• The KIPS Transactions:PartD
• /
• v.14D no.1 s.111
• /
• pp.21-34
• /
• 2007

According to recent rapid price drop and capacity growth of main memory, the number of applications on main memory databases is dramatically increasing. Cache miss, which means a phenomenon that the data required by CPU is not resident in cache and is accessed from main memory, is one of the major causes of performance degradation of main memory databases. Several cache-conscious trees have been proposed for reducing cache miss and making the most use of cache in main memory databases. Since each cache-conscious tree has its own unique features, more than one cache-conscious tree can be used in a single application depending on the application's requirement. Moreover, if there is no existing cache-conscious tree that satisfies the application's requirement, we should implement a new cache-conscious tree only for the application's sake. In this paper, we propose the cache-conscious generalized search tree (CC-GiST). The CC-GiST is an extension of the disk-based generalized search tree (GiST) [HNP95] to be tache-conscious, and provides the entire common features and algorithms in the existing cache-conscious trees including pointer compression and key compression techniques. For implementing a cache-conscious tree based on the CC-GiST proposed in this paper, one should implement only a few functions specific to the cache-conscious tree. We show how to implement the most representative cache-conscious trees such as the CSB+-tree, the pkB-tree, and the CR-tree based on the CC-GiST. The CC-GiST eliminates the troublesomeness caused by managing mire than one cache-conscious tree in an application, and provides a framework for efficiently implementing arbitrary cache-conscious trees with new features.

• KIEE International Transactions on Power Engineering
• /
• v.5A no.2
• /
• pp.177-185
• /
• 2005

This paper proposes an expert system that can enhance the accuracy of real-time bus reconfiguration strategy by adopting the local minimum tree search method and that can minimize the spreading effect of the fault by considering the operating condition when a main transformer fault occurs in an automated substation. The local minimum tree search method is used to expand the best-first search method. This method has the advantage that it can improve the solution performance within the limits of the real-time condition. The inference strategy proposed expert system consists of two stages. The first stage determines the switching candidate set by searching possible switching candidates starting from the main transformer or busbar related to the event. The second stage determines the rational real-time bus reconfiguration strategy based on heuristic rules from the obtained switching candidate set. Also, this paper proposes generalized distribution substation modeling using graph theory, and a substation database based on the study results is designed.

• Journal of the Korean Operations Research and Management Science Society
• /
• v.28 no.4
• /
• pp.191-198
• /
• 2003

The generalized knapsack problem or gknap is the combinatorial optimization problem of optimizing a nonnegative linear function over the integral hull of the intersection of a polynomially separable 0-1 polytope and a knapsack constraint. The knapsack, the restricted shortest path, and the constrained spanning tree problem are a partial list of gknap. More interesting1y, all the problem that are known to have a fully polynomial approximation scheme, or FPTAS are gknap. We establish some necessary and sufficient conditions for a gknap to admit an FPTAS. To do so, we recapture the standard scaling and approximate binary search techniques in the framework of gknap. This also enables us to find a weaker sufficient condition than the strong NP-hardness that a gknap does not have an FPTAS. Finally, we apply the conditions to explore the fully polynomial approximability of the constrained spanning problem whose fully polynomial approximability is still open.

• The Transactions of the Korean Institute of Electrical Engineers A
• /
• v.53 no.10
• /
• pp.565-572
• /
• 2004

This paper proposes an expert system which can enhance the accuracy of real-time bus reconfiguration strategy by adopting local minimum tree search method and minimize the spreading effect of the fault by considering totally the operating condition when a main transformer fault occurs in the automated substation. The local minimum tree search method to expand the best-first search method. This method has an advantage which can improve the performance of solution within the limits of the real-time condition. The inference strategy proposed expert system consists of two stages. The first stage determines the switching candidate set by searching possible switching candidates starting from the main transformer or busbar related to the event. And, second stage determines the rational real-time bus reconfiguration strategy based on heuristic rules for the obtained switching candidate set. Also, this paper studies the generalized distribution substation modelling using graph theory and a substation database is designed based on the study result. The inference engine of the expert system and the substation database is implemented in MFC function of Visual C++. Finally, the performance and effectiveness of the proposed expert system is verified by comparing the best-first search solution and local minimum tree search solution based on diversity event simulations for typical distribution substation.

• ETRI Journal
• /
• v.36 no.4
• /
• pp.564-571
• /
• 2014

Sphere decoding (SD) for multiple-input and multiple-output systems is a well-recognized approach for achieving near-maximum likelihood performance with reduced complexity. SD is a tree search process, whereby a large number of nodes can be searched in an effort to find an estimation of a transmitted symbol vector. In this paper, a simple and generalized approach called layer pruning is proposed to achieve complexity reduction in SD. Pruning a layer from a search process reduces the total number of nodes in a sphere search. The symbols corresponding to the pruned layer are obtained by adopting a QRM-MLD receiver. Simulation results show that the proposed method reduces the number of nodes to be searched for decoding the transmitted symbols by maintaining negligible performance loss. The proposed technique reduces the complexity by 35% to 42% in the low and medium signal-to-noise ratio regime. To demonstrate the potential of our method, we compare the results with another well-known method - namely, probabilistic tree pruning SD.

