Patent application number | Description | Published |
20110161851 | VISUALIZATION AND CONSOLIDATION OF VIRTUAL MACHINES IN A VIRTUALIZED DATA CENTER - A method for visualizing and simulating server consolidation of different virtual machines in a virtualized data center can include identifying different server computers in a virtualized data center, computing load metrics for each of the server computers, and rendering a graph of the computed load metrics for the server computers in a graphical user interface (GUI) in a host computer. The method further can include selecting a source one of the server computers and also a target one of the server computers and further selecting a virtual machine for prospective migration from the source one of the server computers to the target one of the server computers. Yet further, the method can include further computing prospective load metrics for the source and the target resulting from the prospective migration of the virtual machine to the target. Finally, the method can include displaying in the GUI respective graphs of the prospective load metrics for each of the source and the target. | 06-30-2011 |
20110162069 | SUSPICIOUS NODE DETECTION AND RECOVERY IN MAPREDUCE COMPUTING - Embodiments of the present invention address deficiencies of the art in respect to distributed computing for large data sets on clusters of computers and provide a novel and non-obvious method, system and computer program product for detecting and correcting malicious nodes in a cloud computing environment (e.g., MapReduce computing). In one embodiment of the invention, a computer-implemented method for detecting and correcting malicious nodes in a cloud computing environment can include selecting a task to dispatch to a first worker node, setting a suspicion index threshold for the selected task, determining a suspicion index for the selected task, comparing the suspicion index to the suspicion index threshold and receiving a result from a first worker node. The method further can include applying a recovery action when the suspicion index exceeds the selected suspicion index threshold. | 06-30-2011 |
20120005345 | OPTIMIZED RESOURCE MANAGEMENT FOR MAP/REDUCE COMPUTING - Embodiments of the present invention include a method for resource optimization of map/reduce computing in a computing cluster. The method can include receiving a computational problem for processing in a map/reduce module, subdividing the computational problem into a set of sub-problems and mapping a selection of the sub-problems in the set to respective nodes in a computing cluster, for example a cloud computing cluster, computing for a subset of the nodes in the computing cluster a required resource capacity of the subset of the nodes to process a mapped one of the sub-problems and an existing capacity of the subset of the nodes, and augmenting the existing capacity to an augmented capacity when the required resource capacity exceeds the existing capacity, and when a cost of augmenting the existing capacity to the augmented capacity does not exceed a penalty for breaching a service level agreement (SLA) for the subset of the nodes. | 01-05-2012 |
20120005682 | HOLISTIC TASK SCHEDULING FOR DISTRIBUTED COMPUTING - Embodiments of the present invention provide a method, system and computer program product for holistic task scheduling in a distributed computing environment. In an embodiment of the invention, a method for holistic task scheduling in a distributed computing environment is provided. The method includes selecting a first task for a first job and a second task for a different, second job, both jobs being scheduled for processing within a node a distributed computing environment by a task scheduler executing in memory by at least one processor of a computer. The method also can include comparing an estimated time to complete the first and second jobs. Finally, the first task can be scheduled for processing in the node when the estimated time to complete the second job exceeds the estimated time to complete the first job. Otherwise the second task can be scheduled for processing in the node when the estimated time to complete the first job exceeds the estimated time to complete the second job. | 01-05-2012 |
20120159236 | HOLISTIC TASK SCHEDULING FOR DISTRIBUTED COMPUTING - Embodiments of the invention include a method for fault tolerance management of workers nodes during map/reduce computing in a computing cluster. The method includes subdividing a computational problem into a set of sub-problems, mapping a selection of the sub-problems in the set to respective nodes in the cluster, directing processing of the sub-problems in the respective nodes, and collecting results from completion of processing of the sub-problems. During a first early temporal portion of processing the computational problem, failed nodes are detected and the sub-problems currently being processed by the failed nodes are re-processed. Conversely, during a second later temporal portion of processing the computational problem, sub-problems in nodes not yet completely processed are replicated into other nodes, processing of the replicated sub-problems directed, and the results from completion of processing of sub-problems collected. Finally, duplicate results are removed and remaining results reduced into a result set for the problem. | 06-21-2012 |
20120159627 | SUSPICIOUS NODE DETECTION AND RECOVERY IN MAPREDUCE COMPUTING - Embodiments of the present invention address deficiencies of the art in respect to distributed computing for large data sets on clusters of computers and provide a novel and non-obvious method, system and computer program product for detecting and correcting malicious nodes in a cloud computing environment (e.g., MapReduce computing). In one embodiment of the invention, a computer-implemented method for detecting and correcting malicious nodes in a cloud computing environment can include selecting a task to dispatch to a first worker node, setting a suspicion index threshold for the selected task, determining a suspicion index for the selected task, comparing the suspicion index to the suspicion index threshold and receiving a result from a first worker node. The method further can include applying a recovery action when the suspicion index exceeds the selected suspicion index threshold. | 06-21-2012 |
20120215920 | OPTIMIZED RESOURCE MANAGEMENT FOR MAP/REDUCE COMPUTING - The present invention includes a method for resource optimization of map/reduce computing in a computing cluster. The method can include receiving a computational problem for processing in a map/reduce module, subdividing the computational problem into a set of sub-problems and mapping a selection of the sub-problems in the set to respective nodes in a computing cluster, for example a cloud computing cluster, computing for a subset of the nodes in the computing cluster a required resource capacity of the subset of the nodes to process a mapped one of the sub-problems and an existing capacity of the subset of the nodes, and augmenting the existing capacity to an augmented capacity when the required resource capacity exceeds the existing capacity, and when a cost of augmenting the existing capacity to the augmented capacity does not exceed a penalty for breaching a service level agreement (SLA) for the subset of the nodes. | 08-23-2012 |
20120216203 | HOLISTIC TASK SCHEDULING FOR DISTRIBUTED COMPUTING - Embodiments of the present invention provide a method, system and computer program product for holistic task scheduling in a distributed computing environment. In an embodiment of the invention, a method for holistic task scheduling in a distributed computing environment is provided. The method includes selecting a first task for a first job and a second task for a different, second job, both jobs being scheduled for processing within a node a distributed computing environment by a task scheduler executing in memory by at least one processor of a computer. | 08-23-2012 |