Sabin, Mihaela C.

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University of New HampshireUniversity of New Hampshire Scholars' RepositoryApplied Engineering and Sciences Scholarship Applied Engineering and Sciences1-1-1999Network service management with constrainttechnologyMihaela C. SabinUniversity of New Hampshire, Manchester, mihaela.sabin@unh.eduFollow this and additional works at: https://scholars.unh.edu/unhmcis_facpubThis Article is brought to you for free and open access by the Applied Engineering and Sciences at University of New Hampshire Scholars' Repository.It has been accepted for inclusion in Applied Engineering and Sciences Scholarship by an authorized administrator of University of New HampshireScholars' Repository. For more information, please contact nicole.hentz@unh.edu.Recommended CitationMihaela Sabin and Eugene C Freuder, Network service management with constraint technology, Workshop Notes of AAAI Workshopon Artificial Intelligence for Distributed Information Networking (AiDIN'99), Orlando, FL, 1999, pp. 84-85.Network Service Management with Constraint TechnologyMihaela Sabin and Eugene C. FreuderComputer Science DepartmentUniversity of New Hampshire, Durham, NH 03824mcs,ecf@cs.unh.eduManaging Network ServicesPerformant network management platforms have a dis-tributed architecture of diverse agents, which are highlyspecialized in monitoring connection nodes, communi-cation links, computing systems, and business applica-tions along with their supporting services. However,managing enterprise networks is mainly characterizedby "thresholding" solutions, where device or applica-tion events are monitored, logged, and filtered throughpredefined threshold levels. It seems that the challengeraised by Marshall Rose, author of the Internet man-agement protocol, a few years ago, remains actual (Rose1993), and that there is still a tremendous need for"thinkers", or management tools that can turn "datainto information".Knowledge-based network management systems doaddress this problem by adopting a model-based ap-proach (Hamscher, Console, & de Kleer 1992) for repre-senting and reasoning about management data. Thesesystems maintain not only a structural model of thenetwork topology, but also a behavioral model that cap-tures the relations among network constituents. Model-based network management utilizes expressive models,which dynamically map to, mirror, and respond to themanaged systems (Katker & Paterok 1997), (Dreo dosek & Kaiser 1997).A general, expressive, and yet natural problem-solving model is the constraint satisfaction problem(CSP) (Freuder & Mackworth 1994). The CSP malism has been successfully used to solve a represen-tative range of problems: scheduling, planning, design,configuration, and diagnosis. In this position paper wereport on the results we have obtained from applyingthe constraint satisfaction paradigm to the task of net-work service management. We briefly describe the con-straint technology and illustrate with an example whatmakes this technology suitable to the network servicemanagement task. For a complete presentation of ourconstraint-based approach to modeling and solving net-work service problems we invite the reader to furtherexamine our work as referenced at the end of this paper.Constraint TechnologyConstraint networks have been used to represent anddiagnose special classes of randomly generated circuits(El Fattah & Dechter 1992). (Riese 1993) employsconstraints to model and diagnose communication pro-tocols. In our work, we have extended the problemdomain to encompass management of network services(Sabin, Russell, & Freuder 1997), (Sabin et al. 1999).Our contribution in this application domain includes:(1) modeling network services, (2) detecting and isolat-ing faults with the network services, and (3) proactivediagnosis and explanation support.With our approach, we model the network serviceas a CSP. A CSP contains variables with associateddomains of values, and constraints on some of the vari-ables, which restrict the values the constrained variablescan take. The service measurements are either config-uration settings or on-line parameter values, and theyinstantiate the observed or measured variables. Solvinga CSP is based on searching for value assignments thatsatisfy all the constraints. For the task of fault and con-figuration management, we look for violations of con-straints which explain the observations and indicate theroot causes of faults in the service. Thus, the CSP al-gorithm does not settle for "no solution found", thatis, some constraints were violated. Instead it records asdiagnoses or management results the partial solutionsfor which some constraints are violated.ExampleAs example, we consider diagnosing configuration prob-lems with the Internet Domain Name Service (DNS).Although this example is discussed in (Sabin, Russell,& Freuder 1997), for its CSP representation here weuse a different modeling technique, which draws on aspecial class of CSPs, called composite CSPs (Sabin& Freuder 1996). The composite CSP representationhas the advantage of facilitating modeling of complexsystems by supporting composition, local models, andparameterized relationships or ports. A more detailedapplication of composite CSP to