Abstract:
PROBLEM TO BE SOLVED: To provide an information handling system for improving reception. SOLUTION: The system comprises logic for determining a target location for improved communication for a radio communication apparatus based in part on information representing a recent position of the wireless telecommunication unit, wherein the target location is more likely to result in better reception of wireless signals from a wireless access point. The system also includes a transceiver for receiving and transmitting signals to other users of the network. Optionally, the transceiver can be configured for receiving information representing the most recent position of the wireless unit and for transmitting directions to the wireless unit, the directions including information on how to get to the target location. COPYRIGHT: (C)2005,JPO&NCIPI
Abstract:
A method for setting configuration parameters (301) for at least one software system (300), comprises the steps of: a) receiving an identification of a set of configuration parameters (301) for at least one software system (300) to be optimized; b) selecting a random value from a predetermined range (305) for each configuration parameter (301) of interest; c) setting each configuration parameter (301) to a corresponding random value selected (305); d) running an application using the values selected (309); e) gathering performance information relating to the software system (300) while the application is running; f) repeating steps b) through e) for a selected number of times; and g) performing an analysis of the performance information gathered to determine optimal configuration parameters (301). The method can be performed by a programmable computer system (800) running program instructions for carrying out the above method steps or by a specialized apparatus such as an ASIC.
Abstract:
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.
Abstract:
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.
Abstract:
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.
Abstract:
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.
Abstract:
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.