Agents and Service-Oriented Computing for Autonomic Computing Prepared by Faisal Sibai for CS 895

Transcription

1 Agents and Service-Oriented Cmputing fr Autnmic Cmputing Prepared by Faisal Sibai fr CS 895 Original paper Frances M. T. Brazier, Jeffrey O. Kephart, H. Van Dyke Parunak, Michael N. Huhns, Agents and Service-Oriented Cmputing fr Autnmic Cmputing: A Research Agenda, IEEE Internet Cmputing, v.13 n.3, p.82-87, May 2009

2 Presentatin Agenda Objective f the paper Sme definitins and clarificatin Autnmic need Similarities between MAS, SOC and Autnmic systems Autnmic in early papers Benefits f Agent and SOC technlgy twards Autnmic cmputing: Individual Agents Multi Agent Systems(MAS) Service-Oriented Cmputing (SOC) Cnclusin and Discussin

3 Primary Objective Explring the relatinship between three paradigms: Autnmic cmputing, Multi-Agent Systems (MAS), and Service-Oriented Cmputing. The paper als presents what current autnmic research lacks and hw Autnmic systems can better benefit frm the previus research in MAS and SOC

4 Definitins Multi Agent Systems (MAS):A system cmpsed f multiple interacting intelligent agents which are used t slve cmplex and difficult prblems which are difficult r impssible fr individual agents t handle. Examples: nline trading, disaster respnse and mdeling structures The agents in a multi-agent system have several imprtant characteristics: Autnmy: the agents are at least partially autnmus Lcal views: n agent has a full glbal view f the system, r the system is t cmplex fr an agent t make practical use f such knwledge Decentralizatin: there is n designated cntrlling agent (r the system is effectively reduced t a mnlithic system) Surce wikipedia:

5 Definitins Individual Agent Systems: Are a smaller implementatin f a multi-agent where usually nly ne agent interacts with the system, s all prcessing is cntained in ne agent and which interacts with a centralized systems Service-Oriented Cmputing(SOC):Design paradigm that specifies the creatin f autmatin lgic in the frm f services. It is a strategic gal in develping Service-riented architecture (SOA) Autnmic cmputing: Self-Cnfiguratin: Cnfiguring themselves autmatically when cmputing resurces are added r remved. Self-Healing: self-repair and fault crrectin peratins. Self-Optimizatin: Mnitring and cntrlling resurces t ensure ptimal functin with respect t defined requirements (SLA) Self-prtectin: Practively identifying and prtecting themselves frm arbitrary r malicius attacks r cascading failures Autnmic systems can achieve this in bth: Infrastructure level: manages prcessing capacity, strage and cmmunicatin bandwidth. Applicatin level: uses the functins the infrastructure level prvides. Surce wikipedia:

6 Why Autnmic systems? Increasing cmplexity in IT envirnments Individual cmpnents f cmputing systems, such as wrklad managers and database management systems, are becming mre difficult t cnfigure, manage, and maintain as each release includes ever mre features and tuning parameters With the advent f service-riented cmputing (SOC), cmputing envirnments have becme pen and distributed, and cmpnents are n lnger under a single rganizatin s cntrl Typical enterprise cmputing envirnment is a hetergeneus, irregular, multivendr pastiche that s difficult t cnfigure, maintain, and truble-sht

7 Similarities Cmmnly cited definitins: Autnmic cmputing: cmputing systems that can manage themselves given high-level bjectives frm administratrs. Sftware agents: an encapsulated cmputer system, situated in sme envirnment and capable f flexible, autnmus actin in that envirnment in rder t meet its design bjectives Individual agents can be identified with autnmic elements: Autnmus Adaptive entities representing resurces r services that act bth reactively and practively Sensing and respnding t the system envirnment and interacting with each ther t satisfy individual gals. They bth mange: Their wn behavir. They interact actins with ther entities t achieve system wide gals. Agent paradigm includes interactins between services and agents Mst autnmic cmputing systems invlve multiple systems, sme f which will be services and mst agent systems invlve multiple agents Treatment f services verlaps with agents and MAS in this paper Analgies amng autnmic cmputing, services, and MAS are strng and bvius yet surveys shw very little ideas and technlgy has been transferred frm MAS and SOC cmmunities. Cmmunicatin failure amng the cmmunities deprives the emerging autnmic cmputing field