• Journal of the Korean Association of Geographic Information Studies
• /
• v.8 no.1
• /
• pp.63-74
• /
• 2005

The telematics device, which is a typical embedded system on the transportation or vehicle, requires the embedded spatial DBMS based on RTOS (Real Time Operating System) for processing the huge spatial data in real time. This spatial DBMS can be developed very easily by SQL3 functions of the ORDBMS such as UDT (user-defined type) and UDF (user-defined function). However, developing index suitable for the embedded spatial DBMS is very difficult. This is due to the fact that there is no built-in SQL3 functions to construct spatial indexes. In this study, we compare and analyze both Generalized Search Tree and Relational Indexing methods which are suggested as common ways of developing User-Defined Indexes nowadays. Two implementations of R-Tree based on each method were done and region query performance test results were evaluated for suggesting a suitable indexing method of an embedded spatial DBMS, especially for telematics devices.

• ETRI Journal
• /
• v.41 no.2
• /
• pp.145-159
• /
• 2019

To reduce the number of radio frequency (RF) chains in multiple input multiple output (MIMO) systems, generalized spatial modulation (GSM) techniques have been proposed in the literature. In this paper, we propose a zero-forcing (ZF)-based detector, which performs an initial pruning of the search tree that will be considered as the initial condition in a sphere decoding (SD) algorithm. The proposed method significantly reduces the computational complexity of GSM systems while achieving a near maximum likelihood (ML) performance. We analyze the performance of the proposed method and provide an analytic performance difference between the proposed method and the ML detector. Simulation results show that the performance of the proposed method is very close to that of the ML detector, while achieving a significant computational complexity reduction in comparison with the conventional SD method, in terms of the number of visited nodes. We also present some simulations to assess the accuracy of our theoretical results.

• Proceedings of the IEEK Conference
• /
• 2002.07a
• /
• pp.58-61
• /
• 2002

In this paper, we present a new generalized k-Tree-based (CU/PE) allocation model to perform dynamic resource (CU/PE) allocation/deallocation decision for the reconfigurable MSIMD/MIMD multi-dimensional (k-D) mesh-connected architectures. Those reconfigurable multi-SIMD/MIMD systems allow dynamic modes of executing tasks, which are SIMD and MIMD. The MIMD task requires only the free sub-system; however the SIMD task needs not only the free sub-system but also the corresponding free CU. In our new k-Tree-based (CU/PE) allocation model, we introduce two best-fit heuristics for the CU allocation decision: 1) the CU depth first search (CU-DFS) in O(kN$_{f}$ ) time and 2) the CU adjacent search (CU-AS) in O(k2$^{k}$ ) time. By the simulation study, the system performance of these two CU allocation strategies was also investigated. Our simulation results showed that the CU-AS and CU-DFS strategies performed the same system performance when applied for the reconfigurable MSIMD/MIMD 2-D and 3-D mesh-connected architectures.

• Proceedings of the Korean Operations and Management Science Society Conference
• /
• 2003.11a
• /
• pp.93-96
• /
• 2003

The generalized knapsack problem, or gknap is the combinatorial optimization problem of optimizing a nonnegative linear functional over the integral hull of the intersection of a polynomially separable 0 - 1 polytope and a knapsack constraint. Among many potential applications, the knapsack, the restricted shortest path, and the restricted spanning tree problem are such examples. We establish some necessary and sufficient conditions for a gknap to admit a fully polynomial approximation scheme, or FPTAS, To do so, we recapture the scaling and approximate binary search techniques in the framework of gknap. This also enables us to find a condition that a gknap does not have an FP-TAS. This condition is more general than the strong NP-hardness.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.12 no.1
• /
• pp.451-458
• /
• 2011

In order to provide the optimal location based services such as the optimal moving path search or the scheduling pattern prediction, the extraction of significant moving pattern which is considered the temporal and spatial properties of the location-based historical data of the moving objects is essential. In this paper, for the extraction of significant moving pattern we propose the location generalization method which translates the location attributes of moving object into the spatial scope information based on $R^*$-tree for more efficient patterning the continuous changes of the location of moving objects and for indexing to the 2-dimensional spatial scope. The proposed method generates the moving sequences which is satisfied the constraints of the time interval between the spatial scopes using the generalized spatial data, and extracts the significant moving patterns using them. And it can be an efficient method for the temporal pattern mining or the analysis of moving transition of the moving objects to provide the optimal location based services.