• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.8A
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• pp.942-949
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• 2004

This paper proposes and analyzes the anti-collision algorithm in Ubiquitous ID system. We mathematically compares the performance of the proposed algorithm with that of binary search algorithm, slotted binary tree algorithm using time slot, and bit-by-bit binary tree algorithm proposed by Auto-ID center. We also validated analytic results using OPNET simulation. Based on the analytic results, comparing the proposed algorithm with bit-by-bit algorithm which is the best of existing algorithms, the performance of proposed algorithm is about 5% higher when the number of tags is 20, and 100% higher when the number of tags is 200.

• The KIPS Transactions:PartC
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• v.16C no.2
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• pp.267-274
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• 2009

For the implementation of a RFID system, an anti-collision algorithm is required to identify multiple tags within the range of a RFID Reader. There are two methods of anti-collision algorithms for the identification of multiple tags, conclusive algorithms based on tree and stochastic algorithms based on slotted ALOHA. In this paper, we propose a Dynamic Framed Slotted ALOHA-Slot Congestion(DFSA-SC) Algorithm. The proposed algorithm improves the efficiency of collision resolution. The performance of the proposed DFSA-SC algorithm is showed by simulation. The identification time of the proposed algorithm is shorter than that of the existing DFSA algorithm. Furthermore, when the bit duplication of the tagID is higher, the proposed algorithm is more efficient than Query Tree algorithm.

• Journal of Computing Science and Engineering
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• v.9 no.4
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• pp.163-176
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• 2015

Self-organization of distributed wireless sensor nodes is a critical issue in wireless sensor networks (WSNs), since each sensor node has limited energy, bandwidth, and scalability. These issues prevent sensor nodes from actively collaborating with the other types of sensor nodes deployed in a typical heterogeneous and somewhat hostile environment. The automated self-organization of a WSN becomes more challenging as the number of sensor nodes increases in the network. In this paper, we propose a dynamic self-organized architecture that combines tree topology with a drawn-grid algorithm to automate the self-organization process for WSNs. In order to make our proposed architecture scalable, we assume that all participating active sensor nodes are unaware of their primary locations. In particular, this paper presents two algorithms called active-tree and drawn-grid. The proposed active-tree algorithm uses a tree topology to assign node IDs and define different roles to each participating sensor node. On the other hand, the drawn-grid algorithm divides the sensor nodes into cells with respect to the radio coverage area and the specific roles assigned by the active-tree algorithm. Thus, both proposed algorithms collaborate with each other to automate the self-organizing process for WSNs. The numerical and simulation results demonstrate that the proposed dynamic architecture performs much better than a static architecture in terms of the self-organization of wireless sensor nodes and energy consumption.

• Journal of Communications and Networks
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• v.9 no.4
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• pp.499-510
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• 2007

Shortest path tree(SPT) construction is essential in high performance routing in an interior network using link state protocols. When some links have new state values, SPTs may be rebuilt, but the total rebuilding of the SPT in a static way for a large computer network is not only computationally expensive, unnecessary modifications can cause routing table instability. This paper presents a new update algorithm, dynamic shortest path tree(DSPT) that is computationally economical and that maintains the unmodified nodes mostly from an old SPT to a new SPT. The proposed algorithm reduces redundancy using a dynamic update approach where an edge becomes the significant edge when it is extracted from a built edge list Q. The average number of significant edges are identified through probability analysis based on an arbitrary tree structure. An update derived from significant edges is more efficient because the DSPT algorithm neglect most other redundant edges that do not participate in the construction of a new SPT. Our complexity analysis and experimental results show that DSPT is faster than other known methods. It can also be extended to solve the SPT updating problem in a graph with negative weight edges.

• Journal of the Korea Safety Management & Science
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• v.7 no.5
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• pp.1-8
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• 2005

The consequences of rapid industrial advancement, diversified types of business and unexpected industrial accidents have caused a lot of damage to many unspecified persons both in a human way and a material way Although various previous studies have been analyzed to prevent industrial accidents, these studies only provide managerial and educational policies using frequency analysis and comparative analysis based on data from past industrial accidents. The main objective of this study is to find an optimal algorithm for data analysis of industrial accidents and this paper provides a comparative analysis of 4 kinds of algorithms including CHAID, CART, C4.5, and QUEST. Decision tree algorithm is utilized to predict results using objective and quantified data as a typical technique of data mining. Enterprise Miner of SAS and AnswerTree of SPSS will be used to evaluate the validity of the results of the four algorithms. The sample for this work chosen from 19,574 data related to construction industries during three years ($2002\sim2004$) in Korea.

