Hewlett-packard Development Company, L.P.

James Christopher Pruyne

Sven Graupner

Akhil Sahai

Keith Farkas

Subramoniam N Iyer

Vijay Machiraju

Sharad Singhal

Vasiliki Kalogeraki

Svend Frolund

Brian J Watson

Kumar Goswami

Murali Krishna Ramanathan

A system includes a goal state repository, a goal state repository instance and management tools. The goal state repository stores goals for a managed system. The goal state repository instance stores a subset of the goals applicable to a current state of the managed system. The goal state repository instance is created by comparing the current state of the managed system to the goals stored in the goal state repository. The management tools modify the managed system to be in compliance with the subset of goals stored in the goal state repository instance.

System management based on goals relevant to a current state of a managed system

In an embodiment, a method of processing a request by a server computer system begins with a step of receiving an object. The object comprises the request, an exception criterion, and a recovery operation. The method continues with a step of determining that the server computer system is unable to fulfill the request due to an exception which meets the exception criterion. The method concludes with a step of applying the recovery operation to resolve the exception. In an embodiment, the server computer system comprises a resource management system for a shared computing environment and the object comprises a resource request object. The resource request object comprises a resource request, the exception criteria, and the recovery operation. The resource request indicates resources requested from the shared computing environment by a start time and for a time period.

Method of processing request by server computer system

Resources in a resource-on-demand system are reserved to support user desktop utility demand. A demand calendar specifies capacities of resources in the resource-on-demand system reserved to support user desktop utility demand for future time periods. A requested capacity is compared to capacities from the demand calendar for a requested future period of time to determine whether resources for the requested capacity are to be reserved.

Reserving resources in a resource-on-demand system for user desktop utility demand

Resources are provisioned in an automated manner for shared services in a resource-on-demand system. A model representing an observed state of resources in the resource-on-demand system allocated to the shared services and a model representing a desired state of the shared services are stored. At least one policy applicable to provisioning the resources for the shared services is determined. The policy and information from the models are applied to automatically provision the resources for satisfying the desired state of the shared services.

Automated model-based provisioning of resources

An automated provisioning system provisions computing resources for shared services in a resource-on-demand system. A number of virtual machines needed for a virtual machine production pool for a period of time to satisfy the computing demand for the shared services is determined from a policy. Also, a number of unassigned virtual machines needed for a virtual machine buffer pool is determined from the policy. Servers and virtual machines are automatically provisioned for the virtual machine production pool and the virtual machine buffer pool based on the determined number of virtual machines needed for the virtual machine production pool, the determined number of unassigned virtual machines needed for the virtual machine buffer pool, and a changing computing demand of the shared services during the period of time.

Automated provisioning of virtual machines for a virtual machine buffer pool and production pool

Resources are provisioned for shared services in a resource-on-demand system. A model representing an observed state of resources in the resource-on-demand system allocated to the shared services and a model representing a desired state of the shared services are stored. At least one policy applicable to provisioning the resources for the shared services is determined. The policy and information from the models are applied to automatically provision the resources for satisfying the desired state of the shared services.

Model-based provisioning of resources

According to an embodiment, a method of managing resources in a shared computing environment begins with a first step of receiving a resource request object from a client. The resource request object requests resources from a resource pool of the shared computing environment for a time period. The method continues with a second step of assigning the resources to the client, thereby forming assigned resources. In a third step, the method sends a resource access handle to the client. The resource access handle provides the client access to the resources by a start time. The method employs a step of tracking the assigned resources and other state information by amendments to the resource request object. According to another embodiment, a system for managing resources in a shared computing environment employs the method.

Resource management for shared computing environment

A computer system and software are provided for customizing on-line computer services. An application is able to interact with a sub-system between which an interceptor system can be interposed. The interceptor system includes a proxy interacting with the application, a customization module interacting with the proxy and a dispatcher interacting with the customization module and interacting with the sub-system. A customization repository contains the customization module and interacts with a service and a client sharing the application and the sub-system. A control interacts with the customization repository and the service for causing customization of the service and the client by disposing the proxy to interact with the application and the dispatcher to interact with the sub-system.

System having customization modules to provide customizations

A service search network system includes a plurality of file search nodes. Each file search node has a file repository that stores files searchable by a file search request. A first and a second service search node is provided, each having a service repository for storing services that can be searched. When the first service search node receives a service search request for a particular service stored in the second service search node, the first service search node formats the service search request into a format recognized by the file search nodes such that the service request can be propagated to the second service search node via some of the file search nodes. The structure of each service search node is also described. A method of searching a specific service in a search network having file search nodes and service search nodes is also described.

Search network for searching services on the internet

Peers (p) monitor responses received from other peers (s, q) to requests for information and rate the responding peers on their ability to provide information of interest. When a responding peer (s) is discovered to frequently provide good results, the requesting peer (p) attempts to move closer to the responding peer (s) by creating a direct connection (p-s) with that peer and thereby promote the 'good' peer to an 'immediate' peer. If such a promotion would result in too many direct connections, the least important immediate peer is demoted to an &#x201c;indirect&#x201d; peer. The criteria (Imp) used for evaluating the relative importance of at least the immediate peers is preferably a time weighted average (Imp*(t)=&#x3b1;&#xb7;Imp(t)+&#x3b2;&#xb7;Imp*(t&#x2212;1)) that also measures consistency and reliability and preferably includes factors not only representative of the peer's ability to provide requested information (Hits), but also of its proximity to the source of that information (1/Hops) so that it can prove that information efficiently. This leads to clusters of peers with similar interests, and in turn reduces the depth of searches typically required to achieve good results.

Growing community of inventors

Naperville, IL, United States of America

James Christopher Pruyne