6 JOURNAL OF SOFTWARE, VOL. 8, NO. 4, APRIL SWSCPA provde an opmzaon module o opmze he nal plan, whch based on web servces QoS selecon algorhm. QoS-based selecon of servces s very complex, no only due o he dversy of mulfarous qualy mercs wh dfferen value ypes, value range, and measuremens, bu also snce an effecve algorhm, whch evaluaes all mercs n combnaon, s mssng. We assume ha he qualy profle of m canddae servces n se S for ask s denoed as S = { S 1, S 2,..., S m }, where S = { q1, q 2,..., qk }. I defnes ha he adversemen of servce S has k qualy mercs provded. I s que obvous ha s raher unlkely ha any S wll have he same number of qualy mercs. So, we should have a preprocess o he qualy mercs as below: To re-arrange he mercs of S n he same order. If S s lackng a qualy, hen one can add a merc and se s value o 0. Therefore, he marx of QoS for for ask M = S, S,..., S } looks lke: { 1 2 m q11 q12... q1 k q21 q22... q2k M = qm1 qm2... qmk Here, M s a m k marx, wh he qualy nformaon of canddaes servces n he each rows. Each column conans values of he same qualy propery. For unformy, marx M has o be normalzed wh he objecve o map all real values o a relavely small range,.e., he elemens of he fnal marx are real numbers n he closed nerval [0; 1]. The man dea of he algorhm s o scale he value ranges wh he maxmum and mnmum values of each qualy merc for housands of curren canddae servces. Accordngly, he maxmum and mnmum values are mapped o he unform values 1 and 0. Some of he crera used could be negave,.e., he hgher he value s, he lower he qualy s. Ths ncludes crera such as execuon me and execuon prce. Oher crera are posve crera,.e. he hgher he value s, he hgher he qualy s. and, here are a knd crera ha he user expecs he value of hs qualy o be as close he gven value as possble, we call hs knd crera as nearby crera. So, for negave crera, values are scaled accordng o Equaon 1: q qmn 1 f ( qmax qmn v = qmax q (1 mn 1 f ( qmax = qmn For posve crera, values are scaled accordng o Equaon 2: qmax q 1 f ( qmax qmn v = qmax q (2 mn 1 f ( qmax = qmn For nearby crera, values are scaled accordng o Equaon 3: qmax q 1 f ( θ qmax qmax qmn q qmn (3 v = 1 f ( θ qmn qmax qmn q θ 1 f ( θ ( qmn, qmax qmax qmn where q = max ( q, q = mn ( q, j ( 1, k. max (1, m mn (1, m θ s a gven value. By akng he Formula 3 as an example, descrbes he case ha he value of a qualy as close as possble o θ s good. Afer he scalng, we oban a marx V = ( v, he weghed value for each qualy merc s defned n he web servce onology. The followng formula s used o compue he overall qualy score for each servce: Score ( S = k j = 1 where w [0,1 ] and j ( v, j w j k j = 1 w j = 1, w j s he wegh of he crera. The opmze module wll choose he web servce whch has he maxmal value of Score(S for he ask. If here are more han one web servce whch have he same maxmal value of Score(S, hen a web servce wll be seleced from hem randomly. In our servce composon agen framework, here are 6 QoS crera, hey are performance, cos, relably, avalably, repuaon and fdely, can be represened by usng he exensble QoS model as follows: QoS ( S = { q per, qcos, qrel, qaval, qrep, q fd }, so he crera q per, qcos are scaled accordng o Equaon 1, and he crera q rel, qaval, qrep, q fd are scaled accordng o Equaon 2. VI. EXPERIMENT SWSCPA,whch based on OWLS-Xplan and JADE[19], has been mplemened n Java, and provdes an negraed graphcal user nerface. OWLS-Xplan uses he Mcrosof MSXML parser for PDDXML defnons and generang plans n XML forma. In addon, OWLS-XPlan provdes an negraed PDDXML edor ha allows he experenced user o ed he goal, and he nal sae onology of gven plannng problem. JADE, a

