earticle

논문검색

Efficient Mining Maximal Constant Row Bicluster in Function-resource Matrix for IMA Safety Analysis

초록

영어

Integrated Modular Avionics (IMA) uses task synthesis, function fusion and resource integration to achieve the goal of low cost, high efficiency, high efficacy, high performance and high reliability. However, safety issue is caused in the system integration process. In this paper, firstly, we use data mining technology to describe resource-layer safety model, function-layer safety model and task-layer safety model; secondly, we proposed an efficient bicluster mining algorithm: LowCluster, to effectively mine all the maximal constant row biclusters with low usage rate in real-valued function-resource matrix for IMA safety analysis. In LowCluster algorithm, a sample weighted graph is constructed firstly, it includes all resource collections between both samples which meet the definition of low usage rate; then, all the maximal constant row biclusters with low usage rate are mined using sample-growth and depth-first method in the sample weighted graph. In order to improve the mining efficiency, LowCluster algorithm uses pruning strategy to ensure the mining of maximal bicluster without candidate maintenance. The experimental results show that LowCluster algorithm is more efficient than traditional constant row biclustering algorithm, and using our proposed LowCluster algorithm can find the error reason when executing more functions, which will help to improve system safety analysis.

목차

Abstract
 1. Introduction
  1.1 System Safety Design
  1.2 IMA System Safety Problems
  1.3 Our Contributes
 2. IMA System Safety Analysis
  2.1 Safety Problem of IMA-based Resource Sharing Integration
  2.2 Safety Problem of IMA-based Function Information Fusion
  2.3 Safety Problem of IMA-based Task Organization Synthesis
 3. Mining Maximal Constant Row Biclusters
  3.1 Problem Definition
  3.2 The LowCluster Algorithm
 4. Experimental Results
  4.1 Performance Analysis
  4.2 Safety Analysis
 5. Conclusion
 Acknowledgements
 References

저자정보

  • Miao Wang Science and Technology on Avionics Integration Laboratory, Shanghai, China, China National Aeronautical Radio Electronics Research Institute, Shanghai, China
  • Zhiyong Xiong Science and Technology on Avionics Integration Laboratory, Shanghai, China, China National Aeronautical Radio Electronics Research Institute, Shanghai, China
  • Liang Xu China National Aeronautical Radio Electronics Research Institute, Shanghai, China
  • Lihua Zhang Science and Technology on Avionics Integration Laboratory, Shanghai, China, China National Aeronautical Radio Electronics Research Institute, Shanghai, China
  • Qingfan Gu China National Aeronautical Radio Electronics Research Institute, Shanghai, China
  • Guoqing Wang Science and Technology on Avionics Integration Laboratory, Shanghai, China, China National Aeronautical Radio Electronics Research Institute, Shanghai, China

참고문헌

자료제공 : 네이버학술정보

    함께 이용한 논문

      ※ 원문제공기관과의 협약기간이 종료되어 열람이 제한될 수 있습니다.

      0개의 논문이 장바구니에 담겼습니다.