8 Early papers - Autnmic Early papers describe autnmic systems: self-management that are strngly agent-riented interacting cllectins f autnmic elements representing self-managing cmpnents such as cmputing resurces Similar t a sftware agent in that it manages its wn behavir by acting n data btained frm its sensrs in accrdance with plicies and agreements established with ther autnmic elements System-level autnmic behavir arises frm interactins amng the autnmic elements MAS behavir arises frm interactins amng individual sftware agents interactins are dynamic and flexible in pattern relatinships amng agents are established via negtiatin and maintained via agreements created during the negtiatin prcess Agreements between agents and service prviders are, in fact, SLAs

9 Individual Agents: Benefits Several technlgies develped fr Individual agents yet nt applied t autnmic cmputing which include: Knwledge and Reasning: Essential capabilities which gvern behavir and interactins with envirnment and ther agents Agents pssesses knwledge f its envirnment and wn abilities and ther agents (fr example metalevel knwledge) Lets the agent determine and reasn abut its wn envirnment which plicies t use Example self-healing: nrmal and abnrmal behavir Reasning can be applied n bth infrastructure and applicatin level. Infrastructure level cnsiders the fllwing : Structure: making sure right cmpnents and general structure are in the right place. Functin: semantics are crrect? Like input, utputs and precnditins are crrect. Behavir: meeting QS and SLA Benefit fr autnmic systems: enables agents t engage the external wrld and d their jb better Planning and Scheduling: Determine a partial rder f actins that have a specific gal ver time. Planners must take several real-wrld issues such as cping with pen envirnments

10 Benefits Benefit fr autnmic systems: present-day planning engines capabilities prvide functinality needed by AC. In additin AC systems must als be able t asses plan executin when plans g awry. Interagent cmmunicatin: Frmal agent cmmunicatin languages and interactin prtcls gvern the cntent and sequence f messages that agents exchange with ne anther. Benefit fr autnmic systems: Messages are relatively simple and inflexible in frm The mapping t the cre applicatin applicatin s functinality is clear-cut With evlutin frm web services t agents their interactins will evlve frm ne-sht messages t extended multi-messages interactins Multiagent Systems (MAS): Transitin many multiagent paradigms and technlgies t autnmic cmputing shuld be straightfrward due t the high similarity. Many issues with multiparty service and resurce negtiatin research has been explred in (MAS). Virtual emergent rganizatins, auctins and brkering are designed fr this purpse.

11 Benefits Has mdeled, explred and implemented multi-level cmmitments between multiple agents, services and rganizatins. Markets and auctins cnstitute majr a majr sub branch f multiagent technlgy. Naïve apprach used in autnmic cmputing t achieve selfmanagement is by the usage f feedback lps which cvers data center s peratins, this fails in an pen envirnment with external services because f its uncntrllable nature. swarm ( intelligence, insect based agents) a mdel which prvides n direct message exchange but by jintly making and sensing changes t a shared envirnment Individual autnmy prttype cmpnents fr agent-like systems have been built but have nt explited agent platfrms such as JADE agent develpment r sme thers. Benefit fr autnmic systems: Risk assessment f glbal system behavir with new cnfiguratins f system cmpnents r services is unexplred In markets and auctins several authrs have explred using such ecnmic mechanisms t allcate resurces, very few f these mechanisms have been used in AC systems Interactin mdels by using MAS mdels wuld better evlve

12 Benefits Service-Oriented Cmputing (SOC): The existence f service-riented architecture (SOA) develpment tls such as the Eclipse enable the design, cnfiguratin, assembly, deplyment, mnitring, and management f sftware designed arund a service riented architecture make it relatively easy fr vendrs t use an incremental apprach t create Web services frm their existing prducts. Tw strategies fr transitining agent cncepts int autnmic cmputing: Services that respnd t requests (www) is an evlutinary step twards a wrld f agents, services acquire agent capabilities. SOA tl emergence suggest at least tw strategies fr creating agent tlkits fr AC usage: Create new agent tlkits similar t SOA tl kits which AC systems can use (Hitiachi s Autnmus Decentralized Cntrl architecture) Add agent functinality and cmmunicatin capabilities prgressively t existing SOA tlkits and enterprise service busses (ESBs). Benefit fr autnmic systems: Mstly reusable tlkits and the use f incremental appraches t create web services frm existing prducts which eliminates creating stuff frm scratch

13 Cnclusin There is a clear value in bringing autnmic systems, MAS and SOC cmmunities tgether. The agent cmmunity has a gd deal f technlgy that s relevant fr autnmic cmputing. Autnmic cmputing has a set f prblems that are imprtant t agent researches Hsting crss cultural wrkshps Invlving the SOA and SOC cmmunity int the autnmic discussin Hlding autnmic cmputing cmpetitin at ne f the main agent r semantic web cnferences