There has been much interest in a spatial query which acquires sensor
readings from sensor nodes inside specified geographical area of
interests. A centralized approach performs the spatial query at a server
after acquiring all sensor readings. However, it incurs high wireless
transmission cost in accessing all sensor nodes. Therefore, various
in-network spatial search methods have been proposed, which focus on
reducing the wireless transmission cost. However, the in-network methods
sometimes incur unnecessary wireless transmissions because of dead
space, which is spatially indexed but does not contain real data. In
this paper, we propose a hybrid spatial query processing algorithm which
removes the unnecessary wireless transmissions. The main idea of the
hybrid algorithm is to find results of a spatial query at a server in
advance and use the results in removing the unnecessary wireless
transmissions at a sensor network. We compare the in-network method
through several experiments and clarify our algorithm's remarkable
"이러한 Centralized 방법을 보완하기 위한 방법으로 In-network 질의처리 방법들이 제안 되었는데, 이 방법은 공간질의가 서버가 아니라 센 서노드에서 분산되어 처리되는 특징을 가지고 있다. 구체적으로 In-network 질의처리 방법과 관련하여 지금까지 다양한 분산 공간질의처리 알고리즘         "
[Show abstract][Hide abstract] ABSTRACT: Recently, there has been much interest in the spatial query which energy-efficiently acquires sensor readings from sensor nodes inside specified geographical area of interests. The centralized approach which performs the spatial query at a server after acquiring all sensor readings, though simple, it incurs high wireless transmission cost in accessing all sensor nodes. In order to remove the high wireless transmission cost, various in-network spatial indexing schemes have been proposed. They have focused on reducing the transmission cost by performing distributed spatial filtering on sensor nodes. However, these in-network spatial indexing schemes have a problem which cannot optimize both the spatial filtering and the wireless routing among sensor nodes, because these schemes have been developed by simply applying the existing spatial indexing schemes into the in-network environment. Therefore, we propose a new distributed spatial indexing scheme of the GR-tree. The GR-tree which form s a MBR-based tree structure, can reduce the wireless transmission cost by optimizing both the efficient spatial filtering and the wireless routing. Finally, we compare the existing spatial indexing scheme through extensive experiments and clarify our approach's distinguished features.
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