• Journal of Korea Society of Digital Industry and Information Management
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• v.5 no.3
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• pp.59-67
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• 2009

This paper proposes a improved bitmap routing protocol, which finds the best energy efficient routing path by minimizing the network overheads and prolongs the overall network lifetime. Jung proposed a bitmap scheme for sensor networks. His scheme uses a bitmap table to represent the connection information between nodes. However, it has a problem that the table size is depends on the number of nodes in the sensor networks. The problem is very serious in the sensor node with a limited memory. Thereby, this paper proposes a improved bitmap routing protocol to solve the problem in Jung's scheme. Proposed protocol over the memory restricted sensor network could optimize the size of bitmap table by applying the deployed network property. Proposed protocol could be used in the diversity of sensor networks due to it has minimum memory overheads.

• Journal of the Korean Society for Precision Engineering
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• v.32 no.9
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• pp.833-840
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• 2015

Inkjet technology is one of the commonly used technologies in the printed-electronics field. The primary issue regarding the usage of inkjet technology as a printed-electronics tool is the printing resolution; therefore, to print complicated patterns of precise dimensions, we developed software that can convert a CAD file into a bitmap image. Moreover, as a bitmap image is not comprised of physical dimensions, its resolution needs to be defined in terms of pixel distance to print a rasterized bitmap image. In this study, we investigated the effects of pixel distance and dot size on printing resolution; based on the experiment results, we concluded that the printed dot size should be used to determine the optimal pixel distance. Lastly, we also propose inkjet printing procedures for bitmap images.

• Proceedings of the Korea Information Processing Society Conference
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• 2005.05a
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• pp.11-14
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• 2005

데이터베이스 성능이 저하되면, 가장 먼저 SQL 튜닝을 고려한다. SQL 튜닝에서 가장 주의 깊게 사용 해야하는 부분이 바로 Index의 설정과 관련된 부분이다. 본 논문에서 OLAP 환경에서 다양하고 복잡한 질의처리 요구와 관련하여, B-Tree Index의 문제점을 개선하고 질의 성능을 향상시키기 위해서 Bitmap Index를 사용하였다. 또한, Bitmap Index 사용의 최적 임계점을 추적하기 위하여, 데이터 분포도와 조건절의 복잡도를 조사하였으며, 샘플링된 질의문을 기준으로 B-Tree Index를 사용하였을 때와 Bitmap Index를 사용하였을 때의 비교 실험을 통하여 Bitmap Index의 사용으로 RDBMS의 성능향상이 있음을 증명하였다.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.43 no.1 s.307
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• pp.35-44
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• 2006

Recently, a lot of index techniques for storing and querying XML document have been studied so far and many researches of them used coordinate-based methods. But update operation and query processing to express structural relations among elements, attributes and texts make a large burden. In this paper, we propose an efficient BitmapInvert index technique based on Relative Position Coordinate (RPC). RPC has good preformance even if there are frequent update operations because it represents relationship among parent node and left, right sibling nodes. BitmapInvert index supports tort query with bitwise operations and does not casue serious performance degradations on update operations using PostUpdate algerian. Overall, the performance could be improved by reduction of the number of times for traversing nodes.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.5
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• pp.2326-2345
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• 2016

For the compression of color images, a common bitmap usually is generated to replace the three individual bitmaps that originate from block truncation coding (BTC) of the R, G and B channels. However, common bitmaps generated by some traditional schemes are not the best possible because they do not consider the minimized distortion of the entire color image. In this paper, we propose a near-optimized common bitmap scheme for BTC using Binary Ant Colony Optimization (BACO), producing a BACO-BTC scheme. First, the color image is compressed by the BTC algorithm to get three individual bitmaps, and three pairs of quantization values for the R, G, and B channels. Second, a near-optimized common bitmap is generated with minimized distortion of the entire color image based on the idea of BACO. Finally, the color image is reconstructed easily by the corresponding quantization values according to the common bitmap. The experimental results confirmed that reconstructed image of the proposed scheme has better visual quality and less computational complexity than the referenced schemes.

