Keywords Agents, Grid Computing, Adaptation, Scalability, Negotiation, Load Balancing.

Transcription

1 Adaptive Negotiation fo Agent-Based Gid Coputing Weiing Shen and Yangsheng Li Integated Manufactuing Technologies Institute National Reseach Council Canada 800 Collip Cicle London, Ontaio, N6G 4X8, Canada Phone: Haada H. Ghenniwa and Chun Wang Dept. of Electical and Copute Engineeing Univesity of Westen Ontaio 1151 Richond Steet London, Ontaio, N6A 5B9,Canada Phone: ABSTRACT The Gid concept has ecently eeged as a vision fo futue netwo based coputing, by enabling sealess integation of coputing systes and clustes, data stoage, specialized netwos and sophisticated analysis and visualization softwae. Intelligent agents can play an ipotant ole in helping achieve the Gid vision. Although agents have been applied to coputing load balancing fo any yeas, attepts to apply intelligent agents in ealizing the Gid vision have been ade by acadeic eseaches duing the past few yeas. Due to the highly heteogeneous and coplex coputing envionents, effective load balancing fo Gid coputing is a vey difficult poble, even though intelligent agents ae used. In this pape we attept to highlight ao challenges in anaging esouces in a Gid coputing envionent and pesent soe of ou ecent wo on adaptive negotiation stategies fo agent-based load balancing and Gid coputing. The poposed appoach is to ipleent ultiple negotiation odels/potocols/stategies that can be selected by the syste autoatically to adapt to coputation needs as well as changing coputing esouce envionent. Keywods Agents, Gid Coputing, Adaptation, Scalability, Negotiation, Load Balancing. 1. INTRODUCTION Allocation of liited coputing esouces in an open envionent to coplete axiu coputation tass is vey coplex and tie consuing. Ideally, eseaches and pactitiones would spend no tie at all deciding which systes to use, whee the data esides fo a paticula application doain, how to igate the data to the point of coputation (o vice vesa). Dispaate coputing esouces eep disciplines statified, so eseaches often end up wasting tie by eplicating wo, and this often esults in wastage of esouce utilization - as a eseache who decides when and whee to un a ob is often not awae of the loads and pioities of all systes. The Gid concept is poposed as a eans to help addess soe of these concens, enabling sealess integation of coputing systes and clustes, data stoage, specialized netwos and sophisticated analysis and visualization softwae. Lie an electical powe gid, the Gid will ai to povide a steady, eliable souce of coputing powe. Intelligent agents can play an ipotant ole in helping achieve the Gid vision. Due to the highly heteogeneous and coplex coputing envionents, effective load balancing fo Gid coputing is a vey difficult poble, even though intelligent agents ae used. This pape pesents soe of ou ecent wo on adaptive negotiation stategies fo agent-based load balancing and Gid coputing. 2. AGENT-BASED GRID COMPUTING AND RELATED WORK Gid Coputing is an exciting buzzwod in the coputing wold today. It is usually defined as the exploitation of a vaied set of netwoed coputing esouces, including lage o sall coputes, PDAs, file seves and gaphics devices. The netwos could be anything fo high speed ATM to wieless o ode connections. Exploiting these connected esouces could, fo exaple, enable lage scale siulations not possible on a single supecopute, aid coputational wo of geogaphically distibuted collaboations, siplify eote use of achines, and enable the new dynaic application scenaios. Although agents have been applied to coputing load balancing fo any yeas, attepts to apply intelligent agents in ealizing the Gid vision have been ade by acadeic eseaches duing the past few yeas. A seies of woshops on Agent-Based Cluste and Gid Coputing wee initiated in 2001 [7] as pat of the IEEE/ACM Intenational Confeence on Cluste Coputing and the Gid. The ost inteesting wo in the liteatue ight be the Agent Gid concept poposed unde the DARPA ISO's Contol of Agent-Based Systes (CoABS) poga [6]. The agent gid is a specific constuct o echanis within that laye fo aing sevices and esouces available. Anothe inteesting exaple is ARMS [1]. Accoding to Cao et al. [1], thee ae two ey challenges that ust be addessed fo Gid coputing: Scalability and Adaptability. Ou poposed appoach descibed below is to addess these two challenges though scalable syste achitectue and adaptive negotiation techniques.