• Korean Journal of Artificial Intelligence
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• v.10 no.1
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• pp.9-14
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• 2022

The demand for public bicycles operated by the Seoul Metropolitan Government is increasing every year. The size of the Seoul public bicycle project, which first started with about 5,600 units, increased to 3,7500 units as of September 2021, and the number of members is also increasing every year. However, as the size of the project grows, excessive budget spending and deficit problems are emerging for public bicycle projects, and new bicycles, rental office costs, and bicycle maintenance costs are blamed for the deficit. In this paper, the Azure Machine Learning Studio program and the Boosted Decision Tree Regression technique are used to predict the number of public bicycle rental over environmental factors and time. Predicted results it was confirmed that the demand for public bicycles was high in the season except for winter, and the demand for public bicycles was the highest at 6 p.m. In addition, in this paper compare four additional regression algorithms in addition to the Boosted Decision Tree Regression algorithm to measure algorithm performance. The results showed high accuracy in the order of the First Boosted Decision Tree Regression Algorithm (0.878802), second Decision Forest Regression (0.838232), third Poison Regression (0.62699), and fourth Linear Regression (0.618773). Based on these predictions, it is expected that more public bicycles will be placed at rental stations near public transportation to meet the growing demand for commuting hours and that more bicycles will be placed in rental stations in summer than winter and the life of bicycles can be extended in winter.

• Proceedings of the IEEK Conference
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• 2001.06a
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• pp.337-340
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• 2001

This paper presented a new structure of RSA cryptosystem using modified Montgomery algorithm and CSA(Carry Save Adder) tree. Montgomery algorithm was modified to a radix-4 modified Booth algorithm. By appling radix-4 modified Booth algorithm and CSA tree to modular multiplication, a clock cycle for modular multiplication has been reduced to (n＋3)/2 and carry propagation has been removed from the cell structure of modular multiplier. That is, the connection efficiency of full adders is enhanced.

• Journal of Institute of Control, Robotics and Systems
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• v.12 no.11
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• pp.1138-1143
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• 2006

Sensor deployment is an important issue in the mobile wireless sensor network. In this paper, we propose a deployment algorithm for mobile sensor network to spread out mobile sensor nodes widely as well as regularly. Since the proposed algorithm uses tree topology in deploying the sensor nodes, calculating power as well as spreading speed can be reduced compare to other deployment algorithms. The performance of the proposed algorithm is simulated using NS-2 simulator and demonstrated.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.12 no.3
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• pp.51-61
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• 2012

This paper suggests an algorithm that obtains Directed Graph Minimum Spanning Tree (DMST), using Prim MST algorithm which is Minimum Spanning Tree (MST) of undirected graph. At first, I suggested the Prim DMST algorithm that chooses Minimum Weight Arc(MWA) from out-going nodes from each node, considering differences between undirected graph and directed graph. Next, I proved a disadvantage of Prim DMST algorithm and Chu-Liu/Edmonds DMST (typical representative DMST) of not being able to find DMST, applying them to 3 real graphs. Last, as an algorithm that can always find DMST, an advanced Prim DMST is suggested. The Prim DMST algorithm uses a method of choosing MWA among out-going arcs of each node. On the other hand, the advanced Prim DMST algorithm uses a method of choosing a coinciding arc from the out-going and in-going arcs of each node. And if there is no coinciding arc, it chooses MWA from the out-going arcs from each node. Applying the suggested algorithm to 17 different graphs, it succeeded in finding the same DMST as that found by Chu-Liu/Edmonds DMST algorithm. Also, it does not require such a complicated calculation as that of Chu-Liu/Edmonds DMST algorithm to delete the cycle, and it takes less time for process than Prim DMST algorithm.

• The KIPS Transactions:PartC
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• v.10C no.3
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• pp.367-376
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• 2003

This study deals with the DCMST (Delay constrained Capacitated Minimum Spanning Tree) problem applied in the topological design of local networks or finding several communication paths from root node. While the traditional CMST problem has only the traffic capacity constraint served by a port of root node, the DCMST problem has the additional mean delay constraint of network. The DCMST problem consists of finding a set of spanning trees to link end-nodes to the root node satisfying the traffic requirements at end-nodes and the required mean delay of network. The objective function of problem is to minimize the total link cost. This paper presents two-phased heuristic algorithm, which consists of node exchange, and node shift algorithm based on the trade-off criterions, and mean delay algorithm. Actual computational experience and performance analysis show that the proposed algorithm can produce better solution than the existing algorithm for the CMST problem to consider the mean delay constraint in terms of cost.