Resource Scheduling Based on Dynamic Dependence Injection in Virtualization-based Simulation Grid

Transcription

1 Proceedngs of the 200 4th Internatonal Conference on Computer Supported Cooperatve Work n Desgn Resource Schedulng Based on Dynamc Dependence Injecton n Vrtualzaton-based Smulaton Grd Hanbng Lu,Hongy Su, Shouy Zhan School of Computer Scence and Technology Bejng Insttute of Technology Bejng, Chna lhb_bng@26.com Xundong Cha,Yabn Zhang,Baocun Hou,Lnqn Guo,Shua Fan Bejng Smulaton Center Bejng, Chna Abstract Wth the grd appled n smulaton wdely, the tradtonal grd schedulng can not meet the requrements, whch needs to server the apponted doman applcaton not the smple computaton jobs. The extng grd schedulng mechansms based on the physcal computng nodes, whch deployed wth apponted envronment, make the smulaton resource usage less flexble and effcent due to the system structure lmtaton. Accordng to the smulaton applcaton requrement, ths paper ntegrated vrtualzaton technology nto the exted Smulaton Grd to break the statc dependence couplng and proposed a dynamc dependence njecton schedulng mechansm. Furthermore, some solved key technques are ntroduced, manly ncludng resource dscovery and selecton algorthm based the smulaton resource vrtualzaton encapsulaton. Ths schedulng mechansm has a better effcency n dynamc deployment, the real-tme operaton and the capabltes of current networked M&S platform on hghly customzable resources sharng, collaboraton and fault tolerant. Fnally, the concluson and some further works are gven. Keywords-Vrtualzaton-based Smulaton Grd;Schedulng; Dynamc Dependence Injecton; Smulaton Resource Management; Servce-Orented I. INTRODUCTION Now, combnng current M&S technology wth grd technology, provdng a dynamc sharng, autonomy, fault tolerant and collaboraton smulaton resource envronment has become a new trend of networked M&S. Now, more and more smulaton projects ntegrated wth grd technology were conducted, such as SF-Express supported by Unted States Department of Defense [], Cross-Grd [2], DS-Grd [3], Ness- Grd [4], Federaton X Grd [5] and COSIM-GRID of Chna [6], etc. Meanwhle, smulaton s an mportant component of computer scence, whch usng the computng resource to operate the smulaton msson. So, a relable and unform schedulng mechansm that accesses heterogeneous computng nodes n Smulaton Grd must be provded. There are lots of grd schedulng modes and algorthms have been proposed to get a near-optmal schedule [8]. Although the extng schedulng modes and algorthms performed better than the tradtonal random or sequental schedulng approaches, they take the computng node as the whole entty whch already been statcally deployed wth the system-orented and applcaton-orented confguraton. Wth the development of smulaton applcaton scale, the number of grd envronment nodes has to be ncreased to satsfy the smulaton requrement. So, the abundant heterogeneous computng nodes and the computng nodes status dynamc transformaton may make the exstng schedulng modes and algorthms become more complcated, even trgger the NP problem. Vrtualzaton technology can be traced back to the end of the 20th century 50's, Chrstopher Strachey frstly put forward the basc vrtualzaton concept n report the Tme Sharng n Large Fast Computers n 959 [7]. Snce the 20th century 60s, vrtualzaton technology has been used to take full advantage of the relatvely expensve hardware resources. Over tme, mcro-computers and PC can provde more effectve and economcal processng capacty, the vrtualzaton technology was no longer wdely used. In recent year, wth the performance of the PC, the vrtualzaton technology especally the computng system vrtualzaton, whch can realze the utlzaton of computng resources more fully