• Journal of KIISE:Databases
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• 제30권5호
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• pp.451-463
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• 2003

Recently, there have been various research efforts to develop strategies for accelerating OLAP operations on huge amounts of spatio-temporal data. Most of the work is based on multi-tree structures which consist of a single R-tree variant for spatial dimension and numerous B-trees for temporal dimension. The multi~tree based frameworks, however, are hardly applicable to spatio-temporal OLAP in practice, due mainly to high management cost and low query efficiency. To overcome the limitations of such multi-tree based frameworks, we propose a new approach called Hilbert Cube(H-Cube), which employs fractals in order to impose a total-order on cells. In addition, the H-Cube takes advantage of the traditional Prefix-sum approach to improve Query efficiency significantly. The H-Cube partitions an embedding space into a set of cells which are clustered on disk by Hilbert ordering, and then composes a cube by arranging the grid cells in a chronological order. The H-Cube refines cells adaptively to handle regional data skew, which may change its locations over time. The H-Cube is an adaptive, total-ordered and prefix-summed cube for spatio-temporal data warehouses. Our approach focuses on indexing dynamic point objects in static spatial dimensions. Through the extensive performance studies, we observed that The H-Cube consumed at most 20% of the space required by multi-tree based frameworks, and achieved higher query performance compared with multi-tree structures.

• Journal of KIISE:Databases
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• 제36권3호
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• pp.226-234
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• 2009

A data stream is a massive unbounded sequence of data elements continuously generated at a rapid rate. Due to the characteristics of a data stream, it is impossible to save all the data elements of a data stream. Therefore it is necessary to define a new synopsis structure to store the summary information of a data stream. For this purpose, this paper proposes a cuboid prefix tree that can be effectively employed in evaluating an iceberg query over data streams. A cuboid prefix tree only stores those itemsets that consist of grouping attributes used in GROUP BY query. In addition, a cuboid prefix tree can compute multiple iceberg queries simultaneously by sharing their common sub-expressions. A cuboid prefix tree evaluates an iceberg query over an infinitely generated data stream while efficiently reducing memory usage and processing time, which is verified by a series of experiments.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• 제19권8호
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• pp.138-143
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• 2005

A hierarchical tree structure of clusters has advantages for the network design due to its scalability and simple routing protocol. In this paper, the cluster tree routing protocol is studied for the wireless sensor network. From the numerical analysis results, the data aggregation in the intermediate nodes reduces the number of communication message and saves the energy of sensor nodes, but it may result in increased data traffic latency. And also the selection of cluster head can increase the relaying hops very high.

• Journal of Korea Multimedia Society
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• 제9권11호
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• pp.1381-1394
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• 2006

Generation methods of data cube have been studied for many years in data warehouse which supports decision making using stored data. There are two previous studies, one is multi-way array algorithm and the other is H-cubing algorithm which is based on the hyper-tree. The multi-way array algorithm stores all aggregation data in arrays, so if the base data is increased, the size of memory is also grow. The H-cubing algorithm which is based on the hyper-tree stores all tuples in one tree so the construction cost is increased. In this paper, we present an efficient data cube generation method based on hash table using weight mapping table and record hash table. Because the proposed method uses a hash table, the generation cost of data cube is decreased and the memory usage is also decreased. In the performance study, we shows that the proposed method provides faster search operation time and make data cube generation operate more efficiently.

• The Journal of Korean Institute of Communications and Information Sciences
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• 제36권7B호
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• pp.848-857
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• 2011

Due to the advantages of a conveniet, inexpensive installation, flexibility, and scalability, Wireless AMR systems are recently preferred over wired AMR systems. However, a multi-hop supported AMR network, which generally covers large areas, may create energy wastage problem, energy unbalance, and high interference hazard due to a large amount of concurrent-intensive metering data in the network. Therefore in this paper we propose a novel data gathering method which can solve abovementioned problems as well as conserve energy, by reducing the traffic in the network. In addition, the experimental results demonstrate that the proposed scheme shows superior performance to the conventional data transmission method.

