DISTRIBUTED ALGORITHM FOR MULTI-AGENT ENVIRONMENT

Iteratioal Joural of Iformatio Techology ad Kowledge Maagemet July-December 20, Volume 4, No. 2, pp. 59-525 DISTRIBUTED ALGORITHM FOR MULTI-AGENT ENVIRONMENT Maish Arora & M. Syamala Devi 2 Traditioal algorithms are suitable whe steps of algorithm are to be executed i a sequece ad at a sigle locatio. These algorithms have limitatios, whe used i multi-aget eviromet, where differet agets of sigle applicatio ru o differet odes, thus emphasizig the eed for distributed algorithms. Agets i multi-aget systems perform task idepedetly ad share the result with other agets. This motivates to use distributed algorithm, where tasks of the busiess process are distributed amog agets, so that they ca perform i parallel ad idepedetly. This paper presets a distributed algorithm for multi aget systems with case study of budget allocatio i web-based eviromet. The algorithm is based o heuristic approach. Three agets of systems perform differet tasks of budget allocatio procedure like iformatio gatherig, filterig, evaluatig ad budget allocatio at differet locatios ad timigs. This approach takes advatage of distributig ad parallel computig. Keywords: Distributed Algorithm, JADE, Multi Aget System.. INTRODUCTION Distributed algorithms have advatages over traditioal algorithm i multi aget eviromet where may agets operate i eviromet, gather iformatio from eviromet ad act accordigly. Distributed algorithms are efficiet algorithms as compared to traditioal oes that ru i a particular order. A distributed algorithm is desiged ad implemeted for multi aget eviromet. The aim is to allocate budget to deservig fud seekers whe fuds are limited. Agets of system evaluate the proposals techically ad fiacially ad the fially allocate budget after rakig proposals. The structure of the paper is as follows: sectio 2 briefs the backgroud ad related work. Sectio 3 details the budget allocatio problem. Sectio 4 describes multi aget approach to solve the budget allocatio problem. Sectio 5 defied traditioal algorithm to allocate budget, while sectio 6 describes distributed algorithm for multi aget eviromet. Sectio 7 shows the implemetatio of agets ad algorithm usig aget developmet tools. 2. BACKGROUND AND RELATED WORK A Aget is a autoomous etity, which performs a give task usig iformatio gathered from its eviromet to act i a suitable maer to complete the task successfully. Aget must be able to chage its behavior based o chages occurrig i its eviromet. A Aget has characteristics of reactivity, autoomy, collaborative behavior, DOEACC Society, Chadigarh Cetre, Chadigarh, INDIA 2 Departmet of Computer Sciece ad Applicatio, Pajab Uiversity, Patiala, INDIA E-mail: id_maish@yahoo.com, 2 symala@pu.ac.i commuicatio act, mobility, proactive, adaptability ad iferetial capabilities []. A Multi Aget Systems (MAS) cosist of umber of agets that iteract with oe aother. Agets act o the behalf of users/other agets with differet goals ad motivatio. The Agets i MAS work i a team to achieve commo goal by iteractig with oe aother [2]. Agets perform task as a part of their actios. This could be ay scietific computatio or busiess logic. The steps to be performed are represeted as a algorithm ad implemeted usig aget developmet tool. A algorithm is well-defied computatioal procedure that takes some value as iput ad produces some value or set of values as output. Algorithm is thus a sequece of steps that trasforms iput ito output [3]. Algorithm ca be executed i sequetial, parallel or distributed maer. Sequetial algorithm or traditioal algorithm performs steps i a particular sequece at a sigle hardware locatio. With the evolutio of techologies i the area of multiprocessor system or multi taskig capabilities i a sigle processor, the focus of researchers moved from traditioal approach to parallel or distributed algorithm. If traditioal algorithms are executed i multiprocessor computers or etworked computers, these computers would be uderutilized. Moreover, majority of the busiess processes have some tasks that ca be performed idepedetly. Executig such algorithms over etworked machies, multiprocessor machies or sigle processor capable of multitaskig is cost ieffective i terms of CPU utilizatio. Distributed algorithm is desiged to ru o multiple computatioal odes. Nodes could be computer coected i etwork, a process or a thread. Node carries out a task or part of the algorithm ad commuicates with others by passig messages. Differet odes perform differet tasks

