Advanced Micro Devices Corporation

Symantec Corporation

Dell Products Inc.

Ziften Technologies, Inc.

Tamarack Storage Devices

Alfred C Hartmann

J Andrew Lambrecht

Gary Michael Godfrey

Clint H O'Connor

Mark Eric Obrecht

Brendon Woirhaye

Charlotte Chang

Leo Cohen

Christopher Alexander

Scott D Sullivan

Archana S Rajan

Kevin N Pyle

Gary Sabala

Wei Lin

Michael W Little

Keith R Abell

Nick F Alagna

Robert P Myers

Dale E Gulick

Shaun P Cooley

Carey S Nachenberg

Larry David Hewitt

Carl Kittredge Wakeland

Jeffrey Wilhelm

Brian T Witten

Geoffrey S S Strongin

Slava Kritov

Frank X Barajas

Thomas R Ketterhagen

Clint H O'Conner

Gary M Godrey

Techniques are disclosed relating to improving resource usage on a computer system. In one embodiment, a computer system identifies a plurality of processes running on the computer system and determines an importance value and a resource consumption value. In such an embodiment, the importance value is indicative of an importance of an identified process, and the resource consumption value is indicative of a resource consumption of the identified process. The computer system evaluates the importance value and the resource consumption value relative to a usage policy, and takes a corrective action with respect to the identified process based on the evaluating to reconcile resource consumption with process importance value.

Monitoring computer process resource usage

A system and method are provided for strategic power supply sequencing in a computer system. The system and method includes a plurality of processing resources that process data and a plurality of power supplies that provide power for the processing resources. A power management engine adjusts the power supplies in response to processing resource changes to optimize power consumption. The power management engine brings online power supplies to meet the demand created by bringing online additional processing resources and brings offline power supplies to meet the decreased demand caused by a decrease in the number of processing resources. Also, the power management engine rotates which power supplies operate to take advantage of more efficient power supplies and to extend the lives of the power supplies. The power management engine also adjusts the power supplies in advance based upon predicted demand levels for the computer system.

Methods for power management in a computer system with multiple processing resources and multiple power supplies

Security from malicious attack is provided for a user environment running in a virtualized environment by a virtual security appliance (VSA) running outside of the user environment, but on the same computer system as the user environment. For example, a VSA running in a virtual machine can provide security for a user environment running in a second virtual machine. The separation of the VSA from the user environment enhances the robustness of the VSA against malicious attacks seeking to disable/bypass the protections of the VSA, while avoiding the costs and complexities of a physical security appliance.

Virtual security appliance

A computer-implemented method for creating and synchronizing security metadata for data objects within a synchronized-data network is disclosed. This method may comprise: 1) identifying a data object, 2) determining the trustworthiness of the data object, 3) generating security metadata for the data object that identifies the trustworthiness of the data object, and 4) synchronizing the security metadata within the synchronized-data network. The method may also comprise identifying a need to perform a security operation on the data object to determine the trustworthiness of the data object and then offloading or load balancing the security operation within the synchronized-data network. Corresponding systems and computer-readable media are also disclosed.

Systems and methods for creating and synchronizing security metadata within synchronized-data networks

Quarantine periods longer than anticipated working lifetimes for phishing websites are used to protect users from phishing attacks. A central server or the like receives data indicating user attempts to submit confidential information to websites from a plurality of user computers. The received data is aggregated, and used to track website activity concerning solicitation of confidential information. The central server acquires and maintains current statistical data concerning phishing website lifetimes. The aggregated data concerning attempts by users to submit confidential information to websites and the current statistics concerning phishing website lifetimes are used to determine appropriate quarantine periods for websites, which can be enforced when users try to transmit confidential information to these websites.

Anti-phishing system based on end user data submission quarantine periods for new websites

A computer-implemented method for integrating the management of a temporary email address within an email client application is described. An email client application is provided. A function of the email client application is modified. An attribute is added to the modified function. The attribute is configured to allow the selection of a temporary email address or a non-temporary email address. The selected email address is set as a default email address for the modified function.

Systems and methods for integrating the management of a temporary email address within an email client application

Mitigating a network security threat is disclosed. Information associated with a data protection event is received. The received information is evaluated for an indication of a network security threat. One or more remedial actions are performed if it is determined that a potential threat has been indicated. Optionally, the received information is stored.

Profiling backup activity

A managed node executes one or more applications. The applications utilize the resources of the node. A quality-of-service (QoS) agent on the managed node enforces a QoS policy for the node. The QoS agent characterizes an application's usage of the node's resources and predicts its future usage. The QoS agent analyzes the predicted resource usage in view of the QoS policy and generates a QoS envelope for the application. The QoS envelope specifies a ceiling on the level of resources that can be used by the application. The QoS agent queues and meters usage above the ceiling specified by the QoS envelope. A security module determines variations between predicted and actual resource usage and generates security events if warranted.

Application quality of service envelope

A peer-to-peer storage manager measures availability (liveness) of the various nodes in a peer-to-peer storage pool, and adjusts the storage of data within the pool to meet performance expectations based on this liveness information. Based on node liveness statistics, the peer-to-peer storage manager fine tunes storage up or down to efficiently allocate storage while maintaining service level objectives for retrieval time probabilities. Responsive to node liveness information, the peer-to-peer storage manager can dynamically adjust redundancy and/or determine which nodes on which to store data. The peer-to-peer storage manager can execute these storage modifications using rateless erasure codes that allow highly robust storage with only weakly synchronized directory update protocols.

Adaptive liveness management for robust and efficient peer-to-peer storage

A firewall dynamically adapts to changes in a utility computing system. The utility computing system has multiple nodes that are dynamically provisioned in different roles. The different roles are best served by different security and/or Quality-of-Service (QoS) policies. The firewall selects and applies security and/or QoS policies to a node or group of nodes based on the roles provisioned to the node or group. The firewall detects when the provisioning of a node changes, and dynamically applies a new security and/or QoS policy to the node based on the new provisioning. The firewall thus provides adaptive network-level security and QoS functionality to a utility computing system.

Utility computing firewall

Data center activity traces form a corpus used for machine learning. The data in the corpus are putatively normal but may be tainted with latent anomalies. There is a statistical likelihood that the corpus represents predominately legitimate activity, and this likelihood is exploited to allow for a targeted examination of only the data representing possible anomalous activity. The corpus is separated into clusters having members with like features. The clusters having the fewest members are identified, as these clusters represent potential anomalous activities. These clusters are evaluated to determine whether they represent actual anomalous activities. The data from the clusters representing actual anomalous activities are excluded from the corpus. As a result, the machine learning is more effective and the trained system provides better performance, since latent anomalies are not mistaken for normal activity.

Filtering training data for machine learning

System and method for strategic power supply sequencing in a computer system with multiple processing resources and multiple power supplies

A system and method are provided for strategic power reduction in a computer system. The system and method includes a plurality of processing resources that process data. Associated with the processing resources are a plurality of power supplies that provide power for the processing resources. A resource management engine determines the demand on the computer system and scales the processing resources to conserve and reduce power consumption. The resource management engine brings online additional processing resources to meet additional demand or brings offline or to a lower power state processing resources to meet a decreased demand. In addition, the resource management engine predicts future demand requirements and adjusts the processing resources in advance to meet the predicted demand levels and allows for dynamic adjustment of the processing resources based on current demand events.

System and method for strategic power reduction in a computer system

Growing community of inventors

Round Rock, TX, United States of America

Alfred C Hartmann