International Business Machines Corporation

Google Inc.

Lawrence S Hsiung

Lance Warren Russell

Joseph L Hellerstein

Maheswaran Surendra

Todd W Mummert

Noshir Cavas Wadia

Steven E Froehlich

Mukund Raghavachari

Peng Ye

Edwin Richie Lassettre

David Wiley Coleman

Jai P Menon

Jerald Thomas Schoudt

Jay William Warfield

Shiau-Shiau Pei

Chi-Shen Jane Kohn

Todd William Mummert

Automated or autonomic techniques for managing deployment of one or more resources in a computing environment based on varying workload levels. The automated techniques may comprise predicting a future workload level based on data associated with the computing environment. Then, an estimation is performed to determine whether a current resource deployment is insufficient, sufficient, or overly sufficient to satisfy the future workload level. Then, one or more actions are caused to be taken when the current resource deployment is estimated to be insufficient or overly sufficient to satisfy the future workload level. Actions may comprise resource provisioning, resource tuning and/or admission control.

Managing computing deployment in presence of variable workload

Methods and apparatus for managing computing deployment in presence of variable workload

A method and system for sending rich media. In a preferred embodiment, a document containing rich media is parsed using preset filtering options to determine a subset of the document containing rich media that is intended to be sent to a recipient. The document containing rich media and filtering instructions are then sent to a document server. The filtering instructions instruct the document server as to the identity of the subset of the document containing rich media. The entire document containing rich media is stored on the document server, but only the subset of the rich media is copied and sent to an intended recipient.

Method and system for subsetting rich media in a peer-to-peer model

Growing community of inventors

Los Altos, CA, United States of America

Lawrence S Hsiung