ratonal, transparent, effcent and customzable, becomes the research hotspot agan and develops fast[2]. So, the vrtualzaton technology, whch refers to mprove the hgh-level dynamc and effcent resource management, can provde a new way to strengthen the capabltes of current Smulaton Grd. Amng at ntegratng vrtualzaton technology nto exstng grd schedulng mechansm, the remander of ths paper s organzed as follows: Secton 2 brefly surveys current related work on vrtualzaton-based smulaton and grd schedulng mechansm; Secton 3 descrbes the framework of vrtualzaton-based schedulng mechansm; Secton 4 focuses on the key technology of mechansm; Secton5 takes a applcaton to llustrate the research work; Secton6 concludes n a bref dscusson of current ssues and future work. II. RELATED WORK In Chna, Bo Hu L frst proposed Smulaton Grd that s a syntheszed multdscplnary technology and mportant tool to realze the dynamc share and reuse of varous resources n grd/federaton safely, collaboratvely cooperaton, dynamc optmzaton of schedulng executons, etc. [6]. Due to the resource sharng character, Smulaton Grd could be taken as a network-level vrtualzaton. Smulaton Supported by the Natonal 973 plan of Chna (2007CB30900) and the Natonal 863 plan of Chna (2007AA04Z53) /0/$ IEEE 396

2 Grd can overcome the shortcomngs exstng n HLA networktzed M&S applcaton (especally the lmtaton n the dynamc sharng, autonomy, fault tolerant and collaboraton of smulaton resource and the securty applcaton mechansm) [6]. Moreover, the contnuous mprovement of computer performance, quantty, type, especally the advent of mult-core processng or redundant computng resources makes exstng Smulaton Grd need to be strengthenng n the followng aspects: () capablty of sharng fne-graned resources (ncludng the CPU core, memory, software and other subresources n the node), (2) capablty of customzng smulaton resource, (3) effcent and transparent capablty of support mult-level sharng. So, based on the research fruts of smulaton grd, by combnng the vrtualzaton technology and ntroducng consultng cloud computng model, amng to strengthen the granularty and flexblty of resource management, a new knd of networked M&S platform s put forward, namely Vrtualzaton-based Smulaton Grd. It acheves a scalable and transparent physcal framework that can take advantage of the polymerzaton performance of physcal resource to buld the vrtual mage on demand, further to deploy an effcent and customzable smulaton envronment that can satsfy multusers dynamc optmzaton resources cooperaton and schedulng, etc., eventually to support the varous actvtes n smulaton lfe cycle (from argumentaton, research, desgn, development, test, executon, evaluaton to mantenance and dsposal). Vrtualzaton-based smulaton grd prototype archtecture that ntroduced the vrtualzaton technology nto the exstng Smulaton Grd platform s shown n Fg.2, whch ncludes entty resource layer, vrtualzaton resource layer, mddleware layer, smulaton-orented core servce layer, applcaton portal layer of vrtualzaton-based smulaton grd and applcaton layer. Fgure. Archtecture of Vrtualzaton-based Smulaton Grd. Wth the development of vrtualzaton, some smulaton applcatons ntroduce t as a new dea to settle some ssues, such as the BotNet Evaluaton Envronment (BEE) [9], the VMware ESX-based partcle detector smulaton system n ATLAS experment [0] and the complex hydraulc smulaton basng on JVM of Chna [6]. However, the vrtualzaton-based smulaton just started generally. The grd schedulng modes could be classfed nto three centralzed, dstrbuted and herarchy schedulng model [8]. They are defned by the scheduler and hosts relatonshp. In addtonal, varous algorthms have been proposed whch n recent years each one has partcular features and capabltes, such as