An expert network simulation and design system

Transcription

1 An expert network simulation and design system An expert network simulation and design system Bhavani M. Thuraisingham Bhavani M. Thuraisingham Honey well Inc., Corporate Systems Development Division 1000 Boone Avenue North, Golden Valley, Minnesota Honeywell Inc., Corporate Systems Development Division 1000 Boone Avenue North, Golden Valley, Minnesota ABSTRACT ABSTRACT We describe the essential features of an expert system that helps nonexpert designers analyze and design computer networks. The major components of this expert system are the executive, the knowledge management system, the user interface system, the modeler, the analyzer and the synthesizer. A combination of object-oriented techniques, rules and frames is used to represent the application's descriptive and problem-solving knowledge. Principles of planning systems are used to design a network satisfying the user's requirements. We describe the essential features of an expert system that helps nonexpert designers analyze and design computer networks. The major components of this expert system are the executive, the knowledge management system, the user interface system, the modeler, the analyzer and the synthesizer. A combination of object- oriented techniques, rules and frames is used to represent the application's descriptive and problem -solving knowledge. Principles of planning systems are used to design a network satisfying the user's requirements. 1. INTRODUCTION 1. INTRODUCTION In recent years, the computer network industry has grown at an exponential rate.the complexities of the networks have also increased. Networks are being developed for many critical applications such as BM/C3I and space stations. Building high-performance, efficient, cost-effective, reliable and secure networks is crucial for many of these applications. Consequently, highly skilled network designers are needed to achieve the objectives of the communication industry. Unfortunately the supply of such skilled designers does not meet the demands of the industry. Therefore, it is becoming not only desirable but also necessary to automate the knowledge of these experts so that inexperienced designers can continue with the design of these networks. Expert system technology is the ideal vehicle to automate the knowledge of expert designers. In recent years, the computer network industry has grown at an exponential rate.the complexities of the networks have also increased. Networks are being developed for many critical applications such as BM/C3I and space stations. Building high -performance, efficient, cost -effective, reliable and secure networks is crucial for many of these applications. Consequently, highly skilled network designers are needed to achieve the objectives of the communication industry. Unfortunately the supply of such skilled designers does not meet the demands of the industry. Therefore, it is becoming not only desirable but also necessary to automate the knowledge of these experts so that inexperienced designers can continue with the design of these networks. Expert system technology is the ideal vehicle to automate the knowledge of expert designers. This paper describes our preliminary ideas on a framework for developing an expert network simulation and design software system known as XIMNET. XIMNET was conceived from our earlier work on XIMKON, 1 which is an expert simulation and control program to assist inexperienced control engineers in designing, analyzing and modeling process control systems. Similarly, the goal of XIMNET is to assist inexperienced network designers in modeling, designing and analyzing networks. This goal is achieved by applying a combination of expert system technology and object-oriented techniques. This paper describes our preliminary ideas on a framework for developing an expert network simulation and design software system known as XIMNET. XIMNET was conceived from our earlier work on XIMKON,1 which is an expert simulation and control program to assist inexperienced control engineers in designing, analyzing and modeling process control systems. Similarly, the goal of XIMNET is to assist inexperienced network designers in modeling, designing and analyzing networks. This goal is achieved by applying a combination of expert system technology and object- oriented techniques. Recently much attention has been given to applying artificial intelligence (AI) techniques for solving problems in computer networks.2 Many of the applications have been in the areas of network monitoring and troubleshooting. For example, the ACE system3 is a knowledge-based system that analyzes telephone cables daily. This system does not operate in real time. It analyzes the reports obtained from customers and employees and decides whether preventive maintenance is required and also determines where the rehabilitation should take place. The NTC system3 is a network troubleshooting consultant that provides interpretive analysis of network-related problems. Issues that relate to AI and