• 한국정보과학회논문지:정보통신
• /
• 제34권5호
• /
• pp.316-327
• /
• 2007

RFID는 RF신호를 이용하여 물체를 식별하는 가장 유망한 미래의 비접촉 기술이다. RFID 리더의 식별영역에 여러 개의 태그가 있는 경우, 리더의 질의에 대하여 모든 태그들이 동시에 응답을 하기 때문에 충돌이 발생되어 태그를 식별할 수 없게 된다. RFID에서 다중 태그 식별문제는 아주 중요한 핵심 기술로 이것을 해결하기 위해 슬롯기반 알로하 알고리즘, 트리 기반 알고리즘 등과 같은 충돌 방지 알고리즘이 제안되었다. 본 논문에서는 RFID 시스템에서 충돌 트리를 이용한 충돌트리 기반 충돌 방지알고리즘을 제안한다. 제안하는 방법은 효과적인 충돌 방지 메커니즘을 제공하며 메모리래스 알고리즘이다. 제안하는 충돌트리는 다중 태그 식별문제를 해결하기 위한 메커니즘으로 리더와 태그사이 질의와 응답과정에서 만들어진다. 리더가 k 비트로 구성된 프리픽스를 질의하면, 태그는 자신의 식별자와 프리픽스를 비교 하여 일치할 경우 식별자의 K+1 비트에서 마지막 비트까지 리더에게 전송한다. 시뮬레이션 결과에 따라 제안하는 충돌 트리 기반 충돌 방지 알고리즘이 기존의 트리 워킹 알고리즘이나 쿼리 트리 알고리즘보다 좋은 성능을 보임을 알 수 있다.

• 융합신호처리학회논문지
• /
• 제3권2호
• /
• pp.89-95
• /
• 2002

글로벌 라우팅(global routing)은 VLSI 설계 과정중의 하나로, 네트리스트의 모든 네트들을 연결하기 위하여 각 네트들을 라우팅 영역(routing area)에 할당시키는 문제이며, 글로벌 라우팅에서 최적의 해를 얻기 위해 maze routing 알고리즘, line-probe 알고리즘, shortest path 기반 알고리즘, Steiner tree 기반 알고리즘등이 이용된다. 본 논문에서는 라우팅 그래프에서 최단 경로 Steiner tree 탐색방법인 weighted network heuristic(WNH)과 이를 기반으로 하는 글로벌 라우팅 유전자 알고리즘(genetic algorithm; GA)을 제안하였으며, 제안한 방식을 시뮬레이티드 어닐링(SA) 방식과 비교, 분석하였다.

• 한국정보과학회논문지:정보통신
• /
• 제30권3호
• /
• pp.424-436
• /
• 2003

본 논문에서는 공유 트리에 기반에서 IP 멀티캐스팅을 위한 센트로이드 기반 백본코아트리 (Centroid-based Backbone Core Tree: CBCT) 생성 알고리즘을 제안한다 코아기반트리(Core Based Tree: CBT)는 공유 트리를 이용하여 멀티캐스트 자료를 전달하는 것으로 소스 기반 트리에 비하여 각 라우터가 유지해야 하는 상태 정보의 양이 적고, 적용하기 간단한 장점을 가지고 있지만, 코아 라우터(Core router) 선택이 어렵고, 멀티캐스트 트래픽이 코아로 집중되는 문제점을 가지고 있다. 백본코아트리(Backbone Core Tree: BCT)는 CBT의 단점을 보완하기 위해 제안되었다. BCT는 각 멀티캐스트 그룹마다 특정한 코아 라우터를 선정하지 않는 대신 코아라우터 후보들을 백본코아트리(BCT)로 연결하고, 이 트리를 통하여 코아라우터 후보들이 서로 협동하므로써 위의 두 가지 문제점을 해결한다. 이때 BCT를 어떻게 구성하는가에 따라 멀티캐스트 성능이 크게 변하게 된다. 본 논문에서는 백본코아라우터 후보들 및 이들을 연결하는 BCT를 생성하기 위해 네트워크의 최소 신장 트리와 센트로이드를 이용하는 효율적인 알고리즘 CBCT를 제시한다. 제안된 알고리즘의 성능평가를 위해서 CBT와 CBCT 프로토콜의 성능비교 결과를 보인다.

• Journal of Electrical Engineering and Technology
• /
• 제8권4호
• /
• pp.889-898
• /
• 2013

The shortest-path searching algorithm must not only find a global solution to the destination, but also solve a turn penalty problem (TPP) in an urban road transportation network (URTN). Although the Dijkstra algorithm (DA) as a representative node-based algorithm secures a global solution to the shortest path search (SPS) in the URTN by visiting all the possible paths to the destination, the DA does not solve the TPP and the slow execution speed problem (SEP) because it must search for the temporary minimum cost node. Potts and Oliver solved the TPP by modifying the visiting unit from a node to the link type of a tree-building algorithm like the DA. The Multi Tree Building Algorithm (MTBA), classified as a representative Link Based Algorithm (LBA), does not extricate the SEP because the MTBA must search many of the origin and destination links as well as the candidate links in order to find the SPS. In this paper, we propose a new Link-Based Single Tree Building Algorithm in order to reduce the SEP of the MTBA by applying the breaking rule to the LBA and also prove its usefulness by comparing the proposed with other algorithms such as the node-based DA and the link-based MTBA for the error rates and execution speeds.

