• Title/Summary/Keyword: Buffer based network matching

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A Study on Updating Methodology of Road Network data using Buffer-based Network Matching (버퍼 기반 네트워크 매칭을 이용한 도로 데이터 갱신기법 연구)

  • Park, Woo-Jin
    • Journal of Cadastre & Land InformatiX
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    • v.44 no.1
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    • pp.127-138
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    • 2014
  • It can be effective to extract and apply the updated information from the newly updated map data for updating road data of topographic map. In this study, update target data and update reference data are overlaid and the update objects are explored using network matching technique. And the network objects are classified into five matching and update cases and the update processes for each case are applied to the test data. For this study, road centerline data of digital topographic map is used as an update target data and road data of Korean Address Information System is used as an update reference data. The buffer-based network matching method is applied to the two data and the matching and update cases are classified after calculating the overlaid ratio of length. The newly updated road centerline data of digital topographic map is generated from the application of update process for each case. As a result, the update information can be extracted from the different map dataset and applied to the road network data updating.

A Fast String Matching Scheme without using Buffer for Linux Netfilter based Internet Worm Detection (리눅스 넷필터 기반의 인터넷 웜 탐지에서 버퍼를 이용하지 않는 빠른 스트링 매칭 방법)

  • Kwak, Hu-Keun;Chung, Kyu-Sik
    • The KIPS Transactions:PartC
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    • v.13C no.7 s.110
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    • pp.821-830
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    • 2006
  • As internet worms are spread out worldwide, the detection and filtering of worms becomes one of hot issues in the internet security. As one of implementation methods to detect worms, the Linux Netfilter kernel module can be used. Its basic operation for worm detection is a string matching where coming packet(s) on the network is/are compared with predefined worm signatures(patterns). A worm can appear in a packet or in two (or more) succeeding packets where some part of worm is in the first packet and its remaining part is in its succeeding packet(s). Assuming that the maximum length of a worm pattern is less than 1024 bytes, we need to perform a string matching up to two succeeding packets of 2048 bytes. To do so, Linux Netfilter keeps the previous packet in buffer and performs matching with a combined 2048 byte string of the buffered packet and current packet. As the number of concurrent connections to be handled in the worm detection system increases, the total size of buffer (memory) increases and string matching speed becomes low In this paper, to reduce the memory buffer size and get higher speed of string matching, we propose a string matching scheme without using buffer. The proposed scheme keeps the partial matching result of the previous packet with signatures and has no buffering for previous packet. The partial matching information is used to detect a worm in the two succeeding packets. We implemented the proposed scheme by modifying the Linux Netfilter. Then we compared the modified Linux Netfilter module with the original Linux Netfilter module. Experimental results show that the proposed scheme has 25% lower memory usage and 54% higher speed compared to the original scheme.

A Video Traffic Model based on the Shifting-Level Process (Part I : Modeling and the Effects of SRD and LRD on Queueing Behavior) (Shifting-Level Process에 기반한 영상트래픽 모델 (1부: 모델링과 대기체계 영향 분석))

  • 안희준;강상혁;김재균
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.24 no.10B
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    • pp.1971-1978
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    • 1999
  • In this paper, we study the effects of long-range dependence (LRD) in VBR video traffic on queueing system. This paper consists of Part I and II. In Part I, we present a (LRD) video traffic model based on the shifting-level (SL) process. We observe that the ACF of an empirical video trace is accurately captured by the shifting-level process with compound correlation (SLCC): an exponential function in short range and a hyperbolic function in long range. We present an accurate parameter matching algorithm for video traffic. In the Part II, we offer the queueing analysis of SL/D/1/K called ‘quantization reduction method’. Comparing the queueing performances of the DAR(1) model and the SLCC with that of a real video trace, we identify the effects of SRD and LRD in VBR video traffic on queueing performance. Simulation results show that Markoivian models can estimate network performances fairly accurately under a moderate traffic load and buffer condition, whereas LRD may have a significant effect on queueing behavior under a heavy traffic load and large buffer condition.

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