network planning have been addressed recently.4 The network planning tasks included verifying protocol specifications, applying knowledge to routing tasks to reduce work, and providing expert assistance in Recently much attention has been given to applying artificial intelligence (AI) techniques for solving problems in computer networks.' Many of the applications have been in the areas of network monitoring and troubleshooting. For example, the ACE system3 is a knowledge -based system that analyzes telephone cables daily. This system does not operate in real time. It analyzes the reports obtained from customers and employees and decides whether preventive maintenance is required and also determines where the rehabilitation should take place. The NTC system3 is a network troubleshooting consultant that provides interpretive analysis of network -related problems. Issues that relate to AI and network planning have been addressed recently.' The network planning tasks included verifying protocol specifications, applying knowledge to routing tasks to reduce work, and providing expert assistance in SPIE Vol 1095 Applications of Artificial Intelligence VII (1989) / 735 SPIEVol Applications of Artificial Intelligence VII (1989) / 735

2 analyzing and designing networks. Initially our focus is on the last task; namely, analyzing and designing networks. analyzing and designing networks. Initially our focus is on the last task; namely, analyzing and designing networks. The remainder of this paper will provide an overview of XIMNET and a description of the essential features of its components. The remainder of this paper will provide an overview of XIMNET and a description of the essential features of its components. 2.1, Overview 2.1. Overview 2. XIMNET 2. XIMNET The components of XIMNET are illustrated in Figure 1. The expert executive is the main driving force of XIMNET. It supervises the application of XIMNET commands with the modeling, analysis and synthesis commands. The other major components of XIMNET include the expert process modeler, the expert network designer, the expert network analyzer, the expert database system and the expert user interface. Foreign expert system tools can also be interfaced to XIMNET. For example, such tools could be used to represent the information pertaining to a network topology diagram. This representation could then be used by the expert design and analysis components of XIMNET. Each of the components of XIMNET will be described briefly below. The components of XIMNET are illustrated in Figure 1. The expert executive is the main driving force of XIMNET. It supervises the application of XIMNET commands with the modeling, analysis and synthesis commands. The other major components of XIMNET include the expert process modeler, the expert network designer, the expert network analyzer, the expert database system and the expert user interface. Foreign expert system tools can also be interfaced to XIMNET. For example, such tools could be used to represent the information pertaining to a network topology diagram. This representation could then be used by the expert design and analysis components of XIMNET. Each of the components of XIMNET will be described briefly below. The expert executive accepts user's commands and decides what actions are to be taken. If the commands can be processed directly by the modeling, design and analysis components, the expert executive sends the commands to the appropriate module. If the user's request is to query or update the database, the expert database system is invoked. If the request has to be refined further or if the request is incomplete, the expert user interface component is invoked. The expert executive accepts user's commands and decides what actions are to be taken. If the commands can be processed directly by the modeling, design and analysis components, the expert executive sends the commands to the appropriate module. If the user's request is to query or update the database, the expert database system is invoked. If the request has to be refined further or if the request is incomplete, the expert user interface component is invoked. The expert database system component of XIMNET performs intelligent query processing and updating of the information in the expert database (or knowledge base). The expert database consists of two types of knowledge. One is the information about the various types of networks and the components of these networks. The constraints are also included in this information. The second type of knowledge captures the thought process of the expert; that is, it includes expert heuristics and problem-solving information. The expert database system component of XIMNET performs intelligent query processing and updating of the information in the expert database (or knowledge base). The expert database consists of two types of knowledge. One is the information about the various types of networks and the components of these networks. The constraints are also included in this information. The second type of knowledge captures the