520 MANISH ARORA & M. SYAMALA DEVI of the same algorithm at the same time. Distributed algorithms have advatage of iheret parallelism ad scalability. Node, executig a part of algorithm, has limited iformatio about what the other odes, executig other parts of same algorithm, have iformatio with them. A fully decetralized algorithm provides a atural path for parallelism [4]. Oe major challege i desigig distributed algorithm is successful coordiatig behavior i the evet of processor failure or commuicatio lik failure, so these algorithms must be robust eough to hadle such situatios without affectig the overall executio of process. Distributed algorithms are also desiged to exchage iformatio, share resource, icrease reliability, ad icrease performace due to parallelism. These algorithms are suitable for wide rage of applicatio i the area of Telecommuicatio, Distributed Iformatio Processig ad Scietific Computatio. The algorithm of multi-aget systems differs from that of traditioal computatio sciece due to dyamic eviromet. Visualizatio agets, their actio ad behavior ca properly defie the algorithm [5]. Traditioal algorithms are foud usuitable or cost ieffective whe implemeted i multi-aget system due to followig reasos. (i) I multi aget system, differet agets perform differet tasks of the problem idepedetly. (ii) Agets reside o differet machies/odes. (iii) Solutio, i traditioal algorithm, is foud i cetralized, sequetial ad determiistic eviromet while i multi-aget system, solutio is obtaied as result of distributed iteractio of agets. (iv) I case of multi aget system, if traditioal algorithm is used, sequece of evets is very importat ad requires mutual exclusio. I case, a aget, performig oe actio, requires some kid of resources, it has to broadcast request to all the agets operatig i eviromet for the required resource. If aget receives, clear sigal from every aget oly the it ca use the resource. If ay other participatig aget declies the resource, requestig aget will have to wait. Failure i coectio or commuicatio liks durig this process leads to delay i executig the process or algorithm. May owadays applicatios are based o distributed computatio; it may be readig email or browsig Iteret etc. Some form of distributed computig is ivolved, ragig from simple cliet server computig to grid computig. I web applicatio, server process keeps providig iformatio to other cliet processes, eve if, some of them fail or get discoected. Web image retrieval usig multi-aget techology uses distributed algorithm, where agets searches the images with characteristics like color ad shape stored o differet locatios. Images are grouped together ad mobile aget searches from these groups. The images are raked accordig to similarities i features ad are show to cliet [6]. Distributed algorithms are beig used i various multi aget systems like schedulig, productio ad risk allocatios [7-0] Based o backgroud, it is observed that i multi aget applicatio, busiess logic ca be depicted as distributed algorithm ad implemeted accordigly. The parts of algorithms are executed by agets o differet odes. O similar lies, a distributed algorithm has bee desiged to allocate budget to deservig fud seekers ad implemeted for multi-aget budget allocatio problem i web based eviromet. 