Earticle

Recently, with the dramatic popular of geo-social networks and location based services (LBS), more and more mobile users are willing to enjoy the proximity services, which is a friend-alarm when the buddies happen to be in proximity. However, the services provider (SP) and some compromised buddies could try to steal the user’s exact location information. Hence, location privacy preserving is still a challenge question in proximity based services. Unfortunately, existing methods only consider Euclidean distance to calculate neighbors, which would bring great deviation for distance measurement in the actual terrain. To my knowledge, this article is the first time extending to the 3D surface and proposes a novel technique for the privacy-preserving proximity services. The technique utilizes simplicial triangulation decomposition on 3D surface, and the user's location is generalized with a triangular area space, then a more precise proximity distance measurement method based on the triangle fractal is proposed. Next, we design a privacy-preserving proximity query protocol, which provide complete privacy with respect to the SP and the buddies. Final, the experiments shows that our methods have practicality in the services quantity and privacy.

도시표면의 건물정보는 빗물의 유출경로이며 또한 격자기반의 수치해석을 위한 빗물흐름과 건물 외곽을 구분하는 경계조건에 해당한다. 경계조건인 건물자료의 왜곡 최소화는 수치해석 결과의 사실성 확보를 위한 필수적 과정이다. 격자기반의 래스터 전환은 건물자료의 왜곡을 유발하기 때문에 왜곡의 정도를 완화시키기 위한 전처리로 건물 일반화가 필요하다. 본 연구의 목적은 건물 일반화가 일반주거지역의 빗물 유출경로 연속성에 미치는 영향을 분석하고 적정한 일반화 임계값과 수치해석 격자크기를 제시하고자 한다. 빗물 유출경로 연결성 평가를 위한 설명변수로는 일반화 임계값과 수치계산 격자크기를 사용하는 한편 종속변수로는 격자망의 단절 개수와 단절면적을 사용했다. 적정한 격자크기와 일반화 임계값 선정은 임의 격자크기와 임계값을 적용한 일반화 결과로부터 산출된 건물 면적 변화율과 단절 면적 변화율 각각을 비교하고 크기가 가장 낮은 것으로 하였다. 적정 임계값과 격자크기 범위는 각각 3m와 $5{\times}5m{\sim}10{\times}10m$ 이었다. 이를 적용한 결과 건물면적 증가율은 5%이하 그리고 단절면적 감소율은 94.4%이상이었다. 대상지 토지용도를 구분한 건물 일반화 모의 결과, 아파트 단지인 3종의 건물면적과 빗물 유출경로 연결성은 임계값 10m이하에서 크게 변하지 않았다. 한편 개별 주택인 2종 지역에서는 임계값 3m와 격자크기 $5{\times}5m$을 적용한 모의결과는 단절면적의 감소와 양호한 유출경로 연결성을 보였다.

The space between urban buildings becomes a waterway during rain events and requires a boundary condition in numerical calculations on grids to separate overland storm flows from building areas. Minimization of the building data distortion as a boundary condition is a necessary step for generating accurate calculation results. A building generalization is used to reduce the distortion of building shapes and areas during a raster conversion. The objective of this study was to provide the appropriate threshold value for building generalization and grid size in a numerical calculation. The impact of building generation on the connectivity of urban storm waterways were analyzed for a general residential area. The building generalization threshold value and the grid size for numerical analysis were selected as the independent variables for analysis, and the number and area of sinks were used as the dependent variables. The values for the building generalization threshold and grid size were taken as the optimal values to maximize the building area and minimize the sink area. With a 3 m generalization threshold, sets of $5{\times}5m$ to $10{\times}10m$ caused 5% less building area and 94.4% more sink area compared to the original values. Two sites representing general residential area types 2 and 3 were used to verify building generalization thresholds for improving the connectivity of storm waterways. It is clear that the recommended values are effective for reducing the distortion in both building and sink areas.