thought process of the expert; that is, it includes expert heuristics and problem - solving information. The expert user interface component of XIMNET enables nonexpert designers to use XIMNET. It also helps users to formulate requests if insufficient information is known, handles incomplete requests, and draws graphical representations of the network specifications among others. In the case where users of foreign tools have to use XIMKON, the expert user interface should perform the necessary translations between foreign formats and a format that can be understood by XIMNET. The expert user interface component of XIMNET enables nonexpert designers to use XIMNET. It also helps users to formulate requests if insufficient information is known, handles incomplete requests, and draws graphical representations of the network specifications among others. In the case where users of foreign tools have to use XIMKON, the expert user interface should perform the necessary translations between foreign formats and a format that can be understood by XIMNET. The expert network modeler uses first principles in networks such as theory of graphs to model the structures, equations and parameters of the particular network unit. This expert system has access to XIMNET's knowledge base, from which it obtains all of the application- descriptive information as well as the problem - solving information. The commands to this expert system could come from the user or from the expert designer to verify the designs. The expert network modeler uses first principles in networks such as theory of graphs to model the structures, equations and parameters of the particular network unit. This expert system has access to XIMNET's knowledge base, from which it obtains all of the application-descriptive information as well as the problem-solving information. The commands to this expert system could come from the user or from the expert designer to verify the designs. The expert analyzer analyzes the designs produced either by the designer or the user. The designs are first sent to the network modeler, which will represent the network. The representation is then sent to The expert analyzer analyzes the designs produced either by the designer or the user. The designs are first sent to the network modeler, which will represent the network. The representation is then sent to 736 / SPIE Vol 1095 Applications of Artificial Intelligence VII ( / SPIE Vol Applications of Artificial Intelligence VII (1989)

3 the analyzer, which will either simulate the designs or perform theoretical analysis. The information needed to perform this analysis is stored in the expert database. Appropriate analysis programs are then invoked. the analyzer, which will either simulate the designs or perform theoretical analysis. The information needed to perform this analysis is stored in the expert database. Appropriate analysis programs are then invoked. The expert designer (or expert synthesizer) component of XIMNET is a planning system. The user's specifications for a network are sent to this component in an appropriate format. At the highest level of abstraction is the goal of designing a network. The planner consults the knowledge base for problemsolving information and application-dependent information and generates many intermediate subgoals. Partial plans are sent to the modeler and analyzer to determine whether the user's specifications and constraints are met. Successful plans generated are given to the user. The expert designer (or expert synthesizer) component of XIMNET is a planning system. The user's specifications for a network are sent to this component in an appropriate format. At the highest level of abstraction is the goal of designing a network. The planner consults the knowledge base for problem - solving information and application- dependent information and generates many intermediate subgoals. Partial plans are sent to the modeler and analyzer to determine whether the user's specifications and constraints are met. Successful plans generated are given to the user. Foreign Expert System Tools I Foreign Expert System Tools 1 (The Executive) I The Executive I Knowledge- Based I System J JL Expert User Interface * System i ' ~ I [ Expert I Expert f Expert 1 I I Modeler I Analyzer I I Designer I G G Figure 1. XIMNET Figure 1. XIMNET 2,2. Knowledge representation issues 2.2. Knowledge representation issues The knowledge base (or expert database) of XIMNET includes application-descriptive information and problem-solving information. We have used an object-oriented representation to represent much of the application-descriptive information. This information includes knowledge about various networks and the components of networks. Constraints such as integrity and security specifications are represented by rules. The problem-solving information is represented by a combination of rules and frames. The rules encode the expert's thought process and the frames specify the operator frames used by the planner to generate the design plans. Each type of representation