Mn-Mn, Suffer and so on [8]. The extng schedulng modes and algorthms performed better than the tradtonal random or sequental schedulng approaches. However smulaton operaton needs the apponted deployment computng envronment accordng to the applcaton requrement besdes the computng resource communcaton and computatonal capablty, the exstng schedulng mechansms only take the computng nodes as the entty nto consderaton. And smulaton resource means any hardware, software and nformaton resources whch can promote the M&S relatve work. So, wth the development of smulaton applcaton scale, the exstng schedulng mechansms lack flexble and effcent. For the purpose of ncreasng smulaton executon effcency and enhancng fault-tolerance ablty, smulaton schedulng already been nvestgated by many researchers. The vrtualzaton technology whch s used to break the system applcaton statc couplng, gves a new dea for the exstng grd schedulng. Ths schedulng mechansm has been desgned to smplfy the exstng algorthm complcaton based on the smulaton operaton characters and get a deep level resource sharng and cooperaton. III. OVERVIEW OF SCHEDULING MODEL Vrtualzaton-based smulaton grd s a common technology for both mltary applcaton and cvl applcatons, whch wll brng huge reformaton and nnovaton for M&S applcaton mode, management mode, nfrastructure technology, and takes great socal effects and economc benefts. A. Bref of Vrtualzaton-based Smulaton Grd Servce The core layer of the vrtualzaton-based smulaton grd s smulaton-orented core servce (see from Fg), whch bases on the mddleware servce vrtualzaton servce mddleware and grd resource servce mddleware to provdes varous core servces for collaboratve smulaton experment executon and applcatons management. Moreover, the schedulng mechansm s the fundamental and mportant aspect of the smulaton-orented core servce, whch nvokes the sutable resource respondng the request of applcatons/other components/users drectly or ndrectly. In ths secton, we wll present a dynamc dependence njecton schedulng mechansm archtecture, whch ntroduces the vrtualzaton technology to support dstrbuted, collaboratve smulaton resource dynamc schedulng. 397

3 B. Archtecture of the Schedulng mechansm By ntroduced the vrtualzaton technology, the schedulng mechansm can be generalzed as stages: Resource Dscovery, Resource Selecton and Resource Dynamc Dependence Injecton. (Fg2.) Fgure 2. Archtecture of Schedulng Mechansm. After the smulaton applcaton descrpton beng nserted, they wll enter the resource dscovery unt. In ths stage, the am s to dscovery the potental resource accordng to the certan smulaton applcaton, whch could be defned as establshng the resource pool. In our framework, the resources are encapsulated by vrtualzaton technology, whch are the logcal mages of entty smulaton resources. By recevng nformaton, Schedulng Selecton unt selects the more approprate resource. At last the Dynamc Injecton reles on the resource vrtualzaton encapsulaton mappng or applcaton couplng relatonshp dynamcally allocatng the entty smulaton resources when the smulaton executon. IV. KEY TECHNIQUES UNDERLYING THE PROPOSED ARCHITECTURE IN MILITARY ORIENTED SIMULATION GRID A. Smulaton Resource Vrtualzaton Mappng The resource presence s not alone accordng to the smulaton applcaton, they usually have defnte applcatonorented or system-orented dependence couplng. The vrtualzaton s ntroduced to break statc dependence couplng, sheld heterogeneous, etc. and get hgh effcency resource management. The vrtualzaton mappng s the bass of our schedulng mechansm, the dscovery and njecton unts rely on the mappng result. The resource layer of vrtualzaton-based smulaton grd, by ntroducng the vrtualzaton encapsulaton, s dvded nto entty resource layer and