Grid computing is the collection of computer resources from multiple locations to reach a common goal. The grid is a special type of distributed system with non-interactive workloads that involve a large number of files. Partitioning of the application program/ software into a number of small groups of modules among dissimilar processors is an important parameter to determine the efficient util...

These spatial clustering methods can be classified into four categories: partitioning method, hierarchical method, density-based method and grid-based method. The grid-based clustering algorithm, which partitions the data space into a finite number of cells to form a grid structure and then performs all clustering operations to group similar spatial objects into classes on this obtained grid st...

Given d-dimensional N data items and a maximum branching factor Bfmax, packing is partitioning Bfmax amount of data and storing it in a disk page. The range query performance of packing is highly dependent on the methods by which data is partitioned. Thus, partitioning data is the main problem tackled in our work. We suggest two extreme cases of partitioning methods: grid-like balanced and onio...

DBSCAN is widely used in various fields, but it requires computational costs similar to those of re-clustering from scratch update clusters when new data inserted. To solve this, we propose an incremental density-based clustering method that rapidly updates by identifying advance regions where cluster will occur. Also, through extensive experiments, show our provides results DBSCAN.

Unstrucutured grids are used frequently in finite element or finite volume analysis. Unlike structured grids which are mostly applicable to finite difference schemes, unstructured grids require a list of the connectivity which specifies the way that a given set of vertices form the individual elements. To implement models that use an unstructured numerical decomposition on a distributed memory ...

A new partitioning method for complex 3-D hybrid prismatic/tetrahedral meshes is presented, The method uses an orthogonal recursive bisection approach on a special octree corresponding to the hybrid grid. The octree is generated automatically and handles any type of 3-D geometry and domain connectivity. It is employed for partitioning of static, as well as dynamic adaptive meshes. The method yi...

Power grid partition is a major problem in power markets based on zonal marginal price (ZMP). As the preparation of modeling, the zone of a node set is defined as the minimum-girthed convex polygon containing these nodes, and a theorem judging common nodes between two zones of node sets is proposed. Then, the power-grid-partitioning problem is described as a combinatorial optimization model, an...

We present a distributed version of IDA* search algorithm for a computational grid. We also propose a grid architecture based on a multi-agent system paradigm applied to mobile devices on a cellular network. The proposed algorithm is specifically designed to adapt to the flexible environment of the grid. In this paper, we discuss several aspects of the distributed IDA* algorithm and the underly...

This paper examines grid-clustering method. Unlike the conventional methods, this method organizes the space surrounding the patterns. It uses a multidimensional grid data structure. The resulting block partitioning of the value space is clustered via a neighbor search. The mathematical description of the algorithms employed is given. Some case studies and ideas how to use the algorithms are de...

We present an eecient method for the partitioning of rectangular domains into equi-area sub-domains of minimum total perimeter. For a variety of applications in parallel computation, this corresponds to a load-balanced distribution of tasks that minimize interprocessor communication. Our method is based on utilizing, to the maximum extent possible, a set of optimal shapes for sub-domains. We pr...