scheme will be described with examples. The knowledge base (or expert database) of XIMNET includes application -descriptive information and problem -solving information. We have used an object -oriented representation to represent much of the application- descriptive information. This information includes knowledge about various networks and the components of networks. Constraints such as integrity and security specifications are represented by rules. The problem- solving information is represented by a combination of rules and frames. The rules encode the expert's thought process and the frames specify the operator frames used by the planner to generate the design plans. Each type of representation scheme will be described with examples An object model. All conceptual entities are modeled as objects in an object-oriented system5. A group of objects with similar properties form a class that is also an object. A class could be a systemdefined class such as a class of integers, reals or boolean values, or it could be a user-defined class such as a class of networks or computers. Associated with each class is a set of instance variables that describe properties of the objects belonging to that class. For example, a class of networks could have An object model. All conceptual entities are modeled as objects in an object -oriented systems. A group of objects with similar properties form a class that is also an object. A class could be a system - defined class such as a class of integers, reals or boolean values, or it could be a user - defined class such as a class of networks or computers. Associated with each class is a set of instance variables that describe properties of the objects belonging to that class. For example, a class of networks could have SPIE Vol 1095 Applications of Artificial Intelligence VII (1989) / 737 SP/EVo/ Applications of Artificial Intelligence VII (1989) / 737

4 the network ID, network name and owner as its instance variables. An instance variable is also an object whose domain is another class. For example, the instance variable network ID is an integer value and will belong to the integer class. A class has methods associated with it. These methods encapsulate the behavior of the objects associated with the class. Methods consist of code that can be executed. A method is executed when an appropriate message is sent to the class. For example, a message may be sent to the class networks to retrieve the name of the network whose ID is the number 100. Two types of hierarchies may be formed. One is the IS-A hierarchy where a class has subclasses associated with it. For example, the class of Systems has the subclasses Mini, Micro and ; that is, Mini is the class of all minicomputers, Micro is the class of all microcomputers, and is the class of all mainframes. The Systems class is the superclass of Mini, Micro and. All of the subclasses of Systems will inherit its instance variables; that is, if system ID is an instance variable of Systems, then Mini, Micro and will all have system ID as an instance variable. In addition, each subclass will have some additional instance variables that will distinguish it from the other subclasses. A class could also be a subclass of more than one superclass. For example, suppose two computer companies, say Cl and C2, market a computer product of type T. Let i 1 and 2 be the products of Cl and C2, respectively. Then the class of all computer products of type T is a subclass of both i 1 and 2 and inherits the instance variables of both superclasses. This is called multiple inheritance. If there is a conflict in such an inheritance, some a priori rule should determine which instance variable to inherit. The second hierarchy is the IS-PART-OF hierarchy. Here an object in a class is considered to be an aggregation of a set of objects, each of which belongs to some class. For example, a network object can be regarded as an aggregation of a set of hosts, a set of connections, a set of network interface units and a set of terminals. A set of hosts is an instance of the set class. A host object that is an instance of the host class is in turn an aggregation of a set of hardware components and a set of software components. Both the IS IS-A and IS-PART-OF hierarchy for the applications under consideration are illustrated in Figure Rules. The rules are used to to represent the constraints and also the expert thought process. The constraints include the integrity and security constraints. The security constraints include constraints of the following form: If the network ID is 100, then the network cannot be accessed by unclassified users. The integrity constraints specify the rules enforced on the networks. For example, there could be a requirement that the maximum distance between two hosts in a network cannot exceed 1000 miles. The problem-solving rules include the heuristics rules, meta-rules among others. For example, there could be a rule which states that the first step in the design process is to plan the topology of the network. Meta-rules are rules that determine which rules should be selected in the event of a choice Frames. Frames are used to to represent the operators used by the planner. The operator frames have the same format as those used in many planning systems such as SPIE.6 SPD3.6 Each operator frame must //SPIEVol Applications of Artificial Intelligence VII (1989)