3. BUDGET ALLOCATION PROBLEM Budget allocatio problem occurs whe limited fuds are to be allocated to most deservig ad competet fud seekers. These fuds are allocated to fud seekers to execute their projects. I Idia, lots of fuds are allocated i various areas like educatio, research & developmet ad social orieted schemes. Fuds seekers submit project proposals ad these proposals are filtered accordig to criteria set by fud allocator. The proposals are the evaluated techically ad fiacially. Both quatifiable ad o-quatifiable decisio-makig factors are cosidered to rak the projects. Weightage is give to each decisio-makig criterio. After rakig, budget is allocated accordig to availability. Quatificatio of o-quatifiable factors is doe usig heuristic approach ad fuzzy system []. From the review of curret practices ad expert views, five high level decisio makig factors are idetified; Solutio Delivery & Cotributio, Techical, Fiacial, Capacity & Expertise ad Risk Maagemet. 4. MULTI-AGENT BASED BUDGET ALLOCATION Based o the problem metioed above, a multi-aget system for resource (budget) allocatio is desiged that iteracts with users (fud seekers, fud allocator ad reviewer) through web-based iterface. The system has back support of database to share iformatio betwee agets eve if, agets are off lie due to some reaso. Three agets have bee desiged based o requiremets of actios, resposibilities ad autoomy. The Fig. shows the model of complete web based budget allocatio system usig multi-aget techology amed as Multi Aget System for Resource Allocatio ad Moitorig (MASRAM). () Coordiator Aget Coordiator Aget iteracts with three types of users of MASRAM i.e. Fud Seeker user, Fud Allocator user ad Reviewer guser. Fud Seeker user seeks fuds, Fud

DISTRIBUTED ALGORITHM FOR MULTI-AGENT ENVIRONMENT 52 Allocator user allocates fuds ad moitors the utilizatio while Review user reviews the allocatio. sufficiet fuds are available, all the qualified proposals are give fuds accordig to their eed. I secod case, where fuds are more tha weighted required ad less tha total requiremet, fuds are allocated accordig to weight. I third possibility, fuds are allocated proportioally accordig to weighted requiremet. The steps have bee show i Fig.2. Fig. : Architecture of Budget Allocatio (2) Fud Seeker Aget Fud Seeker Aget receives all the requests set by Coordiator Aget ad act accordigly. This aget iteracts with Coordiator Aget oly. (3) Fud Allocator ad Moitor Aget Fud Allocator ad Moitor Aget i tur evaluates proposal, assigs weights ad allocates suitable fuds based o allocatio procedure. Fud Allocator ad Moitor Aget processes all the requests received from Coordiator Aget. Steps ivolved i budget allocatio are: (i) Iformatio Gatherig Phase: I this phase, required iformatio is gathered from user as iput like complete proposal details, fud available, fuds already allocated ad criteria to qualify for availig fuds. (ii) Filterig Phase: I this phase, proposals are checked agaist the criteria set by allocator. Those proposals are cosidered for allocatios who qualify, remaiig proposals are rejected. (iii) Evaluatig Phase: Filterig phase evaluates proposals with respect to decisio-makig criteria. A umerical value is calculated agaist each criterio. Accumulated assiged values helps i rakig the projects. (iv) Allocatig Phase: Allocatig phase allocates budget based o availability ad rak of the proposal. The allocatio could be zero or 00 percet. Three possibilities are there; oe whe Fig. 2: Budget Allocatio Phases 5. ALGORITHM STEPS This sectio describes all four phases metioed above to allocate budget mathematically. Iformatio gatherig phase is covered i step I. Steps II ad III belog to filterig phase, steps IV ad V detail evaluatig phase ad step VI represets allocatig phase as show i Table. The procedures i table are detailed further. Step I Step II Step III Step IV Step V Step VI Table Traditioal Algorithm Do iitialize()//iitializatio Repeat step III to step VI for p = to m Do match_criteria() //Matchig Criteria Do evaluate() //Evaluatig Proposals Do assig_weight() //Assigig Weights to Proposals Do allocate() //Allocatig Fuds

