7576060
Specification-Enhanced Policies for Automated Management of Changes in IT Systems
Enterprise and grid computing systems are complex and subject to a broad range of changes such as configuration updates, failures, and performance degradations. These changes affect infrastructure elements such as computation and storage nodes, applications, and system management elements such as monitoring infrastructures. Today's best practices in use by system administrators to manage these changes are manual and ad-hoc. In large complex installations, this would lead to high operational costs, broken closed loop automation, and reduced agility. Providing tools and mechanisms to administrators that automate the reaction to these changes is highly desirable and is an active research area. 
 
Policy-based management using Event-Condition-Action (ECA) rules is a well-known approach for such automated change management where management actions are executed when specified event-conditions are observed. In complex systems, the interdependence of components generates multiple events when a single change happens causing multiple rules to be triggered. The order of execution of rule actions determines the system behavior necessitating reasoning about execution order. ECA rules do not contain explicit action specifications needed for reasoning and are therefore unsuited for specifying management rules. 
 
In this paper, we propose a specification-enhanced ECA model called Event-Condition-Precondition-Action-Postcondition (ECPAP) for designing adaptation rules. ECPAP rules contain action specifications in first order predicate logic enabling us to develop reasoning algorithms to determine enforcement order of multiple rules. The enforcement order is represented as a Boolean Interpreted Petri Net workflow. We introduce a new notion called enforcement semantics that provides guarantees about rule ordering. We have built an adaptation framework using ECPAP model and have demonstrated it for automated change management of Ganglia and HP OpenView monitoring systems. The evaluation of the framework illustrates the significance of the ECPAP model and demonstrates its applicability for managing complex IT environments.
2517295
Automated Availability Management Driven by Business Policies
Policy-driven service management helps reduce IT management cost and it keeps the service management aligned with business objectives. While most of the previous research focuses on performance/resource managements, little has been researched in the area of availability management driven by business policies. This is a critically important task in enterprise IT, because a single failure in enterprise IT could cause huge business loss. It is still unclear how we can automate the availability management in a highly dynamic and complex system according to business level objectives for performance and risk attitude/preference. As a consequence, users can not manage the availability/performance ratio to match their risk tolerance. In this paper, we propose a policy-driven approach to automate run-time availability management in IT systems, according to high level availability and performance objectives. We further apply von Neumann-Morgenstern utility theory to deal with users' risk attitude policies, an important class of business policies specific for availability management, and the associated preference structures. Based on the proposed approach, we implement an automated decision engine for availability management. The initial evaluation of the solution illustrates the significance of the policy-driven approach and it demonstrates its applicability for availability management in complex IT environments. This way IT users can customize their availability to the risks tolerable by business objectives.
41090805
Distributed policy specification and enforcement in service-oriented business systems
Service-oriented computing (SOC) and Web services (WS) provide a flexible computing platform for electronic business and commerce. Introducing policy-based computing to service-oriented business systems adds another dimension of flexibility and security. While service composition and re-composition in service-oriented business systems allow major system reconstruction, policy-based computing can better deal with the small and routine changes of business processing. This paper reports our latest research on integrating policy-based computing into service-oriented business system and discusses its feasibility, benefits and cost. Under this research, we designed a policy specification and enforcement language PSEL for specifying system constraints and business rules. We implemented a runtime environment in which a service-oriented business system can be modeled, analyzed, deployed, and executed with policy enforcement. Automated tools have been developed to facilitate the entire development process. The cost of policy-based computing is experimentally evaluated
3264554
An Analytical Piecewise Radial Distortion Model for Precision Camera Calibration
The common approach to radial distortion is by the means of polynomial approximation, which introduces distortion-specific parameters into the camera model and requires estimation of these distortion parameters. The task of estimating radial distortion is to find a radial distortion model that allows easy undistortion as well as satisfactory accuracy. This article presents a new piecewise radial distortion model with easy analytical undistortion formula. The motivation for seeking a piecewise radial distortion model is that, when a camera is resulted in a low quality during manufacturing, the nonlinear radial distortion can be complex. Using low order polynomials to approximate the radial distortion might not be precise enough. In contrast, higher order polynomials suffer from the inverse problem. With the new piecewise radial distortion function, more flexibility is obtained and the radial undistortion can be performed analytically. Experimental results are presented to show that with this new piecewise radial distortion model, better performance can be achieved than using the single function. Further, a comparable performance with the conventional polynomial model using two coefficients can also be accomplished.
8090728
The SAHARA Model for Service Composition across Multiple Providers
Services are capabilities that enable applications and are of crucial importance to pervasive computing in next-generation networks. Service Composition is the construction of complex services from primitive ones; thus enabling rapid and flexible creation of new services. The presence of multiple independent service providers poses new and significant challenges. Managing trust across providers and verifying the performance of the components in composition become essential issues. Adapting the composed service to network and user dynamics by choosing service providers and instances is yet another challenge. In SAHARA, we are developing a comprehensive architecture for the creation, placement, and management of services for composition across independent providers. In this paper, we present a layered reference model for composition based on a classification of different kinds of composition. We then discuss the different overarching mechanisms necessary for the successful deployment of such an architecture through a variety of case-studies involving composition.
40089095
Ray-guided global optimization method for training neural networks
Abstract A novel method for globally searching to find the good minima is proposed in this paper. Starting from a local minimum, the weight space around it is scanned with the process being guided by terrain-independent emanating rays. During the search, starting points for further exploration are identified and used to find corresponding local minima. Based on the correct classification rate (CCR) on the validation data, the best minimum is found.
9555510
Long-Distance Mutual Exclusion for Propositional Planning
The use of mutual exclusion (mutex) has led to significant advances in propositional planning. However, previous mutex can only detect pairs of actions or facts that cannot be arranged at the same time step. In this paper, we introduce a new class of constraints that significantly generalizes mutex and can be efficiently computed. The proposed long-distance mutual exclusion (londex) can capture constraints over actions and facts not only at the same time step but also across multiple steps. Londex provides a powerful and general approach for improving planning efficiency. As an application, we have integrated londex into SATPLAN04, a leading optimal planner. Experimental results show that londex can effectively prune the search space and reduce the planning time. The resulting planner, MaxPlan, has won the First Place Award in the Optimal Track of the 5th International Planning Competition.