Patent application number | Description | Published |
20090150717 | AVAILABILITY PREDICTION METHOD FOR HIGH AVAILABILITY CLUSTER - Provided is an availability prediction method for a high availability. The method includes calculating a basic survival probability that the other node survives until a failure on one node of two nodes constituting a cluster is fixed, and determining an optimal number of nodes meeting a preset reference availability probability by calculating an availability probability for a predetermined range of the number of nodes on the basis of the basic survival probability. The method determines the number of nodes in the high availability cluster so as to match a reference availability probability, and is able to accomplish an optimal configuration of a cluster by calculating the availability probabilities for combinations between active node and passive nodes and between head nodes and switches. | 06-11-2009 |
20090150718 | LARGE-SCALE CLUSTER MONITORING SYSTEM, AND METHOD OF AUTOMATICALLY BUILDING/RESTORING THE SAME - Provided are a large-scale cluster monitoring system and a method for automatically building/restoring the same, which can automatically build a large-scale monitoring system and can automatically build a monitoring environment when a failure occurs in nodes. The large-scale cluster monitoring system includes a CM server, a BD server, GM nodes, NA nodes, and a DB agent. The CM server manages nodes in a large-scale cluster system. The DB server stores monitoring information that is state information of nodes in groups. The GM nodes respectively collect the monitoring information that is the state information of the nodes in the corresponding groups to store the collected monitoring information in the DB server. The NA nodes access the CM server to obtain GM node information and respectively collect the state information of the nodes in the corresponding groups to transfer the collected state information to the corresponding GM nodes. The DB agent monitors the monitoring information of the nodes in the groups, which is stored in the DB server, to detect a possible node failure. | 06-11-2009 |
20090158083 | CLUSTER SYSTEM AND METHOD FOR OPERATING THE SAME - Provided are a cluster system, which makes general nodes appear as if they provide seamless services without failure when seen from the outside, and a method for operating the cluster system. The cluster system for operating individual nodes in a distributed management manner includes a board server having a task board registered with a task list, an agent server for managing the task board, and a plurality of general server nodes for performing a corresponding task on the basis of the task list, among which a failed general server node is replaced with another normal general server node. | 06-18-2009 |
20110084969 | METHOD AND APPARATUS FOR OBTAINING MINIMUM COST VECTOR FOR MAKING SKYLINE OBJECT IN MULTI-DIMENSIONAL SPACE - Provided are a method and apparatus for obtaining a minimum cost vector for making a skyline object in a multi-dimensional space. The method includes calculating respective vector values having a query point and respective moving points to which the query point is moved as both end points in a multi-dimensional space having a plurality of coordinate axes, and selecting a vector value whose moving point is included in a skyline and has the minimum distance value from the query point as the minimum vector value from among the vector values. | 04-14-2011 |
20120166630 | DYNAMIC LOAD BALANCING SYSTEM AND METHOD THEREOF - Disclosed is a dynamic load balancing system. The dynamic load balancing system includes a resource management master managing bare servers that do not execute services and having a hierarchical structure and a service master dynamically allocating the bare servers to a load balancing server or a service execution server or dynamically releasing the pre-allocated load balancing server or service execution server by the bare servers, in consideration of monitoring information on a state or performance of a server and service requirements to be provided. | 06-28-2012 |
20130117302 | APPARATUS AND METHOD FOR SEARCHING FOR INDEX-STRUCTURED DATA INCLUDING MEMORY-BASED SUMMARY VECTOR - An apparatus and method for searching for index-structured data including a memory-based summary vector are disclosed. The apparatus for searching for index-structured data including a memory-based summary vector includes a storage unit configured to store a full index and data related to a key; and a key lookup engine configured to include not only a summary vector but also an index storing information related to the full index, search for data stored in the storage unit through the index, and return the searched result. | 05-09-2013 |
20130160006 | APPARATUS AND METHOD FOR CONTROLLING SENSOR DATA IN CLOUD SYSTEM - Disclosed herein is an apparatus for controlling sensor data in a cloud system. The apparatus includes a plurality of virtual machines, and a service module. Each of the plurality of virtual machines obtains sensor information about a user terminal by driving an internal sensor data processing module at a request of the corresponding user terminal, and provides the application execution environment of a requested service by connecting to the user terminal over a network. The service module provides an application corresponding to the requested service to a virtual machine which requested the service. When a sensor Application Programming Interface (API) of the user terminal is called by the application, the virtual machine requests sensor data from the user terminal based on the sensor information about the user terminal, and provides the result of measurement of the sensor data from the user terminal to the corresponding application. | 06-20-2013 |
20140173608 | APPARATUS AND METHOD FOR PREDICTING PERFORMANCE ATTRIBUTABLE TO PARALLELIZATION OF HARDWARE ACCELERATION DEVICES - Disclosed herein are an apparatus and method for predicting performance attributable to the parallelization of hardware acceleration devices. The apparatus includes a setting unit, an operation unit, and a prediction unit. The setting unit divides the time it takes to perform a task into a plurality of task stages and processing stages, and sets one of a parallelization index and target performance. The operation unit calculates the times it takes to perform the stages, and calculates at least one of the ratio of a target parallelization stage in the task and a speed improvement value. The prediction unit calculates an expected performance value or a parallelization index based on at least one of the calculated the times it takes to perform the stages, the calculated ratio of the target parallelization stage, the calculated speed improvement value, and the set target performance. | 06-19-2014 |