522 MANISH ARORA & M. SYAMALA DEVI Procedure iitialize() Table 2 Iitializatio Let R = {R, R2, R3 Rm} be set of resources (fuds) for a particular category of fuds. Let Ai, <=i<= be fud seekers requirig fuds. Let Xi,j be the fuds requiremet by ith fud seeker from jth fud category. Let r be umber of Decisio Makig Factors (DMF). Let CMINi, <=i<=r be miimum requiremet for ith criteria. Let Ci,j be the criteria value of ith fud seeker jth criteria. <=i<=, <=j<=r. Let EVALij be evaluatio matrix where <=i<= ad <=j<=r. Let W = {W, W2, W3 W} be set of weight assiged to ith proposal. Let ARi,j be fud allotted matrix to ith fud seeker from jth resource. Let PROJECT_STATUSi stores whether proposal qualified for allocatio or ot. Procedure match_criteria() For i = to for For j = to r If (CMIN j < C i,j the Else if for Table 3 Filterig Procedure Project_status i = Rejected X i, j 0 Procedure evaluate() Begi For i = to For j = to r Project_status i = Qualified Table 4 Evaluatig Procedure If(PROPJECT_STATUS i = QUALIFIED if for for ; do Evaluate_cri(i,j) // calls procedure to evaluate proposals Table 5 Weight Assigmet Procedure Procedure assig_weight() For i = to r For j = to If(PROPJECT_STATUS i = QUALIFIED = K i * /EVAL k,i ; if for for W i = Geometric Mea ( ), <=i<= ad <=j<=r ad PROPJECT_STATUS i = QUALIFIED Procedure do allocate () beig ed Table 6 Fial Allocatio Procedure Xi, j if Rj Xp, j p= Ri, j Wi * Xi, j if Wp * Xp, j Rj Xp, j p= p= Wi * Xi, j Rj Otherwise Wi * Xp, j p= 6. DISTRIBUTED ALGORITHM TO ALLOCATE BUDGET Agets of the system perform actios at differet time ad at differet locatio. The steps metioed i previous sectio cover all the actios performed by agets at differet times ad locatios. Hece it becomes importat that algorithm may be distributed oe. Though agets perform task idepedetly, yet they eed to share iformatio with other agets to accomplish overall goal of the system. Table 8 shows the distributio of tasks of algorithm amog agets. Table 7 Evaluate Procedure Procedure evaluate_cri(i,j) Begi If(j = ) the Fid total umber of core keywords i i th proposal ad let it be kw EVAL i, j Else if (j = 2) the

DISTRIBUTED ALGORITHM FOR MULTI-AGENT ENVIRONMENT 523 Fid total umber cadidates to be traied i i th proposal ad let it be kw EVAL i, j Else if (j = 3) the Fid total umber atioal developmet ad social impact keywords i i th proposal ad let it be kw EVAL i, j Else if (j = 4) the Fid total umber techical used keywords i i th proposal ad let it be kw EVAL i, j Else if (j = 5) the Let tpc be the total projects completed by i th fud seeker Let tpd be the total projects delayed by i th fud seeker Let tp be the total projects hadled by i th fud seeker prob_tpc = tpc/tp prob_tpd = tpd/tp prob_either = (prob_tpc + prob_tpd)-(prob_tpc * prob_tpd) prob_either Else if (j = 6) the Let tb be total budget proposed by i th fud seeker Let tr be total budget required by i th fud seeker tr/tb Else if (j = 7) the // time beig Else if (j = 8) the Let s be sum of ifrastructure available (ifrastructure ID wise) for all the qualified fud seeker ifrastructure available for i th fud seeker Else if (j = 9) the Fid total umber maagemet capability keywords i i th proposal ad let it be kw Else if (j = 0) the Let s be sum of mapower available (Desigatio wise) for all the qualified fud seeker staff(i) mapower available for i th fud seeker Else if (j = ) the - EVAL i,6 Else if (j = 2) the if Aget Fud Seeker Fud Allocator ad Moitor Coordiator Aget Table 8 Tasks Allocatio Steps of Algorithm Step I, II ad III Step IV, V ad VI To iteract with user through web based iterface Agets ca also work i parallel, e.g. Fud Seeker aget ca be busy i gatherig iformatio from Fud Seeker FS while Fud Allocator ad Moitor Aget is may be i evaluatig ad allocatig budget to FS2 ad FS3 fud seekers. Fud Seeker Aget passes the iformatio