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Context-aware Connectivity Analysis Method using Context Data Prediction Model in Delay Tolerant Networks

Delay Tolerant Networks에서 속성정보 예측 모델을 이용한 상황인식 연결성 분석 기법

  • Received : 2014.12.17
  • Accepted : 2015.02.02
  • Published : 2015.04.30

Abstract

In this paper, we propose EPCM(Efficient Prediction-based Context-awareness Matrix) algorithm analyzing connectivity by predicting cluster's context data such as velocity and direction. In the existing DTN, unrestricted relay node selection causes an increase of delay and packet loss. The overhead is occurred by limited storage and capability. Therefore, we propose the EPCM algorithm analyzing predicted context data using context matrix and adaptive revision weight, and selecting relay node by considering connectivity between cluster and base station. The proposed algorithm saves context data to the context matrix and analyzes context according to variation and predicts context data after revision from adaptive revision weight. From the simulation results, the EPCM algorithm provides the high packet delivery ratio by selecting relay node according to predicted context data matrix.

Keywords

Delay Tolerant Networks;Context-awareness;Connectivity;Matrix

References

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Acknowledgement

Supported by : 정보통신산업진흥원, 한국연구재단