2 3. PROPOSED APPROACH Based on ou pevious eseach esults on agent-based coputing load balancing fo a distibuted ultidisciplinay design optiization (MDO) envionent [4], agent-based anufactuing scheduling [5], as well as agent-based e-maetplace, we have been woing on the developent of adaptive negotiation stategies fo all these siila applications. In this pape, we pesent how this appoach can be applied to coplex Gid coputing envionents. As intoduced in the pevious section, we ae facing two ey challenges fo Gid coputing: scalability and adaptability. In this pape, we popose a five-laye achitectue (Figue 1) to addess the scalability issue. End Uses (Web-Based) Seves Looup Sevices Coputing Resouces Applications Seves Job Agents Diectoy Facilitatos Figue1. Five -Laye Syste Achitectue As shown in Figue 1, the Applications laye contains all inds of softwae applications installed in diffeent coputing esouces (PCs, wostations, HPC clustes, etc.). Each application is to be wapped into a softwae agent. The Coputing Resouces laye contains Resouce Agents. Each esouce agent is used to anage all applications with one coputing esouce which could be a PC, a wostation, o a cluste of coputes, and is esponsible to schedule this coputing esouce. This esouce agent should have nowledge about the hadwae pefoance of this coputing esouce, and all applications installed with it as well as the pefoance of these applications in this paticula hadwae envionent. Casebased leaning echanis will be ipleented in this esouce agent to eep a case histoy fo all local applications. The Looup Sevices laye contains Diectoy Facilitatos o Yellow Page agents. All esouce agents in the Coputing Resouces laye need to egiste with these Diectoy Facilitatos o Yellow Page agents. The (Web-Based) Seves laye includes font-end seves fo end uses (huan uses o othe softwae applications) to subit coputation obs. These seves ae usually ipleented as application seves. When a ob is eceived by the seve, a ob agent will be ceated. This ob agent will be in chage of finding candidate esouce agents though Diectoy Facilitatos, and select a ost suitable negotiation potocol, coodinate the negotiation pocess to finally select esouce agents to do the ob. The ob agent will be dissolved when the ob is finished and the esults ae sent to the end use (the esults ay also be saved in a secue stoage esouce). The ob agent ust be esouce-awae and be able to expess its esouce needs to the syste, and be able to negotiate fo syste esouces. The End Uses laye includes huan end uses o othe softwae applications. The poposed achitectue shaes soe siilaities with existing appoaches, including coecial technologies lie Jini netwo technology ( Howeve, any ipleentation issues ae to be addessed, paticulaly the secuity issue. It is evident that the poposed five-laye achitectue addesses well the scalability issue. As it can be seen in the following section, ou adaptive negotiation appoach is well suited to addess the adaptability issue. 4. NEGOTIATION FRAMEWORK 4.1 Adaptive Negotiation Appoach In the context of agent-based coputing load balancing o Gid coputing, negotiation is used to optiize coputing esouces allocation to coputation obs ove tie. A negotiation potocol contains the basic ules fo the negotiation pocess and the counication. In addition to using a potocol, each agent will develop and use a negotiation stategy appopiate to the poble to be solved. Clealy, negotiation potocols and stategies will be quite diffeent fo diffeent categoies of negotiations. Since negotiation involves exchanges of essages, potocols stuctue what ae called convesations, defining classes of dialogue. The siplest dialogues ae found in contact-net appoaches whee they ae liited to exchanges involving offes, bids, and gants of contact. Moe coplex dialogs ae found in huan types of negotiations, when tying to change othe agent's beliefs. If negotiation potocols goven the exchange of poposals (and pehaps aguents) aong agents, negotiation stategies decide the position of a paticula agent duing the negotiation pocess. In ode to addess the second ey challenge, i.e., adaptability, fo Gid coputing as entioned in the pevious section, we popose to use an adaptive negotiation appoach, i.e., the ob agent is able to select a suitable (optial) negotiation potocol based on the specific coputation needs, available coputing esouces and thei coputing loads. The decision is ade by the ob agent accoding to its nowledge using a case based leaning/easoning echanis, i.e., the ob agent leans negotiation stategies based on