vrtualzaton resource layer. Entty resource layer whch sustans the smulaton operaton as basc groundwork, ncludng the storage resource (all types of storage meda), equpment resource, model resource, software, etc. Vrtualzaton resource layer s the logcal vew of entty resources, whch apply vrtualzaton encapsulaton technology to shelds heterogeneous, couplng, complex and dstrbuted characterstcs of entty resource, to support the mult-granularty, flexblty, transparency and convenent operaton mode. The resources vrtualzaton-based encapsulatons n accordance wth applcaton-orented dependence couplng are classfed as: physcal level, system software level, applcaton software level and smulaton-orented applcaton level. So, a three-herarchy mappng s bult to explan the mappng relatonshp of the entty and the vrtualzaton resource, whch s used to express the dependence couplng. The frst mappng level can be seen from the followng equaton (). The VL means the frst level mappng result, the letter V sgns the vrtualzaton encapsulaton resource. Moreover, the letter d sgns the duplcate set of the vrtualzaton resource. VL = VP{R,R 2,...,R n} Vs {R,R 2,...,R n} vr,vr 2,...,vRm vr 2,vR 2,...,vR 2m = {vr,vr 2,...,vR n} S... vr n,vr n2,...,vr nm P vr,vr 2,...,vRm vr,vr,...,vr {d{vr },d{vr },...,d{vr }}... vr,vr,...,vr 2 2 2m = 2 n S n n2 nm P () Wth the hgh performance, a sngle physcal entty resource s encapsulated as mult-logcal vrtualzaton resources (V P ) accordng to the applcaton requrement and entty performance, whch can mprove the resource customzaton, utlzaton and reduce management costs, etc. The system level resource s encapsulated as mage fle (V S ). In ths vrtualzaton-based mappng level, we can smplfy the smulaton envronment deploy and mprove the physcal resource utlzaton. Basng on the varous functon nterfaces, the applcaton software resource whole or partly encapsulated as servce (V a ), whch can support the requrement of smulaton-orented applcaton. So, equaton (2) s used to explan ths process. VL = Va {R,R,...,R } VL vr,vr,...,vr 2 2 n 2 m vr 2,vR 2,...,vR 2m = VL... vr n,vr n2,...,vr nm a {vr },{vr },...,{vr } 2 m {vr 2},{vR 22},...,{vR 2m} VL, VL VL =... {vr },{vr },...,{vr } n n2 nm a (2) 398

4 R a sgns the applcaton software resource, and VL s the subset of VL whch satsfes the requrement of R a. In addton, the letter sgns the nstance set of the vrtualzaton resource, whch could provde the same functon or servce durng the executon. Others symbols sgnfcaton can see from the llustraton of equaton (). The smulaton-orented applcaton resource s developed or encapsulated as a servce (V o ) regstered n the grd envronment. It can be llustrated n the followng: VL 3= Vo{R,R 2,...,R n} VL2 ={vr,vr 2,...,vR n} o VL2 ={{vr },{vr 2},...,{vR n}} o VL2, VL2 VL 2 (3) R o means the smulaton-orented applcaton resource and others symbols sgnfcaton can see from the llustraton of () and (2). B. Vrtulzaton Resource Dscovery Stage ) Vrtualzaton Smulaton Resource Descrpton The smulaton resource always belongs to vared dstrbuted unts, whch concerned wth multdscplnary knowledge, such as mechancs, acoustcs, optcs and so on. So, n order to acheve effcent resource dscovery, schedulng and guarantee the smulaton applcaton performance, we should establsh the unform, standard vrtualzaton resource descrpton, whch also can be used to regstry resource n the vrtualzaton-based smulaton envronment. Accordng to the mappng result, we summarze the attrbutes of the vrtualzaton resource nto two categores, one category s functon or servce can provde for the upper level; another category s the requrement of the lower level. So, the resource n the vrtualzaton-based smulaton grd was descrbed as: vrresource : =<R R {R-nfo{R-name,R-classfcaton,...,R-address}, R-fundes{fundes,HasInput,HasOutput,...,Int} }}, {R-precson, R-granularty}, PA CR R MR{VL,VL,VL }, 3 2 R RA {R-AR,R-SR,R-PR}> (4) The set of R PA and R RA respectvely represents these two categores. The set R PA not only ncludes the functon(rfundes) whch provdes for the upper but also the resource basc nformaton(r-nfo) that n other vew could be consdered as the functon, such as name, classfcaton, etc.. The set R RA manly ncludes three levels requrements ncludng applcaton software aspect(r-ar), the system aspect(r-sr) and hardware aspect(r-pr). In order to elmnate dependence herarchy and complcaton, R RA just descrbe the proxmate level requrement. In our framework we adapt the mult-granularty modelng technology, so, a model could be composed by several sub-levels components. The R CR was used to explan ths relatonshp and wll be used n the schedulng to dscovery the mult-level models and schedule composton. The R MR means the exstng mappng relatons among the resources, whch wll be manly used n resource schedulng mechansm to defne the R RA set. In addton, R RA and R MR depend on the specfc stuaton, so they may be the empty set. By the way, n our applcaton, we usually take R PA as the prmary factor to get an applcaton orented resource vew. 2) A Mult-phase Dscovery based on Mult-Mappng The frst stage of schedulng takes a mult-phase dscovery process, whch bult on the semantc-based matchng [5]. The followng s the three-phase: R PA matchng-> R MR examnng-> R RA matchng In order to prevent NP problem and guarantee the effcency, the R MR examnng step s to check the R MR set and decde the scale of R RA. From (-3), we know that f the correspondng set R MR s not empty, not only means the resource already got the support of bottom (R RA ) or deployed, but also mples there must be the same resource whch R MR s empty. Moreover, dfferent stages of matchng may use dfferent attrbutes of resources. So, the followng pseudo code ntroduced n the mult-phase dscovery process: Fgure 3. Mult-phase Dscovery Process. We take the R PA matchng process as example to explan the matchng algorthm. Frstly, assumed the R PA of provded resource P had α attrbutes, requested resource R(R PA )had γ attrbutes, the resource matchng process can be explan n equaton(5). P(R ) = R(R ), {,2,, α},(<k γ,j {,2,, γ}) PA PA jm m m= M (P(R ) ) = max M (P(R ),R(R ) ) d Input: Smulaton Applcaton Descrpton Output: Vrtualzaton Resource pool do matchng R PA f R PA s applcaton orented f R MR s not Ø then set R MR =VL 3 break; else set R MR ={R-AR,R-SR,R-PR} do matchng R RA end do R RA f R PA s software orented f R MR s not Ø then set R MR =VL 2 break; else set R MR ={ R-SR,R-PR } do matchng R RA end do R RA f R PA s system orented f R MR s not Ø then set R MR =VL break; else set R MR ={ R-PR} do matchng R RA end do R RA end do R PA k λ PA d PA PA j j= (5) 399

5 M d(p(r PA) ) s the degree of the resource P match request R, ts value [0~]. In addton, the precseness of R PA resource mostly decdes by the R CR. Wth the development of M&S technology, some resource may be composed by sub-component, so, the R CR should be taken nto account. n s defned as the R CR set whch P(R PA ) composes P, n s the composton layers, (5) can be extended to: M d λ PA = max Md PA PA j j= μ n max M d PA k= R(R PA) j (P(R ) ) max{ (P(R ),R(R ) ), (P(R ), } After ths mult-phase, a vrtualzaton resource pool s be set up accordng to the specfc applcaton. C. The Resource Dynamc Dependence Injecton based on Mult-mappng Ths stage s to select the approprate resource from resource pool and nject t to the entty resources to construct the VMs(Vrtual Machnes) accordng to the applcaton requrement. Basng on the mappng relatonshp, ths stage can be regarded as the optmzaton nstantaton of VL, VL 2 