to Fud Allocator ad Moitor Aget through database support ad well-defied otology [2]. Distributed Algorithm completes the task whe all participatig agets complete their tasks. Step IV of the algorithm is further divided ito multiple tasks eablig us to use multi threadig. There are 2 differet decisio makig factors categorized ito five high level factors as discussed i previous sectio. These are idepedet except 5. as is it depedet o 2.2 (Table 3). The computatios of these factors are multithreaded takig advatage of both parallel ad distributed eviromet. The distributed algorithm is described i table 9. Table 9 Distributed Algorithm // Distributed Algorithm Begi Thread FS_thread Requests aget Fud Seeker Aget to provide fud requiremet from fud seeker user Thread FA_thread Requests aget Fud Allocator ad Moitor Aget to provide takes iformatio from fud seeker aget Do while fud requiremet foud ad budget foud Begi //assig task to Fud Allocator ad Moitor Aget Do iitialize() For I = to m // allocatig categories Create thread t i = budget() // calls budget procedure for Thread_wait //Wait for all the active threads to fiish Table 0 Distributed Algorithm (Allocatio Procedure) //budget procedure do match_criteria() do evaluate_da(i) do assig_weight() do allocate_fuds() ed procedure evaluate_da(i) for j = to r//o. of decisio makig factors create thread t ij =evaluate() // calls evaluate procedure ed for thread_wait // waits for all the active threads to fiish 7. IMPLEMENTATION The above metioed algorithm is implemeted i web based multi aget system for resource allocatio ad moitorig. All the three agets reside o server side. Two servers are used for aget-based applicatio: oe as database

524 MANISH ARORA & M. SYAMALA DEVI server ad secod as aget server. Aget Server hosts all three agets. Three types of users iteract with agets from cliet machie through Graphical User Iterface (GUI). Iterface programs to iteract with the users are implemeted usig JSP (Java Server Pages). Agets are implemeted usig JADE, Java Aget Developmet Framework, a FIPA (Foudatio of Itelliget Physical Agets) compliat framework to develop agets, ad oracle is used as backed database. The iteractio betwee agets ad database is through Java busiess classes [3]. Iformatio gatherig task has bee distributed betwee two agets; Fud Seeker Aget ad Fud Allocator & Moitor Aget. Fud Seeker Aget seeks iformatio from fud seeker user while Fud Allocator & Moitor Aget seeks iformatio from Fud allocator user ad reviewer user. Both store the iformatio i database. Fud Allocator & Moitor Aget from time to time seses the requests to Table Budget Requiremet ad Allocatio allocate fuds ad does the remaiig phases of filterig, evaluatig ad allocatig. To evaluate proposals, separate eleve threads are started oe each for eleve idepedet decisio-makig factors. This is takes advatage of parallelism. Table shows the Budget requiremet ad budget allocatio of three projects i two slots. At first time, Fud Allocator & Moitor Aget fids oly oe proposal ad durig ext slot, it fids two proposals. The proposals are raked after evaluatio ad assigig weights. Project ID 8 is allotted full amout of budget required as it was available, but Project ID 48 ad 6 are allocated proportioately accordig to weight ad rak sice limited fuds are available as show i Table 2 alog with criteria ad fuds available. Project Id Category Allocato r ID Seeker ID Budget Weightag Allocated Slot No. Rak Required e Budget 48 2 2002 720000 53.842 64604 2 6 2002 80000 46.58 553896 2 2 8 2 200 2 300000 00 300000 Table 2 Miimum Criteria Allocatio ID Category Criteria Mi Available 200 - For R & D Mi Experiece of Seeker 3 800000 Already Doe similar projects 2002 2- For quality Educatio Mi Staff Member 5 200000 Mi Experiece of Seeker 0 Already Doe similar projects 2 Table 3 shows the decisio-makig factors ad their weightage i allocatio of budget. Table 4 shows the result of evaluatio of proposals agaist these decisio-makig factors. First proposals are evaluated agaist these factors ad the weightage is give accordig to decisio-makig weights. Table 3 Weightage of Decisio Makig Factors Decisio Makig Id Decisio Makig Factor Decisio Makig Weight. Core Area.038.2 HR Developmet.076.3 Natioal Developmet ad Social Impact.06 2. Available Techology 043 2.2 Success Probability.03 3. Cost Ivolved.22 3.2 ECO Beefit.063 4. Ifrastructure.027 4.2 Maagemet Capability.33 4.3 Staff Experiece.098 5. Project Completio Risk.3 5.2 Implemetatio Risk.06

