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  Policy-based management system with automatic policy selection and creation capabilities by using singular value decomposition techniqueUSPTO Application #: 20070282778Title: Policy-based management system with automatic policy selection and creation capabilities by using singular value decomposition technique Abstract: A statistical approach implementing Singular Value Decomposition (SVD) to a policy-based management system for autonomic and on-demand computing applications. The statistical approach empowers a class of applications that require policies to handle ambiguous conditions and allow the system to “evolve” in response to changing operation and environment conditions. In the system and method providing the statistical approach, observed event-policy associated data, which is represented by an event-policy matrix, is treated as a statistical problem with the assumption that there are some underlying or implicit higher order correlations among events and policies. The SVD approach enables such correlations to be modeled, extracted and modified. From these correlations, recommended policies can be selected or created without exact match of policy conditions. With a feedback mechanism, new knowledge can be acquired as new situations occur and the corresponding policies to manage them are recorded and used to generate new event and policy correlations. Consequently, based on these new correlations, new recommended policies can be derived. (end of abstract) Agent: Scully Scott Murphy & Presser, PC - Garden City, NY, US Inventors: Hoi Y. Chan, David M. Chess, Thomas Y. Kwok, Steve R. White USPTO Applicaton #: 20070282778 - Class: 706 48 (USPTO) The Patent Description & Claims data below is from USPTO Patent Application 20070282778. Brief Patent Description - Full Patent Description - Patent Application Claims
FIELD OF THE INVENTION [0001]The present invention relates generally to on-demand and autonomic computing systems in IT systems and environments generally, including those computing systems that are managed by a policy-based management system. The invention particularly relates to a novel system and method by which policies can be selected or created automatically based on events observed and knowledge learned. This new approach treats the observed event-policy relationship represented by an event-policy matrix as a statistical problem that can be yield results using a Singular Value Decomposition (SVD) technique. DESCRIPTION OF THE PRIOR ART [0002]On demand and autonomic computing, such as described in the reference authored by J. O. Kephart and D. M. Chess entitled "The Vision of Autonomic Computing. IEEE Computer Magazine, January 2003, require policy-based management systems to be responsive to changes in environments and adaptive to new operating conditions. In a typical IT environment, there are thousands of events reporting system faults, status and performance information. New events may also appear due to the on-demand operations, and the occurrences of these events are unpredictable. Traditional policy-based management systems and policy authoring, such as relying entirely on static authoring of "if [condition] then [actions]" rules, become insufficient. New approaches to the design and implementation of policy-based systems have emerged, including goal policies such as described in the references entitled "An AI Perspective on Autonomic Computing Policies", Policies for Distributed Systems, Networks, 2004 by J. O. Kephart and W. E. Walsh, and "A Goal-based Approach to Policy Refinement", Proceedings 5th IEEE Policy Workshop (Policy 2004) by A. K. Bandara, E. C. Lupu, J. Moffett, A. Russo. Other new approaches to the design and implementation of policy-based systems have emerged, including utility functions, and data mining and reinforcement learning such as described in the reference entitled "Reinforcement Learning: A Survey", Journal of Artificial Intelligence Research, Volume 4, 1996 by L. P. Kaelbling, M. Littman, A. Moore. [0003]However, it is the case that none of these approaches provides a systematic way to enable policy-based management system and its policies to be responsive to new and ambiguous situations. [0004]It would be highly desirable to provide a statistical approach to the design and implementation of a policy-based management system by utilizing a mathematical technique called Singular Value Decomposition (SVD). SUMMARY OF THE INVENTION [0005]According to the present invention, there is provided a statistical approach to the design and implementation of a policy-based management system by utilizing a mathematical technique called Singular Value Decomposition (SVD). The SVD technique is closely related to a class of mathematical and statistical techniques, such as eigenvector decomposition, spectral analysis and factor analysis. [0006]Generally, the invention provides a system and method using a statistical approach implementing Singular Value Decomposition (SVD) to a policy-based management system for autonomic and on-demand computing applications. The statistical approach empowers a class of applications that require policies to handle ambiguous conditions and allow the system to "evolve" in response to changing operation and environment conditions. In the system and method providing the statistical approach, observed event-policy associated data, which is represented by an event-policy matrix, is treated as a statistical problem with the assumption that there are some underlying or implicit higher order correlations among events and policies. The SVD approach according to the invention enables such correlations to be modeled, extracted and modified. From these correlations, recommended policies can be selected or created without exact match of policy conditions. With a feedback mechanism, new knowledge can be acquired as new situations occur and the corresponding policies to manage them are recorded and used to generate new event and policy correlations. Consequently, based on these new correlations, new recommended policies can be derived. [0007]Thus, according to one embodiment of the invention, there is provided an adaptive policy-based management system, method and computer program product for computing systems. The adaptive policy-based management system comprises: [0008]a means for representing the occurrences of computer system events and action response policies from computing system resources into a first event-policy data structure; [0009]a means for constructing a second event-policy data structure from the first event-policy data structure, the second event-policy data structure representing an event-policy vector space comprising associative patterns and correlations in the event-policy data; [0010]a means for receiving observed event data set from a computing system resource; [0011]a means for recommending a policy for the observed event data set based on existing policy vectors in the constructed event-policy vector space; and, [0012]a means enabling updating of the first event-policy data structure and the second event-policy data structure representing the event-policy vector space as new observed event data sets are received, thereby increasing accuracy in generating recommended policies as new event knowledge is input. [0013]Further to this embodiment of the invention, the adaptive policy-based management system includes a means for storing received observed data event sets and corresponding action response policies from computing system resources. [0014]Moreover, the adaptive policy-based management system further comprises: [0015]an interface means is provided for enabling a user to review and modify a recommended policy for the observed event data set; and, [0016]a means for executing a recommended policy and determining a policy's effectiveness for managing the observed event data set, wherein the storing means is updated with the received observed data event sets and corresponding modified response policies. [0017]Further to this embodiment, the means for recommending a policy for the observed event data set comprises: a means for constructing a pseudo-policy vector for an observed event set from data in the event-policy vector space; and, a means for determining a recommended policy based on proximity of the pseudo-policy vector and existing policy vectors included in the event-policy vector space. The means for determining a recommended policy comprises means for applying a similarity metric between the pseudo-policy vector and one or more policy vectors. [0018]Preferably, according to the invention, first event-policy data structure comprises an event-policy matrix, and the means for constructing a second event-policy data structure from the first event-policy data structure comprises means for implementing Singular Value Decomposition (SVD)] function on the event-policy matrix. [0019]According to another aspect of the invention, there is provided a method for policy-based management of computing systems, the method comprising: [0020]representing the occurrences of computer system events and action response policies from computing system resources into a first event-policy data structure; [0021]constructing a second event-policy data structure from the first event-policy data structure, the second event-policy data structure representing an event-policy vector space comprising associative patterns and correlations in the event-policy data; Continue reading... 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