• Journal of the Korea Society of Computer and Information
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• 제15권5호
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• pp.133-141
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• 2010

Contents adaptation is a technology which converts one content to another content used in various devices. Specially, synchronization of inter-media which are included in a document is needed. There are various proposals and solutions for synchronization of inter-media. In the paper, I present "TATS : Temporal Aggregate Tree Strategy" model, which is used for specifying the temporal relationship among media in series of time. In the TATS model, aggregate tree, a sort of a binary tree, is generated from the execution time of those media. Using this aggregate tree, I implemented the inter-media synchronizations.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• 제20권2호
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• pp.1-11
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• 2020

As an important basic building block of the smart grid environment, smart meter provides real-time electricity consumption information to the utility. However, ensuring information security and privacy in the smart meter data aggregation process is a non-trivial task. Even though the secure data aggregation for the smart meter has been a lot of attention from both academic and industry researchers in recent years, most of these studies are not secure against internal attackers or cannot provide data integrity. Besides, their computation costs are not satisfactory because the bilinear pairing operation or the hash-to-point operation is performed at the smart meter system. Recently, blockchains or distributed ledgers are an emerging technology that has drawn considerable interest from energy supply firms, startups, technology developers, financial institutions, national governments and the academic community. In particular, blockchains are identified as having the potential to bring significant benefits and innovation for the electricity consumption network. This study suggests a distributed, privacy-preserving, and simple secure smart meter data aggregation system, backed up by Blockchain technology. Smart meter data are aggregated and verified by a hierarchical Merkle tree, in which the consensus protocol is supported by the practical Byzantine fault tolerance algorithm.

• The KIPS Transactions:PartC
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• 제17C권1호
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• pp.69-80
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• 2010

Wireless sensor networks (WSN) consisting of a large number of sensors aim to gather data in a variety of environments and are being used and applied to many different fields. The sensor nodes composing a sensor network operate on battery of limited power and as a result, high energy efficiency and long network lifetime are major goals of research in the WSN. In this paper we propose a novel tree-based clustering approach for energy efficient wireless sensor networks. The proposed scheme forms the cluster and the nodes in a cluster construct a tree with the root of the cluster-head., The height of the tree is the distance of the member nodes to the cluster-head. Computer simulation shows that the proposed scheme enhances energy efficiency and balances the energy consumption among the nodes, and thus significantly extends the network lifetime compared to the existing schemes such as LEACH, PEGASIS, and TREEPSI.

• Journal of Korea Spatial Information System Society
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• 제11권2호
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• pp.99-110
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• 2009

Currently, there are many applications being developed based on sensor network technology. A tracking method for moving objects in sensor network is one of the main issue of this field. There is a little research on this issue, but most of the existing work has two problems. The first problem is a communication overhead for visiting sensor nodes many times to track a moving object. The second problem is an disability for dealing with many moving objects at a time. To resolve the problems, we, in this paper, propose a signature-based tracking method using efficient data aggregation for moving objects, called SigMO-TRK. For this, we first design a local routing hierarchy tree to aggregate moving objects' trajectories efficiently by using a space filtering technique. Secondly, we do the tracking of all trajectories of moving objects by using signature in a efficient way, our approach generates signatures to method. In addition, by extending the SigMO-TRK, we can retrieve the similar trajectories of moving objects for given a query. Finally, by using the TOSSIM simulator, we show that our signature-based tracking method outperforms the existing tracking method in terms of energy efficiency.

• Proceedings of the Korean Information Science Society Conference
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• 한국정보과학회 2003년도 가을 학술발표논문집 Vol.30 No.2 (2)
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• pp.46-48
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• 2003

최근 시공간 데이타에 대한 OLAP연산 효율을 증가시키기 위한 여러 가지 연구들이 행하여지고 있다. 이들 연구의 대부분은 다중트리구조에 기반하고 있다. 다중트리구조는 공간차원을 색인하기 위한 하나의 R-tree와 시간차원을 색인하기 위한 다수의 B-tree로 이루어져 있다. 하지만, 이러한 다중트리구조는 높은 유지비용과 불충분한 질의 처리 효율로 인해 현실적으로 시공간 OLAP연산에 적용하기에는 어려운 점이 있다. 본 논문에서는 이러한 문제를 근본적으로 개선하기 위한 접근 방법으로서 힐버트큐브(Hilbert Cube, H-Cube)를 제안하고 있다. H-Cube는 집계질의(aggregation query) 처리 효율을 높이기 위해 힐버트 곡선을 이용하여 셀들에게 완전순서(total-order)를 부여하고 있으며, 아울러 전통적인 누적합(prefix-sum) 기법을 함께 적용하고 있다. H-Cube는 적응적이며, 완전순서화되어 있으며, 또한 누적합을 이용한 셀 기반의 색인구조이다. 본 논문에서는 H-Cube의 성능 평가를 위해서 다양한 실험을 하였으며, 그 결과로서 유지비용과 질의 처리 효율성면 모두에서 다중트리구조보다 높은 성능 향상이 있음을 보인다.