and VL 3. In order to guarantee the performance, especally the realtme capablty and load balancng, the smulaton operaton takes relatve optmal performance resource. Accordng to the requrement of smulaton applcaton, the capablty parameters of the resource performance can be dvded nto two knds. One s the matchng degree of dscovery; another s the parameter obtaned by the montor. The equaton (7) calculates the resource performance. Md{ R PA} s the matchng degree and M{ RPA} respectvely presents the status of the resource tself such as state, verson, computng performance, I/O and so on. λ Optmal ( R ) max ( { } m PA = Md RPA, MR { PA}) j = j= (7) To get the optmal resource of the system software level, applcaton software level and smulaton-orented applcaton level, we manly base on the parameter Md{ R PA}. However, the physcal level resource depends on the parameter M{ R PA}, whch means commputng performance and communcaton performance n our applcaton. For computng performance, CPU s man frequency and memory resource are used to descrbe t, and sgned as Calc( node ).For communcaton performance, we consder communcaton delay and speed of node n the muster s respectvely sgned as DELAY ( node, node j) and SPEED( node, node j). The physcal level resource communcaton performance can be descrbed by (8). COMM ( node, nodej) = { DELAY ( node, node j), SPEED ( node, nodej) j =,2,, M, j} (8) (6) The dynamc dependence njecton of schedulng s shown n Fg.4., t also can be seen as the smulaton resource just-ntme bndng or dynamc deployment process. Input: Resource Pool& Mappng Relatonshp Output: Dependence Injecton Step: // Instantaton VL 3 MaxM ( d{ Vo}) MaxM ( d{{ vr}, vr { 2},..., vr { n }} o ) vr { }, vr { 2},..., vr { m} vr { 2}, vr { 22},..., vr { 2m} Va... vr { n}, vr { n2},..., vr { nm} a Select Max( Md{ Va }) to nject Max( Md{ Vo }) step2: // Instantaton VL 2 VS {d{vr },d{vr 2},...,d{vR n}} S Select Max( Md{ Vs }) to nject Max( Md{ Va }) step3: // Instantaton VL f VL s not Ø then AR { PR} { R - PR} of I( VL ) // I means Instantaton set; A means assgned f AR { PR} Calc({ R PR}) then Select Max( A{ R - PR}) to nject Max{ Md( Vs )} else Max{ R PR} Max( Calc({ R PR} towords { Max( Md{ Vo}), Max( Md{ Vs})})) Select Mn( COMM ( Max{ R PR}, A{ R PR} j)) to nject Max{ Md( Vs )} else Select Max{ R PR} to nject Max{ Md( Vs )} Fgure 4. Dynamc Dependence Injecton. After the dependence njecton, the smulaton engne mports parameters and nvokes smulaton executon. V. AN ILLUSTRATION EXAMPLE The prototype system s manly composed of control, multbody dynamcs and hydraulc models, and a varety of tools, such as MATLAB, ADAMS and EASY5, etc.. The users through the portal, whch provded by vrtualzaton-based smulaton grd, dynamcally constructs the smulaton applcatons to carry out varous smulaton problem solvng tasks. In vrtualzaton-based applcaton system, the smulaton model servces and software tools are encapsulated based on resource vrtualzaton technology and deployed dynamcally n the dstrbuted computng envronment (ncludng hghperformance computer cluster).all encapsulated resource the platform can generate one or more nstance for user who apples for usng t. So, even the applcaton number ncreases, the entty resources number s not more than the statc couplng way. And, the njecton way can make the resource usage more flexble and effcent. Users can do smulaton task many tmes to complete the optmzed desgn of vrtual prototype system. 400