5 include as a minimum the slots for Operator name, Goal and Preconditions. A sample operator frame is shown below: include as a minimum the slots for Operator name, Goal and Preconditions. A sample operator frame is shown below: Operator Name: Network-Design Goal: Produce a plan to design the network according to the specifications Preconditions: Determine Topology Determine Interconnection media Determine Host Types Determine Network Interface Unit Types Operator Name: Network -Design Goal: Produce a plan to design the network according to the specifications Preconditions: Determine Topology Determine Interconnection media Determine Host Types Determine Network Interface Unit Types Systems Clas s ^^ "l^-*^~-~^ Systems ----"--, Mi crocomputer Microcomputer Minicomputer Minicomputer Companyl ^^ Companyl p=» - -? \. Company2 Company2 a. IS -A Hierarchy i. IS-A Hierarchy I System Instance 1 ^/ 1 Set of Hardware I Components J \ V^ 1 Set of Software I Components J Operating System, Software Component Operating System ] 1 Software Component! ^^ Memory Management J 1 *^ ^^-^^ Process Management Process Management 1 1 Input Output b. IS-PART-OF Hierarchy b. IS- PART -OF Hierarchy G G Figure 2. Hierarchies Figure 2. Hierarchies SPIE Vol Applications of Artificial Intelligence VII (1989) / 739 SPIEVol Applications of Artificial Intelligence VII (1989) / 739

6 23. The planner 2.3. The planner The planner that we propose to use is similar to the one we are using.for XIMKON. This planner has been influenced greatly by the planner developed for control system design.7 The essential features of this planner will be described here. The planner that we propose to use is similar to the one we are using.for XIMKON. This planner has been influenced greatly by the planner developed for control system design.' The essential features of this planner will be described here. Like most planning systems, XIMNET uses a tree data structure. The design starts with the preliminary node, which is the root node of the tree. This node has the ultimate goal attached to it. The first step is to examine the operator frames to determine which of them have this ultimate goal as their goal. If there are none, the rule base is examined as to whether there are any alternatives. To simplify the discussion, we will assume that there are such operators. If there is more than one such operator, then the rule base is examined as to which one is more likely to achieve the goal. If there are rules that will help in this decision, the suggestions are taken. Otherwise, the first operator in the list is tried. The operator is applied to the goal and the preconditions are examined. If there is more than one condition, the rule base is examined to see if there are possible conflicts. Each precondition will correspond to an operator frame or some fact in the database. If a precondition selected does not cause any conflicts, it is generated as one of the subgoals of the ultimate goal. Now the planner has two options: either to expand on this subgoal and recursively generate more subgoals, or to examine another precondition for the ultimate goal. Again the rule base will guide this decision process. As partial plans are generated, the user's specifications are examined to see if the plans are viable. If they are viable, they are committed; if not, some alternative plan should be attempted. The task of testing the plans is performed by the modeler and the analyzer. Once a plan or plans are generated that satisfy the requirements, the problemsolving process ends. Like most planning systems, XIMNET uses a tree data structure. The design starts with the preliminary node, which is the root node of the tree. This node has the ultimate goal attached to it. The first step is to examine the operator frames to determine which of them have this ultimate goal as their goal. If there are none, the rule base is examined as to whether there are any alternatives. To simplify the discussion, we will assume that there are such operators. If there is more than one such operator, then the rule base is examined as to which one is more likely to achieve the goal. If there are rules that will help in this decision, the suggestions are taken. Otherwise, the first operator in the list is tried. The operator is applied to the goal and the preconditions are examined. If there is more than one condition, the rule base is examined to see if there are possible conflicts. Each precondition will correspond to an operator frame or some fact in the database. If a precondition selected does not cause any conflicts, it is generated as one of the subgoals of the ultimate goal. Now the planner has two options: either to expand on this subgoal and recursively generate