• Journal of Korea Spatial Information System Society
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• v.11 no.1
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• pp.115-126
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• 2009

Recent development in wireless communication and mobile positioning technologies makes Location-Based Services (LBSs) popular. However, because, in the LBSs, users request a query to database servers by using their exact locations, the location information of the users can be misused by adversaries. Therefore, a mechanism for users' privacy protection is required for the safe use of LBSs by mobile users. For this, we, in this paper, propose a efficient cloaking region creation scheme using Hilbert curves in distributed grid environment, so as to protect users' privacy in LBSs. The proposed scheme generates a minimum cloaking region by analyzing the characteristic of a Hilbert curve and computing the Hilbert curve values of neighboring cells based on it, so that we may create a cloaking region to satisfy K-anonymity. In addition, to reduce network communication cost, we make use of a distributed hash table structure, called Chord. Finally, we show from our performance analysis that the proposed scheme outperforms the existing grid-based cloaking method.

• Journal of KIISE:Databases
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• v.33 no.5
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• pp.463-475
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• 2006

In applications such as a traffic management system, analysis using a spatial hierarchy of a spatial data warehouse and a simple aggregation is required. Over the past few years, several studies have been made on solution using a spatial index. Many studies have focused on using extended R-tree. But, because it just provides either the current aggregation or the total aggregation, decision support of traffic policy required historical analysis can not be provided. This paper proposes hybrid index based on extended aR-tree for the spatio-temporal aggregation. The proposed method supports a spatial hierarchy and the current aggregation by the R-tree. The sorted hash table using the time structure of the extended aR-tree provides a temporal hierarchy and a historical aggregation. Therefore, the proposed method supports an efficient decision support with spatio-temporal analysis and is Possible currently traffic analysis and determination of a traffic policy with historical analysis.

• Smart Media Journal
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• v.10 no.1
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• pp.25-31
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• 2021

As the machine learning becomes more common, development of application using machine learning is actively increasing. In addition, research on machine learning platform to support development of application is also increasing. However, despite the increasing of research on machine learning platform, research on suitable load balancing for machine learning platform is insufficient. Therefore, in this paper, we propose a load balancing scheme that can be applied to machine learning distributed environment. The proposed scheme composes distributed servers in a level hash table structure and assigns machine learning task to the server in consideration of the performance of each server. We implemented distributed servers and experimented, and compared the performance with the existing hashing scheme. Compared with the existing hashing scheme, the proposed scheme showed an average 26% speed improvement, and more than 38% reduced the number of waiting tasks to assign to the server.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.6
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• pp.46-54
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• 2018

The Internet of Things (IoT) is an environment in which various devices provide services to users through communications. Because of the nature of the IoT, data are stored and distributed in heterogeneous information systems. In this situation, IoT end applications should be able to access data without having information on where the data are or what the type of storage is. This mechanism is called Service Discovery (SD). However, some problems arise, since the current SD architectures search for data in physical devices. First, turnaround time increases from searching for services based on physical location. Second, there is a need for a data structure to manage devices and services separately. These increase the administrator's service configuration complexity. As a result, the device-oriented SD structure is not suitable to the IoT. Therefore, we propose an SD structure called Name-based Service-centric Service Discovery (NSSD). NSSD provides name-based centralized SD and uses the IoT edge gateway as a cache server to speed up service discovery. Simulation results show that NSSD provides about twice the improvement in average turnaround time, compared to existing domain name system and distributed hash table SD architectures.

• Journal of KIISE:Databases
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• v.31 no.3
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• pp.261-273
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• 2004

Advances in information and communication technologies have been creating new classes of applications in the area of databases. For example, in moving object databases, which track positions of a lot of objects, or stream databases, which process data streams from a lot of sensors, data Processed in such database systems are usually changed very rapidly and continuously. However, traditional database systems have a problem in processing these rapidly and continuously changing data because they suppose that a data item stored in the database remains constant until It is explicitly modified. The problem becomes more serious in the R-tree, which is a typical index structure for multidimensional data, because modifying data in the R-tree can generate cascading node splits or merges. To process frequent updates more efficiently, we propose a novel update technique for the R-tree, which we call the leaf-update technique. If a new value of a data item lies within the leaf MBR that the data item belongs, the leaf-update technique changes the leaf node only, not whole of the tree. Using this leaf-update manner and the leaf-access hash table for direct access to leaf nodes, the proposed technique can reduce update cost greatly. In addition, the leaf-update technique can be adopted in diverse variants of the R-tree and various applications that use the R-tree since it is based on the R-tree and it guarantees the correctness of the R-tree. In this paper, we prove the effectiveness of the leaf-update techniques theoretically and present experimental results that show that our technique outperforms traditional one.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.46 no.4
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• pp.21-30
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• 2009

Fusion flash memory such as OneNAND$^{TM}$ is popular as a ubiquitous storage device for embedded systems because it has advantages of NAND and NOR flash memory that it can support large capacity, fast read/write performance and XIP(eXecute-In-Place). Besides, OneNAND$^{TM}$ provides not only advantages of hybrid structure but also multi-block erase function that improves slow erase performance by erasing the multiple blocks simultaneously. But traditional NAND Flash Translation Layer may not fully support it because the garbage collection of traditional FTL only considers a few block as victim block and erases them. In this paper, we propose an Erase Group Flash Translation Layer for improving multi-block erase function. EGFTL uses a superblock scheme for enhancing garbage collection performance and invalid block management to erase multiple blocks simultaneously. Also, it uses clustered hash table to improve the address translation performance of the superblock scheme. The experimental results show that the garbage collection performance of EGFTL is 30% higher than those of traditional FTLs, and the address translation performance of EGFTL is 5% higher than that of Superblock scheme.