• The Transactions of the Korea Information Processing Society
• /
• v.7 no.9
• /
• pp.2827-2835
• /
• 2000

In recent years, much attention has been focused on improving I/O devices' processing speed which is essential in such large data processing areas as multimedia data processing. And studies on high-performance parallel file systems are considered to be one of such efforts. In this paper, an efficient disk allocation scheme is proposed for high-performance parallel file systems. In other words, the concept of a parallel disk file's parallelism is defined using data declustering characteristic of a given parallel file. With the concept, an efficient disk allocation scheme is proposed which calculates the appropriate degree of data declustering on disks for each parallel file in order to obtain the maximum throughput when more than one parallel file is used at the same time. Since, calculation for obtaining the maximum throughput is too complex as the number of parallel files increases, an approximate disk allocation algorithm is also proposed in this paper. The approximate algorithm is very simple and especially provides very good results when I/O workload is high. In addition, it has shown that the approximate algorithm provides the optimal disk allocation for the maximum throughput when the arrival rate of I/O requests is infinite.

• The Transactions of the Korea Information Processing Society
• /
• v.6 no.9
• /
• pp.2294-2304
• /
• 1999

Our research purpose in this paper is to improve the performance of query processing in GIS(Geographic Information System) by enhancing the I/O performance exploiting parallel I/O and efficient disk access. By packing adjacent spatial data, which are very likely to be referenced concurrently, into one block or continuous disk blocks, the number of disk accesses and the disk access overhead for query processing can be decreased, and this eventually leads to the I/O time decrease. So, in this paper, we proposes EPR(Enhanced Parallel R-tree) indexing method which integrates the parallel I/O method of the previous Parallel R-tree method and a packing-based clustering method. The major characteristics of EPR method are as follows. First, EPR method arranges spatial data in the increasing order of proximity by using Hilbert space filling curve, and builds a packed R-tree by bottom-up manner. Second, with packing-based clustering in which arranged spatial data are clustered into continuous disk blocks, EPR method generates spatial data clusters. Third, EPR method distributes EPR index nodes and spatial data clusters on multiple disks through round-robin striping. Experimental results show that EPR method achieves up to 30% or more gains over PR method in query processing speed. In particular, the larger the size of disk blocks is and the smaller the size of spatial data objects is, the better the performance of query processing by EPR method is.

• Journal of Digital Convergence
• /
• v.11 no.11
• /
• pp.421-427
• /
• 2013

Disk Cache Manager(DCM), a functional server of microkernel based, to improve the I/O power of shared disks is designed and implemented in this work. DCM interfaces other different servers with message passing through ports by serving as a system actor the multi-thread mode on the Minix3 micro-kernel. DCM proposed in this paper uses the shared disk logically as a Seven Disk and Sodd Disk to enable parallel I/O. DCM enables the efficient placement of disk data because it raises disk cache hit-ratio by increasing the cache size when the utilization of the particular disk is high. Through experimental results, we show that DCM is quite efficient for a shared disk with higher utilization.

• Journal of the Institute of Electronics Engineers of Korea CI
• /
• v.41 no.2
• /
• pp.9-22
• /
• 2004

This paper presents a parallel genetic algorithm for the Multi-disk data allocation problem an NP-complete problem. This problem is to find a method to distribute a Binary Cartesian Product File on disk-arrays to maximize parallel disk I/O accesses. A Sequential Genetic Algorithm(SGA), DAGA, has been proposed and showed the superiority to the other proposed methods, but it has been observed that DAGA consumes considerably lengthy simulation time. In this paper, a parallel version of DAGA(ParaDAGA) is proposed. The ParaDAGA is a 2-dimension torus-based Parallel Genetic Algorithm(PGA) and it is based on a distributed population structure. The ParaDAGA has been implemented on the parallel computer simulated on a single processor platform. Through the simulation, we study the impact of varying ParaDAGA parameters and compare the quality of solution derived by ParaDAGA and DAGA. Comparing the quality of solutions, ParaDAGA is superior to DAGA in all cases of configurations in less simulation time.

