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Naveen G.
Naveen G. Balani, Mumbai IN
| Patent application number | Description | Published |
|---|---|---|
| 20110231525 | CONFIGURING CLOUD RESOURCES - A computer implemented method, system and/or program product configure cloud resources. A request is received for a specific set of cloud resources. The set of cloud resources comprises at least one cloud resource that has been associated with an ontological database. The ontological database defines descriptive terms for the cloud resource and describes relationships between the descriptive terms used by different cloud resources. An optimal set of cloud resources that satisfies the request is configured and saved for future usage in responding to requests for the specific set of cloud resources. | 09-22-2011 |
Naveen G. Balani, Kandivali IN
| Patent application number | Description | Published |
|---|---|---|
| 20110307523 | CONFIGURING CLOUD RESOURCES - A method, system, and program product for identifying cloud resources are provided, and further a method, system, and program product for configuring cloud resources are provided. The method for identifying cloud resources may include receiving a request with respect to at least one resource in a cloud and determining a set of resources among the at least one resource in the cloud in accordance with the received request. Determining the set of resources may include consulting an ontology including metadata associated with the at least one resource in the cloud and computing the set of resources based on the metadata and the received request. Additionally, the method may include computing a cost factor with respect to the determined set of resources. Furthermore, the method may include rendering, in response to the received request, the determined set of resources and the cost factor with respect to the determined set of resources. | 12-15-2011 |
Naveen G. Yeri, Charlotte, NC US
| Patent application number | Description | Published |
|---|---|---|
| 20090063361 | Risk and Reward Assessment Mechanism - A data driven and forward looking risk and reward appetite methodology for consumer and small business is described. The methodology includes customer segmentation to create pools of homogeneous assets in terms of revenue and loss characteristics, forward looking simulation to forecast expected values and volatilities of revenue and loss, and risk and reward optimization of the portfolio. One methodology used for modeling revenue and loss is a generalized additive effect decomposition model to fit historical data. Based on the model, a segmentation procedure is performed, which allows for creation of groups of customers with similar revenue and loss characteristics. An estimation procedure for the model is developed and a simulation strategy to forecast and simulate revenue and loss volatility is developed. Efficient frontier curves of risk (e.g., return volatility) and reward (e.g., expected return) are created for the current portfolio under various economic scenarios. | 03-05-2009 |
| 20100293107 | Risk and Reward Assessment Mechanism - A data driven and forward looking risk and reward appetite methodology for consumer and small business is described. The methodology includes customer segmentation to create pools of homogeneous assets in terms of revenue and loss characteristics, forward looking simulation to forecast expected values and volatilities of revenue and loss, and risk and reward optimization of the portfolio. One methodology used for modeling revenue and loss is a generalized additive effect decomposition model to fit historical data. Based on the model, a segmentation procedure is performed, which allows for creation of groups of customers with similar revenue and loss characteristics. An estimation procedure for the model is developed and a simulation strategy to forecast and simulate revenue and loss volatility is developed. Efficient frontier curves of risk (e.g., return volatility) and reward (e.g., expected return) are created for the current portfolio under various economic scenarios. | 11-18-2010 |