3 pevious expeiences. Each agent involved in the negotiation should be able to adapt to the potocol selected by the ob agent (such infoation is contained in the equest essages, e.g., Call fo Bid essages). By ipleenting this adaptive negotiation appoach, the syste will also be able to adapt to changes in syste state. This is an ipotant poble in Gid coputing in which syste esouce availability ay fluctuate. Such fluctuation ay esult fo connection/disconnection of coputing esouces, huan inteaction/inteuption on the coputes, etc. Once scheduled, the ob agent ust also be notified if the syste state has changed in a way that ipacts the ob (coputation tass) and pehaps ente e-negotiation and e-scheduling. At this point, the ob agent ay need to adapt to a diffeent set of allocated esouces. It should be noted that a esouce agent o a ob agent ight be involved in seveal negotiations of diffeent types at the sae tie, which is usually called cobined negotiation. Cobined negotiation is anothe difficult issue, paticulaly in a ulti-agent syste ipleented with the poposed adaptive negotiation appoach. It is being investigated in ou eseach goup and will be epoted sepaately. 4.2 Negotiation Models We have been investigating vaious negotiation odels/ potocols/stategies fo ou adaptive negotiation faewo. In this pape, we intoduce fou negotiation odels that ae believed to be useful in agent-based coputing load balancing: Contact Net Potocol [2]; Auction Model; Gae Theoy Based Model; and Discete Optial Contol Model Contact Net Potocol A odified Contact Net Potocol (CNP) was the only negotiation potocol ipleented in the fist pototype of ou distibuted MDO envionent [4]. It will also be the ost useful negotiation potocol in ou adaptive negotiation envionent. As entioned in Section 4.1, the negotiation is done though a ob and a selected esouce agents (the selection pocess is done by the ob agent checing with one of the Diectoy Facilitatos with thei looup sevices). In the bidding pocess fo selecting a copute, a cluste, o a goup of coputes/clustes fo the equested coputation tas (one ob agent can have a nube of paallel o sequential coputation tass), afte eceiving the diffeent popositions (bids) fo diffeent esouce agents, the ob agent will select a (o a goup) of esouce agent(s) to pefo the tas accoding to its citeia (e.g., cost citeia o tie constaint) and awad a contact to it. Othe suitable esouces ae not selected to pefo the tas, but ae ecoded as altenatives which ay be contacted (negotiated with) in the futue in the case of unfoeseen situations such as copute failues o any othe tas delays. This will geatly educe the e-negotiation / escheduling tie when such unfoeseen situations happen. The infoation about the altenative coputing esouces will be saved by the ob agent togethe with the infoation about the selected esouces. When the selected esouces cannot pefo the scheduled tass due to unfoeseen situations, the ob agent ay negotiate diectly with altenative esouce agents. The CNP is the default negotiation potocol to be used the cuent pototype syste in case no othe specific potocol is selected Auction Model An auction is a negotiation echanis fo selling indivisible goods (coputation esouces, in ou case) to biddes (application agents). An auction is a one-to-any negotiation, between one selle (esouce agent) and any buyes in which the negotiation is educed into a single vaiable doain, naely pice (e.g., oney). An auction negotiates a utually acceptable solution fo the buye and the selle (it uses aet foces to negotiate a cleaing pice fo the ite). The auction echanis sets out ules fo bidding, and allocates the coputation esouce to a cetain bidde based on its pedefined ule set. The auction liteatue is ich and vaied, and the following is only a bief oveview of fou ao types of auction echaniss. Note that we assue that thee is no futhe penalty to losing the auction (i.e., the losing biddes do not pay anything). 