7 906 JOURNAL OF SOFTWARE, VOL. 8, NO. 4, APRIL 2013 Java based agen developmen envronmen, can be used o develop he agens and o esablsh communcaon beween hem. JADE also provde he envronmen for mplemenng he FIPA Conrac Ne Proocol [18] for negoaon beween he agens nvolved n he sysem. Fgure 6 shows he layou of SWSCPA n he form of blocks, wh each block represenng dfferen asks for varous acves such as CreaeMedcalTransporAccounServce, FndNearesArporServce, BookMedcalFlghServce nvolved n a Medcal Plannng reques. SWSCPA mpors he defnons of smple, aomc web servces expressed n OWL-S and ranslaes hem o plannng operaors. Inpus and precondons of OWL-S web servces are reaed as relaons o be quered n he precondon ls, whle oupus are reaed as aoms o be added hrough he operaor's add ls. Effecs are also aoms o be eher added hrough he add-ls or deleed, hrough he delee-ls. Fnally, SWSCPA generae a opmze plan based on servces QoS selecon mehod. In he followng case sudy, SWSCPA akes 30 avalable OWL-S servces whch belong o dfferen communes, a doman descrpon conssng of relevan OWL onologes and a plannng query as npu, reurns a nal plan sequence of composed servces ha sasfes he query goal, he ask name s he servce name, he screen sho lke Fg 6(a. There are several avalable servces n each communy. For example, Table 1 shows ha here are four web servces n Flgh Accoun Communy, hs four servce have he same IOPE parameers, bu her QoS qualy crera values are dfferen. In order o es selecon mode, we assgn a es values for hs QoS qualy crera values as show n able 2. smaller, Relably, Avalably, and Repuaon are o be bgger. The resul of normalzaon carred ou by our algorhm for he four canddae servces referrng o v s: (4 V = Assumng he weghed value for each qualy merc as w ={0.2,0.5,0.1,0.1,0.1 }, we apply Formula 4. o oban a qualy evaluaon se, named Score ( = {0.25,0.73,0.63,0.6}. Tha s, n case of pung a hgh wegh on prce, servce CreaeMedcalFlghAccoun2Servce s he bes choce for he ask. As show n Fg. 6(b, afer opmzng he nal plan, SWSCPA ge a opmzed plan for he compose servce. TABLE 1: THE SERVICES OF FLIGHTACCOUNT COMMUNITY Commun y name FlghAcco un Web servce CreaeMedcalFlghAccoun Servce CreaeMedcalFlghAccoun 2Servce CreaeMedcalFlghAccoun 3Servce CreaeMedcalFlghAccoun 4Servce Servce Parameer Inpu: CreaeMedcalFlghAccoun2.ow l#credcardinformaon CreaeMedcalFlghAccoun2.ow l#desredaccoundaa Oupu: NONE Precond: NONE Effecs: MedcalFlghCompany2_Onolo gy.owl#valdaccoun TABLE 2: TEST DATA Servce Name per for ma cos rel abl y ava lab ly rep ua on nce CreaeMedcalFlghAccounServce CreaeMedcalFlghAccoun2Servce CreaeMedcalFlghAccoun3Servce CreaeMedcalFlghAccoun4Servce From he defnons of each qualy creron, we know ha Cos and Performance are expeced o be REFERENCE [1] D. Wu, B. Parsa, E. Srn, J. Hendler, D. Nau, Auomang DAML-S Web servces composon usng SHOP2, n: Proc. ISWC 03, 2003 [2] S. McIlrah, R. Fadel, Plannng wh complex acons, n: Proc. NMR 02, [3] Huhns, M.N. e al, Research Drecons for Servce- Orened Mulagen Sysems IEEE Inerne Compung, IEEE Compuer Socey 2005 [4] S. McIlrah, S. Son, Adapng Golog for composon of semanc Web servces, n: Proc. KR 02, [5] Lu, Y., Anne H.H. Ngu and Zeng, L., QoS Compuaon and Polcng n Dynamc Web Servce Selecon, IEEE Compuer Scocey, ACM Press, New York, May [6] Kalepu, S., Krshnaswamy, S. and Loke, S. W., Very: A QoS Merc for Selecng Web Servces and Provders, WISEW 03, 2004, pp [7] D. Mc Dermo, Esmaed-regresson plannng for neracons wh Web servces, n: Proc. AIPS 02, 2002, pp [8] Web Servces Plannng Agen n Dynamc Envronmens wh Incomplee Informaon and Tme Resrcons

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