• The KIPS Transactions:PartD
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• v.13D no.4 s.107
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• pp.477-490
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• 2006

Existing index structures need very much update cost because they repeat delete and insert operations in order to update continuously moving objects. In this paper, we propose a new index structure which reduces the update cost of continuously moving objects. The proposed index structure consists of a space partitioning index structure that stores the location of the moving objects and an auxiliary index structure that directly accesses to their current positions. In order to increase the fanout of the node, it stores not the real partitioning area but kd-tree as the information about the child node of the node. In addition, we don't traverse a whole index structure, but access the leaf nodes directly and accomplish a bottom-up update strategy for efficiently updating the positions of moving objects. We show through the various experiments that our index structure outperforms the existing index structures in terms of insertion, update and retrieval.

• KIPS Transactions on Software and Data Engineering
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• v.5 no.4
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• pp.171-180
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• 2016

As social networking services such as twitter become increasingly popular, data streams are widely prevalent these days. In order to search data accumulated from data streams efficiently, the use of an index structure is essential. In this paper, we propose an update-efficient, disk-based inverted index structure for efficient keyword search on data streams. When new data arrive at the data stream, the index needs to be updated to incorporate the new data. The traditional inverted index is very inefficient to update in terms of disk I/O, because all index data stored in the disk need to be read and written to the disk each time the index is updated. To solve this problem, we divide the whole inverted index into a sequence of inverted indices with exponentially increasing size. When new data arrives, it is first inserted into the smallest index and, later, the small indices are merged with the larger indices, which leads to a small amortize update cost for each new data. Furthermore, when indices stored in the disk are merged with each other, we minimize the disk I/O cost incurred for the merge operation, resulting in an even smaller update cost. Through various experiments, we compare the update efficiency of the proposed index structure with the previous one, and show the performance advantage of the proposed structure in terms of the update cost.

• The Journal of Information Systems
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• v.10 no.1
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• pp.257-278
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• 2001

An IR(information retrieval) index for dynamic document databases where insertion, deletion, and update of documents happen frequently should be frequently updated. As the conventional structure of IR index is, however, focused on the information retrieval purpose, its structure is inefficient to handle dynamic update of it. In this paper, we propose a new structure for IR Index, we call it Index Graph, which is organized by connecting multiple indexes into a graph structure. By analysis and experiment, we prove the Index Graph is superior to the conventional structure of IR index in the performance of insertion, deletion, and update of documents as well as the performance of information retrieval.

• 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.

• Journal of KIISE:Databases
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• v.31 no.1
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• pp.39-47
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• 2004

Spatio-temporal databases have been mostly studied in the area of access methods. However, without considering an extraordinary update maintenance overhead after building up a spatio-temporal index, most indexing techniques have focused on fast query processing only. In this paper, we propose an efficient update management method that reduces the number of disk accesses required in order to apply the updates of moving objects to a spatio-temporal index. We consider realistic update patterns that can represent the movements of objects properly. We present a memory based structure that can efficiently maintain a small number of very frequently updating objects. For an experimental environment with realistic update patterns, the number of disk accesses of our method is about 40% lower than that of a general update method of existing spatio-temporal indexes.

• Journal of Korea Spatial Information System Society
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• v.8 no.3
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• pp.117-130
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• 2006

With the rapid development of technologies related to Ubiquitous Sensor Network (USN), sensors are being utilized in various application areas. In general, the data sensed by each sensor node on ubiquitous sensor networks are stored into the central server for efficient search. Because update is delayed to reduce the cost of update in this environment, uncertain data can be stored in the central server. In addition, Uncertain data make query processing produce wrong results in the central server. Thus, this paper examines how to process uncertain data in ubiquitous sensor networks and suggests a new index for efficient processing of uncertain data. The index reduces the cost of update by delaying update in uncertainty areas. Uncertainty areas are areas where uncertain data are likely to exist. In addition, it solves the problem of low accuracy in search resulting from update delay by delaying update only for specific update areas. Lastly, we analyze the performance of the index and prove the superiority of its performance by comparing its performance evaluation.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.5
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• pp.1807-1824
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• 2015

As the technologies advance, mobile peer-to-peer (MP2P) networks or systems become one of the major ways to share resources and information. On such a system, the information retrieval (IR), including the development of scalable infrastructures for indexing, becomes more complicated due to a huge increase on the amount of information and rapid information change. To keep the systems on MP2P networks more reliable and consistent, the index structures need to be updated frequently. For a semantic IR system, the index structure is even more complicated than a classic IR system and generally has higher update cost. The most well-known indexing technique used in semantic IR systems is Latent Semantic Indexing (LSI), of which the index structure is generated by singular value decomposition (SVD). Although LSI performs well, updating the index structure is not easy and time consuming. In an MP2P environment, which is fully distributed and dynamic, the update becomes more challenging. In this work, we consider how to update the sematic index generated by LSI and keep the index consistent in the whole MP2P network. The proposed Concept Space Update (CSU) protocol, based on distributed 2-Phase locking strategy, can effectively achieve the objectives in terms of two measurements: coverage speed and update cost. Using the proposed effective synchronization mechanism with the efficient updates on the SVD, re-computing the whole index on the P2P overlay can be avoided and the consistency can be achieved. Simulated experiments are also performed to validate our analysis on the proposed CSU protocol. The experimental results indicate that CSU is effective on updating the concept space with LSI/SVD index structure in MP2P semantic IR systems.

• The Journal of the Korea Contents Association
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• v.4 no.4
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• pp.141-152
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• 2004

In this paper, we propose the index structure supporting the future position retrievals with efficiently updating continuous positions of moving objects in location based services. For reducing update costs of moving objects, our index structure directly accesses to the leaf node with moving objects using secondary index structure and performs bottom up update when node information is changed. Positions of moving objects are stored in primary index structure. In primary index structure, the split information similar to kd-tree is stored to internal node for increasing node's fanout. And the proposed index structure supports the future position retrievals using velocity of moving objects in the child node.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.29B no.7
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• pp.11-22
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• 1992

In this paper, a new indexing technique is proposed for efficient evaluation of nested queries on aggregation hierarchy in object-oriented data model. As an index data structure, an extended $B^{+}$ tree is introduced in which instance identifier to be searched and path information used for update of index record are stored in leaf node and subleaf node, respectively. the retrieval and update algorithm on the introduced index data structure is provided. Comparisons under a variety of conditions are given with current indexing techniques, showing improved performance in cost, i.e., the total number of pages accessed for retrieval and update.

• Journal of the Korea Society of Computer and Information
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• v.20 no.4
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• pp.1-10
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• 2015

NAND flash systems require deletion operation and do not support in-place update, so the storage systems should use Flash Translation Layer (FTL). However, there are a lot of memory consumptions using mapping table in the FTL, so recently, many studies have been proposed to resolve mapping table overhead. These studies try to solve update propagation problem in the nand flash system which does not use mapping table. In this paper, we present a novel index structure, called CL-Tree(Cache List Tree), to solve the update propagation problem. The proposed index structure reduces write operations which occur for an update propagation, and it has a good performance for search operation because it uses multi-list structure. In experimental evaluation, we show that our scheme yields about 173% and 179% improvement in insertion speed and search speed, respectively, compared to traditional B+tree and other works.