• ETRI Journal
• /
• 제22권1호
• /
• pp.30-37
• /
• 2000

Existing tree construction mechanisms are classified into source-based trees and center-based trees. The source-based trees produce a source-rooted tree with a low delay. However, for the applications with multiple senders, the management overheads for routing tables and resource reservations are too high. The center-based trees are easy to implement and manage, but a priori configuration of candidate center nodes is required, and the optimization mature such as tree cost and delay is not considered. In this paper, we propose a new multicast tree building algorithm. The proposal algorithm basically builds a non-center based shared tree. In particular, any center node is not pre-configured. In the purposed algorithm, a multicast node among current tree nodes is suitably assigned to each incoming user: Such a node is selected in a fashion that tree cost and the maximum end-to-end delay on the tree are jointly minimized. The existing and proposed algorithms are compared by experiments. In the simulation results, it is shown that the proposed algorithm approximately provides the cost saving of 30% and the delay saving of 10%, compared to the existing approaches. In conclusion, we see that the cost and delay aspects for multicast trees can be improved at the cost of additional computations.

• 경영과학
• /
• 제23권1호
• /
• pp.63-74
• /
• 2006

Decision tree induction algorithm is one of the most widely used methods in classification problems. However, they could be trapped into a local minimum and have no reasonable means to escape from it if tree algorithm uses top-down search algorithm. Further, if irrelevant or redundant features are included in the data set, tree algorithms produces trees that are less accurate than those from the data set with only relevant features. We propose a hybrid algorithm to generate decision tree that uses genetic programming with sequentially selected features. Correlation-based Feature Selection (CFS) method is adopted to find relevant features which are fed to genetic programming sequentially to find optimal trees at each iteration. The new proposed algorithm produce simpler and more understandable decision trees as compared with other decision trees and it is also effective in producing similar or better trees with relatively smaller set of features in the view of cross-validation accuracy.

• Journal of Information Processing Systems
• /
• 제18권4호
• /
• pp.500-509
• /
• 2022

With the rapid development of educational informatization, teaching methods become diversified characteristics, but a large number of information data restrict the evaluation on teaching subject and object in terms of the effect of English education. Therefore, this study adopts the concept of incremental learning and eigenvalue interval algorithm to improve the weighted decision tree, and builds an English education effect evaluation model based on association rules. According to the results, the average accuracy of information classification of the improved decision tree algorithm is 96.18%, the classification error rate can be as low as 0.02%, and the anti-fitting performance is good. The classification error rate between the improved decision tree algorithm and the original decision tree does not exceed 1%. The proposed educational evaluation method can effectively provide early warning of academic situation analysis, and improve the teachers' professional skills in an accelerated manner and perfect the education system.

• 정보보호학회논문지
• /
• 제14권2호
• /
• pp.57-68
• /
• 2004

본 논문에서는 UOWHF의 도메인을 확장하기 위한 새로운 병렬 처리 알고리즘을 제안한다. 제시되는 알고리즘은 non-complete l-ary tree 에 기반을 두고 있으며 현재까지 최적의 키 길이를 가진 유일한 알고리즘인 Shoup 의 알고리즘과 동일한 최적의 키 길이를 가진다. 또한 Sarkar의 결과를 이용하여 본 논문에서 제시되는 알고리즘이 Shoup의 알고리즘과 함께 Sarkar가 제시한 도메인 확장 알고리즘들의 커다란 집합 중에서 가장 최적화된 키 길이를 가짐을 증명한다. 그러나 제안 알고리즘의 병렬처리능력은 complete tree에 기반 한 구성 방법들 보다 약간 비효율적이다. 그러나 만약 l이 점점 커진다면 알고리즘의 병렬처리능력도 complete tree 에 기반 한 방법들에 가까워진다.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• 제15권9호
• /
• pp.3138-3150
• /
• 2021

Multimedia services on the Internet are continuously increasing. Accordingly, the demand for a technology for efficiently delivering multimedia traffic is also constantly increasing. The multicast technique, that delivers the same content to several destinations, is constantly being developed. This technique delivers a content from a source to all destinations through the multicast tree. The multicast tree with low cost increases the utilization of network resources. However, the finding of the optimal multicast tree that has the minimum link costs is very difficult and its calculation complexity is the same as the complexity of the Steiner tree calculation which is NP-complete. Therefore, we need an effective way to obtain a multicast tree with low cost and less calculation time on SDN-based smart network platforms. In this paper, we propose a new multicast tree generation algorithm which produces a multicast tree using an agent trained by model-based meta reinforcement learning. Experiments verified that the proposed algorithm generated multicast trees in less time compared with existing approximation algorithms. It produced multicast trees with low cost in a dynamic network environment compared with the previous DQN-based algorithm.

• 대한산업공학회지
• /
• 제27권1호
• /
• pp.30-36
• /
• 2001

We present a new algorithm for mining association rules in the large database. Association rules are the relationships of items in the same transaction. These rules provide useful information for marketing. Since Apriori algorithm was introduced in 1994, many researchers have worked to improve Apriori algorithm. However, the drawback of Apriori-based algorithm is that it scans the transaction database repeatedly. The algorithm which we propose scans the database twice. The first scanning of the database collects frequent length l-itemsets. And then, the algorithm scans the database one more time to construct the data structure Common-Item Tree which stores the information about frequent itemsets. To find all frequent itemsets, the algorithm scans Common-Item Tree instead of the database. As scanning Common-Item Tree takes less time than scanning the database, the algorithm proposed is more efficient than Apriori-based algorithm.