more subgoals, or to examine another precondition for the ultimate goal. Again the rule base will guide this decision process. As partial plans are generated, the user's specifications are examined to see if the plans are viable. If they are viable, they are committed; if not, some alternative plan should be attempted. The task of testing the plans is performed by the modeler and the analyzer. Once a plan or plans are generated that satisfy the requirements, the problem - solving process ends. 3. CONCLUSIONS 3. CONCLUSIONS In this paper we have described the preliminary design of an expert system that will help nonexpert designers analyze and design computer networks satisfying the user's requirements. The driving force behind this expert system is the executive. The other components of the expert system are the knowledge base management system, the user interface management system, the modeler, the analyzer and the designer. We have used a combination of object-oriented techniques, rules and frames to represent the application-descriptive knowledge and the problem-solving knowledge. The principles of a planning system are used to design a network. In this paper we have described the preliminary design of an expert system that will help nonexpert designers analyze and design computer networks satisfying the user's requirements. The driving force behind this expert system is the executive. The other components of the expert system are the knowledge base management system, the user interface management system, the modeler, the analyzer and the designer. We have used a combination of object- oriented techniques, rules and frames to represent the application -descriptive knowledge and the problem- solving knowledge. The principles of a planning system are used to design a network. Our future plans are to design each component of the expert system in more detail and subsequently implement the design. Many of our ideas have been influenced by the approach taken to design XIMKON,3 which is an expert simulation and control program that helps inexperienced control engineers design and analyze process control systems. Our future plans are to design each component of the expert system in more detail and subsequently implement the design. Many of our ideas have been influenced by the approach taken to design XIMKON,3 which is an expert simulation and control program that helps inexperienced control engineers design and analyze process control systems. 4. ACKNOWLEDGMENTS 4. ACKNOWLEDGMENTS The author wishes to thank Dr. Ferit Konar (who pioneered XIMKON) and Mr. Paul Felix, both of Honey well Inc., for the helpful discussions. The author wishes to thank Dr. Ferit Konar (who pioneered XIMKON) and Mr. Paul Félix, both of Honeywell Inc., for the helpful discussions. 740 / SPIE Vol Applications of Artificial Intelligence VII (1989) 740 / SPIE Vol Applications of Artificial Intelligence VII (1989)

7 5. REFERENCES 5. REFERENCES 1. F. Konar, B.Thuraisingham and P.Felix, "XIMKON - An Expert Simulation and Control Program," presented at the AAAI Conference Workshop on AI in Process Engineering, St. Paul, Minnesota (August 1988). 2. L. Mantelman, "AI Carves Inroads: Network Design, Testing and Management," Data Communications Magazine, pp (July 1986). 3. J. Hannan, "Network Solutions Employing Expert Systems," Proceedings of the IEEE Phoenix Conference on Communications, pp (1987). 4. L. Hiebert, "AI and Network Planning," AI Expert Magazine. 3(9), pp (September 1988). 5. J. Banerjee, H. Chou, J. Garza, W. Kirn, D. Woelk, N. Ballou and H. Kirn, "Data Model Issues for Object-Oriented Applications," ACM Transactions on Office Information Systems, 5(1), pp (1987). 6. D. Wilkins, "Representation in a Domain-Independent Planner," Proceedings of the IJCAI Conference, pp (1983). 7. T. Trankle and L. Markosian, "An Expert System for Control System Design," Proceedings of the IEEE International Conference on Control (1985). 1. F. Konar, B.Thuraisingham and P.Felix, "XIMKON - An Expert Simulation and Control Program," presented at the AAAI Conference Workshop on AI in Process Engineering, St. Paul, Minnesota (August 1988). 2. L. Mantelman, "AI Carves Inroads: Network Design, Testing and Management," Data Communications Magazine, pp (July 1986). 3. J. Hannan, "Network Solutions Employing Expert Systems," Proceedings of the IEEE Phoenix Conference on Communications, pp (1987). 4. L. Hiebert, "AI and Network Planning," AI Expert Magazine, 3(9), pp (September 1988). 5. J. Banerjee, H. Chou, J. Garza, W. Kim, D. Woelk, N. Ballou and H. Kim, "Data Model Issues for Object -Oriented Applications," ACM Transactions on Office Information Systems, 5(1), pp (1987). 6. D. Wilkins, "Representation in a Domain -Independent Planner," Proceedings of the IJCAI Conference, pp (1983). 7. T. Trankle and L. Markosian, "An Expert System for Control System Design," Proceedings of the IEEE International Conference on Control (1985). SP /E Vol 1095 Applications of Artificial Intelligence VII (1989) SPIEVol Applications of Artificial Intelligence VII (1989) / 741