• Journal of Korea Multimedia Society
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• v.4 no.5
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• pp.465-475
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• 2001

Recent1y, there is growing attention on the researches of inducing association rules from large volume of database. One of them is the method that can be applied to quantitative attribute data. This paper presents a new method for generating large-interval itemsets, which uses locality for partitioning the range of data. This method can minimize the loss of data-inherent characteristics by generating denser large-interval items than other methods. Performance evaluation results show that our new approach is more efficient than previously proposed techniques.

• Journal of Korea Multimedia Society
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• v.7 no.8
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• pp.1086-1096
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• 2004

In case of a multimedia application which deals with streaming data, in terms of cache management, cache loses its efficiency due to weak temporal locality of the data. This means that when data have been brought into cache, much of the data are supposed to be replaced without being accessed again during its service. However, there is a good chance that such multimedia data has a commanding locality in it. In this paper, to take advantage of the memory reference regularity which typically innates even in the multimedia data showing up its weak temporal locality, a method is suggested. The suggested method with the feature of dynamic regular-stride reference prefetching can identify for 2-dimensional array format(block pattern). The suggested method is named as block-reference-prediction-technique (BRPT) since it identifies a block pattern and place an address to be prefetched by the regulation of the block format. BRPT proved to be reassuring to reduce memory reference time significantly for applications having abundant block patterns although new rule has complicated the prefetching system even further.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.7
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• pp.3583-3598
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• 2019

In order to improve the reliability and repair efficiency of distributed storage systems, minimum bandwidth regenerating (MBR) codes based on cyclic variable fractional repetition (VFR) codes are constructed in this thesis, which can repair failed nodes accurately. Specifically, in order to consider the imbalance of data accessed by the users, cyclic VFR codes are constructed according to that data with different heat degrees are copied in different repetition degrees. Moreover, we divide the storage nodes into groups, and construct MBR codes based on cyclic VFR codes to improve the file download speed. Performance analysis and simulation results show that, the repair locality of a single node failure is always 2 when MBR codes based on cyclic VFR codes are adopted in distributed storage systems, which is obviously superior to the traditional MBR codes. Compared with RS codes and simple regenerating codes, the proposed MBR codes based on cyclic VFR codes have lower repair locality, repair complexity and bandwidth overhead, as well as higher repair efficiency. Moreover, relative to FR codes, the MBR codes based on cyclic VFR codes can be applicable to more storage systems.

• Journal of KIISE:Software and Applications
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• v.32 no.10
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• pp.1003-1012
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• 2005

The most significant difference of embedded systems from general purpose systems is that embedded systems are allowed to use only limited resources including battery and memory. Especially, the number of applications increases which deal with multimedia data. In those systems with high data computations, the delay of memory access is one of the major bottlenecks hurting the system performance. As a result, many researchers have investigated various techniques to reduce the memory access cost. Most programs generally have locality in memory references. Temporal locality of references means that a resource accessed at one point will be used again in the near future. Spatial locality of references is that likelihood of using a resource gets higher if resources near it were just accessed. The latest embedded processors usually adapt cache memory to exploit these two types of localities. Processors access faster cache memory than off-chip memory, reducing the latency. In this paper we will propose the enhanced dynamic allocation technique for structure-type data in order to eliminate unused memory space and to reduce both the cache miss rate and the application execution time. The proposed approach aggregates fields from multiple records dynamically allocated and consecutively remaps them on the memory space. Experiments on Olden benchmarks show $13.9\%$ L1 cache miss rate drop and $15.9\%$ L2 cache miss drop on average, compared to the previously proposed techniques. We also find execution time reduced by $10.9\%$ on average, compared to the previous work.

• KIISE Transactions on Computing Practices
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• v.23 no.5
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• pp.275-283
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• 2017

A large amount of RDF data has been generated along with the increase of semantic web services. Various distributed storage and query processing schemes have been studied to efficiently use the massive amounts of RDF data. In this paper, we propose a distributed SPARQL query processing scheme that considers the data locality and query execution path of large RDF data. The proposed scheme considers the data locality and query execution path in order to reduce join and communication costs. In a distributed environment, when processing a SPARQL query, it is divided into several sub-queries according to the conditions of the WHERE clause by considering the data locality. The proposed scheme reduces data communication costs by grouping and processing the sub-queries through the index based on associated nodes. In addition, in order to reduce unnecessary joins and latency when processing the query, it creates an efficient query execution path considering data parsing cost, the amount of each node's data communication, and latency. It is shown through various performance evaluations that the proposed scheme outperforms the existing scheme.

