Patent application number | Description | Published |
20090064342 | SENSITIVITY-ENABLED ACCESS CONTROL MODEL - Apparatus, methods, and computer program products are disclosed that determine Rights to an entity. The disclosed technology maintains data structures representing a set of entities. These entities include protected-entities and sensitivity-entities. Each of the sensitivity-entities is associated with a respective sensitivity access-control-list. The sensitivity-entities include a first sensitivity-entity that is associated with a first sensitivity-access-control-list. A first protected-entity being one of one or more of the protected-entities associated with the first sensitivity-entity. The technology evaluates Rights to the first protected-entity with respect to the first sensitivity-access-control-list and enables access to the first protected-entity responsive to the Rights evaluation and presents the first protected-entity when access is enabled. | 03-05-2009 |
20090158425 | USER DEFINABLE POLICY FOR GRADUATED AUTHENTICATION BASED ON THE PARTIAL ORDERINGS OF PRINCIPALS - Apparatus, methods, and computer program products are disclosed that determine an actor context of an actor as well as an access environment for an attempted operation responsive to the actor context and a necessary condition. The method also evaluates whether the access environment satisfies the necessary condition and activates a principal responsive to the evaluation and authenticates the actor against the principal. | 06-18-2009 |
20090193499 | METHOD FOR APPLICATION-TO-APPLICATION AUTHENTICATION VIA DELEGATION - Apparatus, methods, and computer program products are disclosed that present a delegated-right to a delegation system by a service-application provisioned with the delegation system. The delegated-right enables the service-application to perform an operation/access on behalf of a delegator-user. The method then attempts to perform the operation/access. | 07-30-2009 |
20140310235 | SEASONAL TRENDING, FORECASTING, ANOMALY DETECTION, AND ENDPOINT PREDICTION OF JAVA HEAP USAGE - Data can be categorized into facts, information, hypothesis, and directives. Activities that generate certain categories of data based on other categories of data through the application of knowledge which can be categorized into classifications, assessments, resolutions, and enactments. Activities can be driven by a Classification-Assessment-Resolution-Enactment (CARE) control engine. The CARE control and these categorizations can be used to enhance a multitude of systems, for example diagnostic system, such as through historical record keeping, machine learning, and automation. Such a diagnostic system can include a system that forecasts computing system failures based on the application of knowledge to system vital signs such as thread or stack segment intensity and memory heap usage. These vital signs are facts that can be classified to produce information such as memory leaks, convoy effects, or other problems. Classification can involve the automatic generation of classes, states, observations, predictions, norms, objectives, and the processing of sample intervals having irregular durations. | 10-16-2014 |
20140324924 | SYSTEM AND METHOD FOR TWO-TIER ADAPTIVE HEAP MANAGEMENT IN A VIRTUAL MACHINE ENVIRONMENT - In accordance with an embodiment, described herein is a system and method for two-tier adaptive heap management (AHM) in a virtual machine environment, such as a Java virtual machine (JVM). In accordance with an embodiment, a two-tier AHM approach recognizes that more virtual machines can be run on a particular host, or the same number of virtual machines can support higher load while minimizing out-of-memory occurrences, swapping, and long old garbage collection pauses, if the heap is divided into tiers, so that a garbage collection policy that minimizes pause time can be used in a first (normal) tier, and a garbage collection policy that favors heap compaction and release of free memory to the host can be used in another (high-heap) tier. | 10-30-2014 |
Patent application number | Description | Published |
20140310714 | PREDICTIVE DIAGNOSIS OF SLA VIOLATIONS IN CLOUD SERVICES BY SEASONAL TRENDING AND FORECASTING WITH THREAD INTENSITY ANALYTICS - Data can be categorized into facts, information, hypothesis, and directives. Activities that generate certain categories of data based on other categories of data through the application of knowledge which can be categorized into classifications, assessments, resolutions, and enactments. Activities can be driven by a Classification-Assessment-Resolution-Enactment (CARE) control engine. The CARE control and these categorizations can be used to enhance a multitude of systems, for example diagnostic system, such as through historical record keeping, machine learning, and automation. Such a diagnostic system can include a system that forecasts computing system failures based on the application of knowledge to system vital signs such as thread or stack segment intensity and memory heap usage. These vital signs are facts that can be classified to produce information such as memory leaks, convoy effects, or other problems. Classification can involve the automatic generation of classes, states, observations, predictions, norms, objectives, and the processing of sample intervals having irregular durations. | 10-16-2014 |