Hewlett-packard Development Company, L.p.

Vmware, Inc.

Chengwei Wang

Vanish Talwar

Ganesha Shanmuganathan

Anne Holler

Choudur K Lakshminarayan

Krishnamurthy Viswanathan

Chirag Bhatt

Canturk Isci

Parthasarathy Ranganathan

Wade James Satterfield

Partha Ranganathan

Methods and systems for allocating resources in a virtual desktop resource environment are provided. A method includes making a prediction on the future demand for processes running on a distributed environment with several hosts. The prediction is based on the process demand history and includes the removal of historic process demand glitches. Further, the prediction is used to perform a cost and benefit analysis for moving a candidate process from one host to another, and the candidate process is moved to a different host when the cost and benefit analysis recommends such move. In another embodiment, the predictions on future process demand are used for distributed power management by putting hosts in stand-by mode when the overall demand decreases or by adding hosts to the distributed environment when the load increases.

Process demand prediction for distributed power and resource management

Probable anomalies associated with at least one data metric may be detected across a series of windows of time series data by comparison of data to a threshold. An estimated probability of anomalies for each of the windows of time series data may be determined based on the detected probable anomalies and the threshold. The windows of time series data may be ranked based on the estimated probabilities. Probable anomalies associated with highest ranked windows of time series data may be output to a user.

System and method for ranking anomalies

Systems, methods, and machine-readable and executable instructions are provided for network system management. Network system management can include receiving a network system size and a number of system parameters. Network system management can also include receiving a desired monitoring performance and a desired monitoring quality. Furthermore, network system management can include generating a monitoring system topology for a monitoring and analysis system based on the network system size, the number of system parameters, the desired monitoring performance, and the desired monitoring quality.

Network system management

Illustrated is a system and method for anomaly detection in data centers and across utility clouds using an Entropy-based Anomaly Testing (EbAT), the system and method including normalizing sample data through transforming the sample data into a normalized value that is based, in part, on an identified average value for the sample data. Further, the system and method includes binning the normalized value through transforming the normalized value into a binned value that is based, in part, on a predefined value range for a bin such that a bin value, within the predefined value range, exists for the sample data. Additionally, the system and method includes identifying at least one vector value from the binned value. The system and method also includes generating an entropy time series through transforming the at least one vector value into an entropy value to be displayed as part of a look-back window.

Cloud anomaly detection using normalization, binning and entropy determination

Systems and methods of anomaly detection in data centers. An example method may include analyzing time series data for the data center by testing statistical hypotheses. The method may also include constructing upper and lower bounds based on the statistical hypotheses. The method may also include flagging anomalies in the time series data falling outside of the upper and lower bounds.

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Atlanta, GA, United States of America

Chengwei Wang