modeling replicationgroupware service can be found in (Sabin et al. 1999).In Figure 1 we show a simplified part of the DNSresolution model. It contains variables (drawn withinAiDIN99 Working Notes84Orlando, Florida, July 1999From: AAAI Technical Report WS-99-03. Compilation copyright © 1999, AAAI (www.aaai.org). All rights reserved. rectangles), composite values (drawn within ovals), one constraint, on variables remoteHost and hosts. Theconstraint asks for the name of the remote host to belisted in the hosts file on the local machine. Let us as-sume that the value observed for the remoteHost vari-able is not in the list of host names of the hosts variable.By failing to check this constraint, the CSP-based con-figuration management tool catches the root cause ofthe problem. Instead of the DNS error message: "XXXhost unknown", the CSP management tool provides acomplete explanation: "Local resolution failed. XXX isnot in the ’hosts’ configuration file".[ DNS Resolution]Figure 1: Composite CSP model of DNS managementMore challenging than developing a CSP engine thatwould perform the diagnosis as shown above is the issueof casting the network management problem into a CSPin the first place. On the same example, we explainnext the modeling capabilities of the composite CSPframework.Composite values can instantiate variables in a CSPthe same way elementary values can. However, whileelementary values are restricted to simple types (nu-meric, string), composite values stand for entire CSPs.Instantiating a variable to a composite value leads todynamically modifying the original CSP with the newsubproblem. In Figure 1 the DNS resolution compositevalue extends the model with variables remoteHost andIocalHost, and the composite value connectionMonitor.The dynamic model’s change through composition isrepresented graphically by an horizontal arc tying to-gether the constituents of the new CSP subproblem.Variable instantiation on the other hand is representedby separate edges branching out from the instantiatedvariable to its possible values. The variable resolution-Type for example can take either the value local or thevalue bind, at which point the model will capture ei-ther local resolution or the much more complex remoteresolution.A direct consequence of composing variables and con-straints into composite values is the modeling capabilityof expressing local models. Local models are context-independent in the sense that they define only con-straints among the variables they contain. To repre-sent how a local model is used in a larger model, newconstraints are defined between some of the local modelvariables and other external variables. The constraintCON in Figure 1 is not part of the local submodel. In-stead, it tells how this local model is used in the largerDNS local resolution model.ConclusionIn this position paper we presented an application ofthe constraint technology to managing network ser-vices. The technology uses an extension to the clas-sic CSP paradigm, called composite CSP, to model andsolve problems with configuring and running networkservices. The composite CSP class captures in a naturalway both the dynamic aspects and complex structurespecific to modeling network services.AcknowledgmentThis material is based upon work supported in partby Candle Corporation, National Science Foundationunder Grant No. IRI-9504316, and Trilogy.ReferencesDreo Rodosek, G., and Kaiser, T. 1997. Determiningthe availability of distributed applications. In Proceed-ings of the Fifth IFIP/IEEE International Symposiumon Integrated Network Management (IM’97).El Fattah, Y., and Dechter, R. 1992. Empirical eval-uation of diagnosis as optimization in constraint net-works. In Working Notes of the Third InternationalWorkshop on Principles of Diagnosis (DX-92).Freuder, E., and Mackworth, A., eds. 1994.Constraint-Based Reasoning. MIT Press.Hamscher, W.; Console, L.; and de Kleer, J., eds.1992. Readings in Model-Based Diagnosis. San Ma-teo, CA" Morgan Kaufmann Publishers.Katker, S., and Paterok, M. 1997. Fault isolationand even correlation for integrated fault management.In Proceedings of the Fifth IFIP/IEEE InternationalSymposium on Integrated Network Management.Riese, M. 1993. Model-based diagnosis of Commu-nication Protocols. Ph.D. Dissertation, Swiss FederalInstitute of Technology, Lausanne.Rose, M. 1993. Challenges in network management.IEEE Network 7(6):16-19.Sabinl D., and Freuder, E. 1996. Composite con-straint satisfaction for configuration. In Freuder, E.,ed., Working Notes of the AAAI’96 Fall Symposium.Sabin, M.; Bakman, A.; Freuder, E.; and Russell, R.1999. A constraint-based approach to fault manage-ment for groupware services. In To appear in the Pro-ceedings of the Sixth IFIP/IEEE International Sym-posium on Integrated Network Management.Sabin, M.; Russell, R.; and Freuder, E. 1997. Gener-ating diagnostic tools for network fault management.In Proceedings of the Fifth IFIP/IEEE InternationalSymposium on Integrated Network Management.AiDIN99 Working Notes , 85 Orlando, Florida, July 1999

Network service management with constraint technology

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Network service management with constraint technology

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