• Journal of the Korea Society of Computer and Information
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• v.17 no.1
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• pp.203-209
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• 2012

Recently, k-nearest neighbors query methods based on wireless broadcasting environment are actively studied. The advantage of wireless broadcasting environment is the scalability that enables collective query processing for unspecified users connected to the server. However, in case existing k-NN query is applied in wireless broadcasting environment, there can be a disadvantage that backtracking may occur and consequently the query processing time is increasing. In this paper proposes a hierarchical bitmap-based spatial index in order to efficiently process the k-NN queries in wireless broadcasting environment. HBI reduces the bitmap size using such bitmap information and tree structure. As a result, reducing the broadcast cycle can reduce the client's tuning time and query processing time. In addition, since the locations of all the objects can be detected using bitmap information, it is possible to tune to necessary data selectively. For this paper, a test was conducted implementing HBI to k-NN query and the proposed technique was proved to be excellent by a performance evaluation.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.5 no.10
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• pp.1862-1878
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• 2011

With the advances in wireless communication technology and the advent of smartphones, research on location-based services (LBSs) is being actively carried out. In particular, several spatial index methods have been proposed to provide efficient LBSs. However, finding an optimal indexing method that balances query performance and index size remains a challenge in the case of wireless environments that have limited channel bandwidths and device resources (computational power, memory, and battery power). Thus, mechanisms that make existing spatial indexing techniques more efficient and highly applicable in resource-limited environments should be studied. Bitmap-based Spatial Indexing (BSI) has been designed to support LBSs, especially in wireless broadcast environments. However, the access latency in BSI is extremely large because of the large size of the bitmap, and this may lead to increases in the search time. In this paper, we introduce a Selective Bitmap-based Spatial Indexing (SBSI) technique. Then, we propose an Adaptive Bitmap-based Spatial Indexing (ABSI) to improve the tuning time in the proposed SBSI scheme. The ABSI is applied to the distribution of geographical objects in a grid by using the Hilbert curve (HC). With the information in the ABSI, grid cells that have no objects placed, (i.e., 0-bit information in the spatial bitmap index) are not tuned during a search. This leads to an improvement in the tuning time on the client side. We have carried out a performance evaluation and demonstrated that our SBSI and ABSI techniques outperform the existing bitmap-based DSI (B DSI) technique.

• The KIPS Transactions:PartA
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• v.11A no.2
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• pp.129-142
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• 2004

As the Internet gets faster, the demand for high-speed routers that are capable of forwarding more than giga bits of data per second keeps increasing. In the previous research, Bitmap Trie algorithm was developed to rapidly execute LPM(longest prefix matching) process which is Well known as the Severe performance bottleneck. In this paper, we introduce a novel algorithm that drastically enhanced the performance of Bitmap. Trie algorithm by applying three techniques. First, a new table called the Count Table was devised. Owing to this table, we successfully eliminated shift operations that was the main cause of performance degradation in Bitmap Trie algorithm. Second, memory utilization was improved by removing redundant forwarding information from the Transfer Table. Lastly. the range of prefix lookup was diversified to optimize data accesses. On the other hand, the processing delays were classified into three categories according to their causes. They were, then, measured through the execution-driven simulation that provides the higher quality of the results than any other simulation techniques. We tried to assure the reliability of the experimental results by comparing with those that collected from the real system. Finally the Enhanced Bitmap Trie algorithm reduced 82% of time spent in previous algorithm.

• Journal of Computing Science and Engineering
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• v.1 no.2
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• pp.177-194
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• 2007

Index selection is one of the most important decisions to take in the physical design of relational data warehouses. Indices reduce significantly the cost of processing complex OLAP queries, but require storage cost and induce maintenance overhead. Two main types of indices are available: mono-attribute indices (e.g., B-tree, bitmap, hash, etc.) and multi-attribute indices (join indices, bitmap join indices). To optimize star join queries characterized by joins between a large fact table and multiple dimension tables and selections on dimension tables, bitmap join indices are well adapted. They require less storage cost due to their binary representation. However, selecting these indices is a difficult task due to the exponential number of candidate attributes to be indexed. Most of approaches for index selection follow two main steps: (1) pruning the search space (i.e., reducing the number of candidate attributes) and (2) selecting indices using the pruned search space. In this paper, we first propose a data mining driven approach to prune the search space of bitmap join index selection problem. As opposed to an existing our technique that only uses frequency of attributes in queries as a pruning metric, our technique uses not only frequencies, but also other parameters such as the size of dimension tables involved in the indexing process, size of each dimension tuple, and page size on disk. We then define a greedy algorithm to select bitmap join indices that minimize processing cost and verify storage constraint. Finally, in order to evaluate the efficiency of our approach, we compare it with some existing techniques.

• The KIPS Transactions:PartA
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• v.9A no.3
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• pp.287-294
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• 2002

In this paper we propose a new mechanism for file system using a dynamic bitmap assignment. While traditional file systems rely on a fixed bitmap structures for metadata such as super block, inode, and directory entries, the proposed file system allocates bitmap and allocation area depends on file system features. Our approach gives a solution of the problem that the utilization of the file system depends on the file size in the traditional file systems. We show that the proposed mechanism is superior in the efficiency of disk usage compared to the traditional mechanisms.