• Journal of KIISE:Computing Practices and Letters
• /
• v.9 no.6
• /
• pp.635-645
• /
• 2003

One of very important features that are necessarily supported by clustered parallel computer systems is a single I/O system image in which users can access both the local and remote I/O resources transparently. In this paper, we propose an efficient disk sharing technique supporting a single disk I/O system image architecture. The design separates the I/O subsystem of a cluster into the file system and a set of virtual hard disk drivers. The virtual hard disk driver deals with a hard disk in the remote node as a local hard disk. All services provided by it are performed in the device driver level without any modification of file systems. Users can, therefore, access all the disks in the cluster regardless of their locations. Our virtual hard disk driver is implemented under the linux, and also tested in a linux cluster system. We find by experiments that it can successfully support a single disk I/O space, and at the same time it shows better performance than NFS. We are sure that this paper can be a guideline for single I/O space of other devices to be easily constructed.

• Journal of the Korea Society for Simulation
• /
• v.8 no.2
• /
• pp.29-43
• /
• 1999

As real-time processing of data with large storage space is required in the era of multimedia, disk arrays are generally used as storage subsystems which be able to provide improved I/O performance. To design the cost-effective disk array, it is important to develop performance models which evaluate the disk array performance. Both queueing theory and simulation are applicable as the method of performance evaluation through queueing modeling. But there is a limit to the analytical method using queueing theory due to the characteristics of disk array requests being serviced in the parallel and concurrent manner. So in this paper we evaluate the disk array performance using simulation method which abstract disk array systems in the low level. Performance results were evaluated through simulation, so that mean response time, mean queueing delay, mean service time, mean queue length for disk array requests and utilization, throughput for disk array systems, can be utilized for capacity planning in the phase of disk array design.

• Journal of the Korean Institute of Telematics and Electronics B
• /
• v.32B no.11
• /
• pp.1365-1373
• /
• 1995

In this paper, we address the issues related to storage and retrieval of continuous media (CM)data we face in designing multimedia on-demand (MOD) storage servers. To support the two orthogonal factors of MOD server design, i.e., storage and retrieval of CM data, this paper discusses the techniques of disk layout, disk striping and real-time disk scheduling, which are integrated as a combined solution to the high- performance MOD storage subsystem. The proposed clustered striping technique enables either a multiple-disk or a parallel system to guarantee a continuous retrieval of CM data at the bandwidth required to support user playback rate by avoiding the formation of I/O bottlenecks.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2007.05a
• /
• pp.769-772
• /
• 2007

공간 데이터의 효율적인 처리는 현대의 멀티미디어 데이터베이스에 있어서 대단히 중요한 역할을 하고 있다. 많은 응용분야에서 방대한 양의 공간 데이터는 보조기억장치(예: disk)에 저장이 되어 사용이 되고 공간 색인구조의 처리는 I/O에 대한 의존도가 크므로, I/O 연산의 병렬처리는 공간 색인구조의 질의반응시간을 현저하게 줄일 수 있다. 본 논문에서는 PR-tree라는 병렬형 공간 색인구조를 제안한다. PR-tree는 MXR-tree에 비해 높은 공간활용도와 빠른 처리시간을 보임으로써 공간 데이터베이스를 위한 효율적인 색인구조로 사용이 될 것으로 기대된다.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2009.11a
• /
• pp.775-776
• /
• 2009

공간데이터를 관리하는 공간 index structure는 대부분 순차처리를 위한 구조를 가지고 있다. 많은 응용분야에서 방대한 양의 공간 데이터는 보조기억장치(예: disk)에 저장이 되어 사용이 되고 공간 index structure의 operation은 I/O에 대한 의존도가 크므로, I/O operation의 병렬처리는 공간 index structure의 질의반응시간을 현저하게 줄일 수 있다. 본 논문에서는 PPR-tree라는 병렬형 공간 index structure를 제안한다.

• Journal of the Korean Institute of Telematics and Electronics C
• /
• v.35C no.3
• /
• pp.46-58
• /
• 1998

Multi-disk data allocation problem examined in this paper is to find a method to distribute a Binary Cartesian Product File on multiple disks to maximize parallel disk I/O accesses for partial match retrieval. This problem is known to be NP-hard, and heuristkc approaches have been applied to obtain sub-optimal solutions. Recently, efficient methods have been proposed with a restriction that the number of disks in which files are stored should be power of 2. In this paper, we propose a new disk Allocation method based on Genetic Algorithm(GA) to remove the restriction on the number of disks to be applied. Using the schema theory, we prove that our method can find a near-optimal solutionwith high probability. We compare the quality of solution derived by our method with General Disk Modulo, Binary Disk Modulo, and Error Correcting Code methods through the simulation. The simulation results show that proposed GA is superior to GDM method in all cases and provides comparable performance to the BDM method which has a restriction on the number of disks.