DISTRIBUTED ALGORITHM FOR MULTI-AGENT ENVIRONMENT 525 Table 4 Calculated Weights Project Id - 48 Project Id - 6 Project Id - 8 Decisio Evaluated Decisio Evaluated Decisio Makig Makig Value Makig Value Makig Value ID ID ID. 0.5. 0.5..2 0.5.2 0.5.2.3 0.5.3 0.5.3 2. 0.5 2. 0.5 2. 2.2 0.455 2.2 0.545 2.2 3. 0.47 3. 0.529 3. 3.2 0.5 3.2 0.5 3.2 4. 0.605 4. 0.395 4. 4.2 0.5 4.2 0.5 4.2 0 4.3 0.723 4.3 0.277 4.3 5. 0.6 5. 0.4 5. 0 5.2 0.635 5.2 0.365 5.2 0 8. CONCLUSION I multi-aget systems, agets perform differet tasks at differet locatios ad time to achieve their idividual goals ad overall goal of the system. Traditioal algorithms to allocate budget were foud usuitable due to their characteristics of orderly executio ad that too at a sigle locatio i multi aget eviromet. The distributed algorithm to allocate budget i multi-aget eviromet removes the limitatio of traditioal algorithms. Parts of the budget allocatio problem were distributed amog two agets. Durig allocatio procedure, further multithreadig is used. This distributed algorithm to allocate budget foud fit for multi aget eviromet. This procedure takes advatage of parallel ad distributig computatio. REFERENCES [] Associatio of Advacemet of Artificial Itelligece, Available at http://www.aaai.org/aitopics/html/multi.html, accessed o April 0, 2007. [2] Jarg Deziger, Multi Aget Systems, Departmet of Computer Sciece, Uiversity of Calgary, Caada, Available at http://pages.cpsc.ucalgary.ca/~dezige/courses/567- witer2006/slides/04-masdef-hadout.pdf, accessed o April, 2007. [3] Thomas H. Corme et al., Itroductio to Algorithm, Secod editio, MIT Press, Cambridge, Massachusetts Lodo, Eglad, 200. [4] Raz Nissim, et al., A Geeral, Fully Distributed Multi-Aget Plaig Algorithm,9 th Iteratioal Coferece o Autoomous Agets ad Multi Aget Systems, AAMAS, Toroto, pp 323-330, 200. [5] Jose M. Vidal et al., The Past ad Future of Multi Aget System, AAMAS Workshop o Teachig Multi-Aget Systems, 2004. [6] Alaa M. Riad, et al., A Itelliget Distributed Algorithm for Efficiet Web Images Retrieval, Iteratioal Joural of Commuicatio, pp 63-76, 2009. [7] Ro Xie, et al, Schedulig Multi-Task Multi Aget Systems, Proceedig o 5 th Iteratioal Coferece o Autoomous Agets, ACM New York, 200 [8] Masahiro Oo, et al, Market Based Risk Allocatio for Multi Aget System, Proceedig o 9 th Iteratioal Coferece o Autoomous Agets ad Multi Aget Systems,, AAMAS 0, 200. [9] Toru Ishida, Parallel, Distributed ad Multi-Aget Productio Systems -A Research Foudatio for Distributed Artificial Itelligece, Proceedigs of the First Iteratioal Coferece o Multi Aget Systems, pp 46-422, 995. [0] Sebastie Paquet et al., Multi-aget Systems Viewed as Distributed Schedulig Systems: Methodology ad Experimets, Advaces i Artificial Itelligece, Lecture Notes i Computer Sciece (Sprigerlik), vol 350, 2005. [] Ji Cheg, Haipig Bai ad Zipig Li, Quatificatio of No Quatitative Idicators of Performace Measuremet, Wireless Commuicatios, Networkig ad Mobile Computig, 2008. WiCOM 08. 4th Iteratioal Coferece, page(s): -5, 2008. [2] Maish Arora, M. Syamala Devi, Otology Based Aget Commuicatio i Resource Allocatio ad Moitorig, IJCSI Iteratioal Joural of Computer Sciece Issues, 7, Issue 6, November 200, ISSN (Olie): 694-084 [3] Maish Arora, M. Syamala Devi, Role of Database i Resource Allocatio Problem, Iteratioal Joural of Computer Sciece ad Iformatio Techology, 2(2),pp 668-672, 20.