1. English auction: This is the ost coon type of auction. It is an open outcy, ascending auction. The auctionee begins at the selle's esevation pice, and solicits pogessively highe oal bids fo the audience until only one bidde is left. The winne clais the ite, at the pice it last bid. This auction is stategically equivalent to the Vicey auction, and caies the additional benefits that it aes bidde esevation pices publicly nown and is efficient in the sense that it will give the obect to the bidde who values it the ost. 2. Dutch auction: This auction is an open outcy, descending auction. The auctionee begins with a pice too high fo any buye to pay, and pogessively lowes the pice until one bidde calls out, "Mine!" The winne clais the ite, at the pice it bid. This auction, howeve, is not necessaily efficient. 3. Fist-pice, sealed-bid auction: In this auction biddes subit a single, ievocable sealed bid. The bids ae opened siultaneously, and the winne is the highest bidde, who clais the ite at the pice he bid. 4. Vicey auction: In this auction biddes subit a single, ievocable, sealed bid. The bids ae opened siultaneously, and the winne is the highest bidde, who clais the ite at the second-highest bid pice. This auction is stategically equivalent to the English auction. An auction is suited quite well to the autoation of the dynaic esouce allocation poble fo the following easons: The esouce allocation optiization poble can be diectly apped into a single vaiable doain, i.e., pice. The dynaic stuctue of the poble has been natually captued in the ulti-agent syste achitectue and auction

4 echanis; by which the solution is dynaically eege fo the cuent setting of the poble. The ules of the negotiation ae clealy spelled out in the ules of the auction. Softwae agents can be easily designed to follow clea ules. An auction's echanis can be infeence-poof. When an auction is designed popely, neithe the buye no the selle will have an incentive to lie o hide thei stategies (i.e., the Revelation Pinciple). Tae the English auction with no esevation pice as an exaple: The selle announces its stategy: to sell to the highest bidde at the last pice offeed. The selle's ules dictate the buyes' stategies. A ational buye would establish a esevation pice and actively bid up to but not beyond that esevation pice. A ational buye's stategy is public nowledge. The pice negotiation coences with the fist bid; the ite will be sold to the highest bidde at the secondhighest bidde's esevation pice. The stategy is infeence-poof; in fact, it depends on infeence fo its success. If biddes wee not awae of the ule fo deteining the winne, they would not aise the bidding accodingly Gae Theoy Based Model Negotiation aong self-inteested agents has been studied fo the pespective of gae theoy. Ealy eseach wo in this aea was caied out by Rosenschein and Zlotin [3]. In gae theoy, the global outcoe fo the syste is given in a table showing the esults of cobined decisions. Each playe, howeve, aes decisions independently. In case that ob agents ae copeting to get thei obs done o esouce agents ae copeting to do oe coputation tass to ean oe oney (e.g., coputing esouces ae opeated by diffeent coecial sevice povides), Gae theoy based negotiation potocols ay be useful. When a gae theoy based potocol is selected, all agents involved in the negotiation pocess ae self-inteested. To siplify the explanation, we assue only Rosenschein s potocol of altenating offes [3] ae used, individual agent has its own utility function, and they can choose out (withdaw fo the negotiation). Two scenaios can be ipleented: If a esouce agent thins a ob is costly thus against his inteest, it could offe a plan which involves othe agents in the ob befoe it accepts it. If othe agents in the goup do not agee with its offe, they can offe thei plans to shae the esponsibility. Evey agent has its oppotunity to offe a plan. If a plan is accepted by all agents in the goup, the negotiation is teinated and the plan is ipleented. If all agents choose out o no ageeent is eached, the ob ight be siply tuned down, o the ob agent needs to stat a new negotiation pocess using a diffeent potocol. When two o any ob agents ae copeting one o seveal coputing esouces at the sae tie. The ob agents and esouces agents could fo a negotiation goup. They offe thei plans to solve this copetition in tun. The agents ty to achieve