• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.17 no.2
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• pp.177-187
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• 1999

Up to date, in many application fields of GSIS, we usually have used vector-based spatial overlay or grid-based spatial algebra for extraction and analysis of spatial data. But, because these methods are based on traditional crisp set, concept which is used these methods. shows that many kinds of spatial data are partitioned with sharp boundary. That is not agree with spatial distribution pattern of data in the real world. Therefore, it has a error that a region or object is restricted within only one attribution (One-Entity-one-value). In this study, for improving previous methods that deal with spatial data based on crisp set, we are suggested to apply into spatial overlay process the concept of fuzzy set which is good for expressing the boundary vagueness or ambiguity of spatial data. two methods be given. First method is a fuzzy interval partition by fuzzy subsets in case of spatially continuous data, and second method is fuzzy boundary set applied on categorical data. with a case study to get a land suitability map for the development site selection of new town, we compared results between Boolean analysis method and fuzzy spatial overlay method. And as a result, we could find out that suitability map using fuzzy spatial overlay method provide more reasonable information about development site of new town, and is more adequate type in the aspect of presentation.

• Journal of KIISE:Information Networking
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• v.33 no.1
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• pp.76-90
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• 2006

Sensor network consists of a large number of sensor nodes that are densely deployed either inside the phenomenon or very close to it. The life time of each node in the sensor network significantly affects the life time of whole sensor network. A node which drained out its battery may incur the partition of whole network in some network topology The life time of each node depends on the battery capacity of each node. Therefore if all sensor nodes in the network live evenly long, the life time of the network will be longer. In this paper, we propose Cluster-Based Power-Efficient Routing (CBPER) Protocol which provides scalable and efficient data delivery to multiple mobile sinks. Previous r(luting protocols, such as Directed Diffusion and TTDD, need to flood many control packets to support multiple mobile sinks and many sources, causing nodes to consume their battery. In CBPER, we use the fact that sensor nodes are stationary and location-aware to construct and maintain the permanent grid structure, which makes nodes live longer by reducing the number of the flooding control packets. We have evaluated CBPER performance with TTDD. Our results show that CBPER is more power-efficient routing protocol than TTDD.