• 제목/요약/키워드: Boundary node identification

검색결과 3건 처리시간 0.02초

A City-Level Boundary Nodes Identification Algorithm Based on Bidirectional Approaching

  • Tao, Zhiyuan;Liu, Fenlin;Liu, Yan;Luo, Xiangyang
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제15권8호
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    • pp.2764-2782
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    • 2021
  • Existing city-level boundary nodes identification methods need to locate all IP addresses on the path to differentiate which IP is the boundary node. However, these methods are susceptible to time-delay, the accuracy of location information and other factors, and the resource consumption of locating all IPes is tremendous. To improve the recognition rate and reduce the locating cost, this paper proposes an algorithm for city-level boundary node identification based on bidirectional approaching. Different from the existing methods based on time-delay information and location results, the proposed algorithm uses topological analysis to construct a set of candidate boundary nodes and then identifies the boundary nodes. The proposed algorithm can identify the boundary of the target city network without high-precision location information and dramatically reduces resource consumption compared with the traditional algorithm. Meanwhile, it can label some errors in the existing IP address database. Based on 45,182,326 measurement results from Zhengzhou, Chengdu and Hangzhou in China and New York, Los Angeles and Dallas in the United States, the experimental results show that: The algorithm can accurately identify the city boundary nodes using only 20.33% location resources, and more than 80.29% of the boundary nodes can be mined with a precision of more than 70.73%.

절 경계와 트리 거리를 사용한 2단계 부분 의미 분석 시스템 (A Two-Phase Shallow Semantic Parsing System Using Clause Boundary Information and Tree Distance)

  • 박경미;황규백
    • 한국정보과학회논문지:컴퓨팅의 실제 및 레터
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    • 제16권5호
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    • pp.531-540
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    • 2010
  • 본 논문은 최대 엔트로피 모형에 기반한 두 단계 부분 의미 분석 방법을 제안한다. 먼저, 의미 논항의 경계를 인식하고, 그 다음 단계에서 확인된 논항에 적절한 의미역을 할당한다. 두 단계 부분 의미 분석에서는 두 번째 단계인 논항 분류가 논항 확인 단계의 결과에 기반하여 수행되기 때문에 논항 확인의 성능이 매우 중요하다. 본 논문은 논항 확인의 성능을 향상시키기 위하여 논항 확인의 전처리 단계에 구문 지식을 통합한다. 구체적으로, 절 인식 결과로부터 술어의 인접절 및 상위절들을 확인하고, 구문 분석 결과로부터 술어의 부모 노드로부터 구문 구성 요소의 부모 노드까지의 트리 거리를 추출하여 전처리 단계에서 활용한다. 실험을 통해, 구문 지식을 활용하는 것이 부분 의미 분석 성능에 기여함과 제안하는 두 단계 방법이 한 단계 방법보다 우수한 성능을 낼 수 있음을 보인다.

Self-Identification of Boundary's Nodes in Wireless Sensor Networks

  • Moustafa, Kouider Elouahed;Hafid, Haffaf
    • Journal of Information Processing Systems
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    • 제13권1호
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    • pp.128-140
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    • 2017
  • The wireless sensor networks (WSNs) became a very essential tool in borders and military zones surveillance, for this reason specific applications have been developed. Surveillance is usually accomplished through the deployment of nodes in a random way providing heterogeneous topologies. However, the process of the identification of all nodes located on the network's outer edge is very long and energy-consuming. Before any other activities on such sensitive networks, we have to identify the border nodes by means of specific algorithms. In this paper, a solution is proposed to solve the problem of energy and time consumption in detecting border nodes by means of node selection. This mechanism is designed with several starter nodes in order to reduce time, number of exchanged packets and then, energy consumption. This method consists of three phases: the first one is to detect triggers which serve to start the mechanism of boundary nodes (BNs) detection, the second is to detect the whole border, and the third is to exclude each BN from the routing tables of all its neighbors so that it cannot be used for the routing.