an ageeent to wo out a schedule using gae theoy based potocols Discete Optial Contol Model The poposed discete optial contol odel can be consideed as a ind of optiized aet odel. It consists of thee steps: acquiing infoation, aing a decision and announcing a decision. A Maetplace Agent obtains the infoation about elated esouce agents (poduces o pocessos in this case) such as the pice ($ pe hou), tass (custoes) such as the nube of the tass and pefoance obectives. Then the Maetplace Agent chooses a pope algoith to ae a decision based all available infoation and its nowledge. Finally, it poclais the esults to othe elated agents. In this case, we suppose that thee ae pocessos: ( = 1,2,..., ), and n tas T ( i = 1,2,..., n). In ode to ephasize i the pinciple, we pesue: (1) the tass ae independent to each othe; (2) tas T ( i = 1,2,..., n) can be un on pocesso i ( = 1,2,..., ) ; (3) peeptions ae not allowed; (4) the pefoance obective is the load balancing. The dynaic syste odel can be ceated as follow: Dynaic equation: X = X Measue: +1 X 1 = X (1) + B U, ( = 1,2,..., n) Min. Q = 1 n + 1 ( x = 1 = 1 = 1 x ) whee: 1 2 X = x x L x is state of the syste descibing the [ ] T accuulative wo tie vecto of the pocessos befoe the tas T is loaded. The unit vecto 1 2 U = [ u u L u ] T ( R is contol input vecto (decision). = 1 Ω ) 2 P P u efes to the tas T un on the pocesso P, vice vesa. 1 2 B = b e b e L b e stands fo the pocessing tie [ ] 1 atix of the tas on the pocesso 2 T. P. b is the pocessing tie of the tas e T is the vecto which the ow is 1 and othe ows ae 0; ( = 1,2,..., ). The pocessing tie of the tas T on pocesso P usually can be descibed as ( = 1,2,..., n), ( = 1,2,..., ). Q epesents the diffeence of the un tie of each pocesso. This odel is a discete optial contol odel with constaints. b

5 This echanis can be used to get an optial solution when the above-entioned conditions ae et. Foe othe coplex situations, soft coputing techniques (Genetic Algoiths, Neual Netwos, and Fuzzy Logic, etc.) can be cobined with the poposed ethod to siplify the optiization pocess. 5. CONCLUSIONS AND PERSPECTIVES Gid coputing and paticulaly agent-based gid coputing ae new aeas of eseach with any open issues and challenges. Thopson [6] enueates a long list of open issues fo Agent Gid point of view. This pape epots soe of ou ecent wo on adaptive negotiation stategies fo agent-based load balancing and Gid coputing, without consideing any othe elated issues such as volue of data to be tansfeed, netwo bandwidth, taffic, and secuity, etc. We tied to addess the two ey challenges fo Gid coputing, i.e., scalability and adaptability, by applying intelligent agents to coputing esouce anageent o load balancing in Gid coputing envionent. Ou eseach wo is still at a peliinay stage, and any detailed ipleentation issues ae to be investigated. The ao contibutions of this eseach wo include adaptive negotiation and cobined negotiation stategies as well as the discete optial contol odel as a novel negotiation odel. It should be noted that the poposed appoach can be used not only in agent-based Gid coputing envionent, but also in othe siila esouce allocation o scheduling pobles, e.g., agentbased anufactuing scheduling and tanspotation scheduling, as well as agent-based e-maetplace o e-business. 6. REFERENCES [1] Cao, J., Kebyson, D.J. and Nudd, G.R. Pefoance evaluation of an agent-based esouce anageent infastuctue fo gid coputing, in Poceedings of the Fist IEEE/ACM Intenational Syposiu on Cluste Coputing and the Gid, (Bisbane, Austalia, 2001), pp [2] Davis, R., and Sith, R.G. Negotiation as a Metapho fo Distibuted Poble Solving. Atificial Intelligence 20 (1983), [3] Rosenschein, J. S., and Zlotin, G., Rules of Encounte: Designing Conventions fo Autoated Negotiation aong Coputes, (MIT Pess, 1994) [4] Shen, W. and Ghenniwa, H.H., Multidisciplinay Design Optiization: A Faewo fo Technology Integation, in Poceedings of the Fist Intenational Confeence on MDO, (London, ON, Canada, July 2001), pp [5] Shen, W. Distibuted Manufactuing Scheduling Using Intelligent Agents, IEEE Expet / Intelligent Systes, 17(1) (Jan/Feb., 2002), [6] Thopson, C. Chaacteizing the Agent Gid, Technical Repot, Obect Sevices and Consulting, Inc., 1998 [ [7] Woshop on Agent based Cluste and Gid Coputing, 2001,