6 The Fg.5 shows resource number comparson between statc couplng schedulng and dynamc dependence njecton. vrtualzaton mgraton technology to mprove the exstng smulaton self-adapt mgraton mechansm. ACKNOWLEDGMENT Ths paper s supported by Natonal Defense Key Lab, and authors should lke to express the sncere thanks to all colleagues for ther help and valuable contrbuton. REFERENCES Fgure 5. Entty Resource Number Comparson The njecton schedulng mode also has a good load balance performance. In the Fg.6, the DOS console vew shows the vrtualzaton resource capablty sequence, the system selects vm90, vm9, vm92, vm233 and vm234 as smulaton nodes to nject, whch has the comparatvely low load. Fgure 6. Schedulng Executon of Prototype System By the vrtualzaton technology, the smulaton applcaton dose not need to consder the physcal envronment, t gets the full and dynamc sharng of resources. So, as compared to the tradtonal mplementaton, the development costs can be reduced by 30%, especally wth compute-ntensve ncreasng. VI. CONCLUSION A vrtualzaton-based schedulng mechansm s proposed and key ssues are addressed. Accordng to the smulaton applcaton requrements, t ntroduces the vrtualzaton technology to extend smulaton resource schedulng pattern, and develop a transparent, effcent, customzaton operaton dynamc dependence njecton mode. Moreover, t smplfes the smulaton complexty and mproves the effcency utlzaton of smulaton resources and smulaton operaton. It was appled n some applcatons and proved ts effectveness verfcaton. Future work wll look nto adoptng the [] KATARZYNA Z, AL FREDO T R and ZHAO Zhmng, Grd servces for HLA - based dstrbuted smulaton frameworks, Proceedng of European Across Grds Conference. Santago de Compostela, Span: Sprnger - Verlag, 2003,pp [2] Georgos, Theodoropoulos. DS - grd: large scale dstrbuted smulaton on the grd e-scence sster project, 2006, research/ project s/dsgrd/. [3] PEARLMAN L, NEES grd, 2006, system. php. [4] Magnetar Games,Federaton grd, 2006, [5] LI Bohu, CHAI Xudong and DI Yanqang, Research on Servce Orented Smulaton Grd, the Proceedngs of ISADS, Chna, 2005, pp [6] Bo Hu L, Xudong Cha and Baocun Hou, Research and Applcaton on CoSm (Collaboratve Smulaton) Grd, Proceedngs of MS- MTSA2006,Alberta, Canada, 2006, pp [7] Strachey C, Tme Sharng n Large Fast Computers, Proceedngs of the Internatonal Conference on Informaton Processng,UNESCO, June 959. [8] Lda Zou, Fang-a Lu and Yan Ma, Grd Servce Schedulng Algorthm Based on Margnal Prncple Seventh Internatonal Conference on Grd an Cooperatve Computng, Oct. 2008,pp [9] Toward Botnet Mesocosms, 2007, hothosts07/tech/full_papers/barford/barford.pdf. [0] Saler R, Jaeger T and Valdez E, Buldng a MAC-based Securty Achtecture for the Xen Opensource Hypervsor, IBM Research Report RC23629,2005. [] R. Chandra, N. Zeldovch, C. Sapuntzaks and M. S. Lam, The Collectve: A Cache-Based System Management Archtecture, In Proceedngs of the Second Symposum on Networked Systems Desgn and Implementaton (NSDI 2005), May, 2005,pp [2] S. A. Herrod (VMware), The Future of Vrtualzaton Technology, Keynotes of ISCA 2006, /docs/herrod-keynote.pdf. [3] Hanbng Lu, Hongy Su and Shouy Zhan, Research and Applcaton for Dstrbuted Fle Management System Base on Web n the Dstrbuted Mltary Orented Vrtual Envronment, Systems Engneerng and Electroncs, vol. 3,2009. [4] Hanbng Lu, Hongy Su and Xudong Ca, Study on Model Resource Semantc-based Dynamc Dscovery n Mltary Orented Smulaton Grd, Proceedngs of the th Internatonal Conference on Computer Supported Cooperatve Work n Desgn, Aprl 2008, pp [5] R. Akkraju, R.Goodwn and P.Dosh, A Method for Semantcally Enhancng the Servce Dscovery Capabltes of UDDI, Proceedngs of IJCAI Informaton Integraton on the Web Workshop, Acapulco, Mexco, August 2003,pp [6] Yyou Dong, Janhua Yang and Zhaohu Wu, ODSG: An Archtecture of Ontology-based Dstrbuted Smulaton on Grd, In Proceedngs of the Frst IEEE Internatonal Mult-Symposums on Computer and Computatonal Scence (IMSCCS 06 ),Vol., pp ,june [7] GT 4.0: Informaton Servces, 2006, /docs/4.0/nfo/ 40