Patent application number | Description | Published |
20110213838 | MANAGING AT LEAST ONE COMPUTER NODE - In a system for managing at least one computer node, a first device is configured to perform out-of-band operations in the at least one computing node. The system also includes a second device configured to perform compute-intensive tasks in the at least one computing node and a third device that is external to the at least one computing node configured to perform administration operations for the first device and the second device. | 09-01-2011 |
20110246748 | Managing Sensor and Actuator Data for a Processor and Service Processor Located on a Common Socket - Illustrated is a system and method that includes a processor and service processor co-located on a common socket, the service processor to aggregate data from a distributed network of additional service processors and processors both of which are co-located on an additional common socket. The system and method also includes a first sensor to record the data from the processor. The system and method also includes a second sensor to record the data from a software stack. The system and method further includes a registry to store the data. | 10-06-2011 |
20110301998 | MANAGING A NETWORK SYSTEM - Managing a network system includes determining metrics for a plurality of nodes in the network system, determining a plurality of zones including the plurality of nodes based on the metrics for the network system, and, for each zone of the plurality of zones, determining a computational architecture to be implemented for the zone based on the metrics for each node of the plurality of nodes in the zone. | 12-08-2011 |
20120136909 | CLOUD ANOMALY DETECTION USING NORMALIZATION, BINNING AND ENTROPY DETERMINATION - 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. | 05-31-2012 |
20120239799 | NETWORK SYSTEM MANAGEMENT - 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. | 09-20-2012 |
20130024559 | Automatic Zone-Based Management of a Data Center - Automatic zone-based management of a data center. Nodes are assigned to a first zone. One of the nodes is selected as zone leader. A load ratio of the zone leader is monitored, nodes are identified for shedding if the load ratio exceeds a predetermined maximum, and the identified nodes are assigned to a new zone. One of the nodes in the new zone is selected as zone leader. The load ratio of each zone leader is monitored, nodes are identified for shedding if the load ratio exceeds a predetermined maximum, and the identified nodes are assigned to an additional new zone, the zone leaders negotiate for reassignment of loads. | 01-24-2013 |
20130030761 | STATISTICALLY-BASED ANOMALY DETECTION IN UTILITY CLOUDS - Systems and methods for detecting anomalies in a large scale and cloud datacenter are disclosed. Anomaly detection is performed in an automated, statistical-based manner by using a parametric Gini coefficient technique or a non-parametric Tukey technique. In the parametric Gini coefficient technique, sample data is collected within a look-back window. The sample data is normalized to generate normalized data, which is binned into a plurality of bins defined by bin indices. A Gini coefficient and a threshold are calculated for the look-back window and the Gini coefficient is compared to the threshold to detect an anomaly in the sample data. In the non-parametric Tukey technique, collected sample data is divided into quartiles and compared to adjustable Tukey thresholds to detect anomalies in the sample data. | 01-31-2013 |
20130046904 | MANAGEMENT PROCESSORS, METHODS AND ARTICLES OF MANUFACTURE - Example management processors, methods and articles of manufacture are disclosed. A disclosed example management processor includes a network card interface to communicatively couple the management processor to an operating environment, and a request processor to forward a received external management request to the operating environment via the network card interface, and to combine response information received from the operating environment with response information generated at the management processor. | 02-21-2013 |
20130080375 | ANOMALY DETECTION IN DATA CENTERS - 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. | 03-28-2013 |
20130110761 | SYSTEM AND METHOD FOR RANKING ANOMALIES | 05-02-2013 |
20130111027 | ACCESSING PHYSICAL RESOURCES IN A CLOUD COMPUTING ENVIRONMENT | 05-02-2013 |
20130116975 | Providing Elastic Insight to Information Technology Performance Data - Elastic insight to Information Technology (“IT”) performance data is provided. Local performance data is continuously pushed from a front-end component to a back-end component. Global performance data is continuously pushed from the back-end component to the front-end component. The local performance data and the global performance data are aggregated at the front-end component by product, product family, and product solution. The aggregated data is monitored at the front-end component to identify a performance bottleneck. | 05-09-2013 |
20130227194 | ACTIVE NON-VOLATILE MEMORY POST-PROCESSING - A computing node includes an active Non-Volatile Random Access Memory (NVRAM) component which includes memory and a sub-processor component. The memory is to store data chunks received from a processor core, the data chunks comprising metadata indicating a type of post-processing to be performed on data within the data chunks. The sub-processor component is to perform post-processing of said data chunks based on said metadata. | 08-29-2013 |
20130246731 | DISTRIBUTED GRAPH STORAGE SYSTEM - In a method of implementing a graph storage system, the graph storage system is stored on a plurality of computing systems. A global address space is provided for distributed graph storage. The global address space is managed with graph allocators, in which a graph allocator allocates space from a block of the distributed global memory in order to store a plurality of graphs. | 09-19-2013 |
20140019490 | EVENT PROCESSING FOR GRAPH-STRUCTURED DATA - Examples of the present disclosure may include methods, systems, and computer readable media with executable instructions. An example method for event processing for graph-structured data can include storing graph structured data. The graph structured data includes a plurality of vertex, edge, and/or property graph elements. The example method further includes defining a first graph view of a characteristic of vertex, edge, and/or property graph elements. A subgraph is determined as a subset of the plurality of vertex, edge, and/or property graph elements that have the characteristic of vertex, edge, and/or property graph elements defined by the first graph view. The vertex, edge, and/or property graph elements of the subgraph are processed responsive to a predefined event that occurs on at least one of the vertex, edge, and/or property graph elements of the subgraph. | 01-16-2014 |