• Journal of Information Technology and Architecture
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• v.10 no.1
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• pp.79-91
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• 2013

This paper proposes a systematic methodology that could be used to decide which one shows the best performance among space filling curves (SFCs) in applying lower-dimensional transformations to histogram sequences. A histogram sequence represents a time-series converted from an image by the given SFC. Due to the high-dimensionality nature, histogram sequences are very difficult to be stored and searched in their original form. To solve this problem, we generally use lower-dimensional transformations, which produce lower bounds among high dimensional sequences, but the tightness of those lower-bounds is highly affected by the types of SFC. In this paper, we attack a challenging problem of evaluating which SFC shows the better performance when we apply the lower-dimensional transformation to histogram sequences. For this, we first present a concept of spatial locality, which comes from an intuition of "if the entries are adjacent in a histogram sequence, their corresponding cells should also be adjacent in its original image." We also propose spatial locality preservation metric (slpm in short) that quantitatively evaluates spatial locality and present its formal computation method. We then evaluate five SFCs from the perspective of slpm and verify that this evaluation result concurs with the performance evaluation of lower-dimensional transformations in real image matching. Finally, we perform k-NN (k-nearest neighbors) search based on lower-dimensional transformations and validate accuracy of the proposed slpm by providing that the Hilbert-order with the highest slpm also shows the best performance in k-NN search.

• The KIPS Transactions:PartA
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• v.16A no.2
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• pp.69-78
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• 2009

One of the most effective way to improve cache performance is to exploit both temporal and spatial locality given by any program executive characteristics. In this paper we present a high performance and low power cache structure with a bank selection mechanism that enhances exploitation of spatial and temporal locality. The proposed cache system consists of two parts, i.e., a main direct-mapped cache with a small block size and a fully associative buffer with a large block size as a multiple of the small block size. Especially, the main direct-mapped cache is constructed as two banks for low power consumption and stores a small block which is selected from fully associative buffer by the proposed bank selection algorithm. By using the bank selection algorithm and three state bits, We selectively extend the lifetime of those small blocks with high temporal locality by storing them in the main direct-mapped caches. This approach effectively reduces conflict misses and cache pollution at the same time. According to the simulation results, the average miss ratio, compared with the Victim and STAS caches with the same size, is improved by about 23% and 32% for Mibench applications respectively. The average memory access time is reduced by about 14% and 18% compared with the he victim and STAS caches respectively. It is also shown that energy consumption of the proposed cache is around 10% lower than other cache systems that we examine.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.9
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• pp.1734-1740
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• 2015

This paper introduces a generalized notion, referred to as joint locality, of the usual locality in distributed storage systems and proposes a code construction of binary locally repairable codes with joint locality ($r_1$=2, $r_2$=3 or 4). Joint locality is a set of numbers of nodes for repairing various failure patterns of nodes. The proposed scheme simplifies the code design problem utilizing complete multipartite graphs. Moreover, our construction can generate binary locally repairable codes achieving (2,t)-availability for any positive integer t. It means that each node can be repaired by t disjoint repair sets of cardinality 2. This property is useful for distributed storage systems since it permits parallel access to hot data.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.41 no.10
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• pp.1167-1175
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• 2016

This paper proposes an efficient page-level mapping algorithm that reduces the erase count in the FTL for flash memory systems. By maintaining the weight for each write request in the request buffer, the proposed algorithm estimates the degree of temporal locality for each incoming write request. To exploit temporal locality deliberately for determination of hot request, the degree of temporal locality should be much higher than the reference point determined experimentally. While previous LRU algorithm treats a new write request to have high temporal locality, the proposed algorithm allows write requests that are estimated to have high temporal locality to access hot blocks to store hot data intensively. The pages are more frequently updated in hot blocks than warm blocks. A hot block that has most of invalid pages is always selected as victim block at Garbage Collection, which results in delayed erase operation and in reduced erase count. Experimental results show that erase count is reduced by 9.3% for real I/O workloads, when compared to the previous LRU algorithm.

• Journal of KIISE:Computer Systems and Theory
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• v.27 no.6
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• pp.592-598
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• 2000

The locality of data references at the distributed shared memory systems affects the performance significantly. Data allocation methods by considering the locality of data references can improve the performance of DSM systems. This paper evaluates the performance for the dynamic limited directory scheme which data allocation methods can apply very effectively. The information of the data allocation is used by the dynamic limited directory scheme to set the presence bit effectively. And the proper use of the presence bit improves the performance by reducing memory overhead and using directory pool efficiently. Simulations are conducted using three application programs which have various data sharing. The results show that the optimal data allocation method improves the performance up to 3.6 times in the proposed scheme.