Hybrid Spatial Query Processing between a Server and a Wireless Sensor Network.

IEICE Transactions 01/2010; 93-D:2306-2310. DOI: 10.1587/transinf.E93.D.2306
Source: DBLP

ABSTRACT 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

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    ABSTRACT: Wireless sensor networks composed of battery-powered sensor nodes are invaluable instruments for remote environment sensing. For sensor network applications, sensed readings are often collected in the form of aggregated data from a portion of a sensor network as requested by spatial aggregation queries. In a large distributed sensor network, queries can be issued from various locations at any time. Existing in-network query execution techniques execute queries independently that considerably overconsumes the precious energy of sensor nodes. As a result, the lifespan of a sensor network is inevitably shortened. In this paper, we propose a Materialized In-Network View (MINV) framework that precalculates aggregated data from clusters of sensor nodes as intermediate query results preserved in the network and made ready for queries. The executions of queries are performed as simple collections of these aggregated data. Thus, the quantities and sizes of messages transmitted among sensor nodes can be greatly reduced, thus prolonging the lifetime of a sensor network. Through extensive simulations, the effectiveness of our proposed framework is validated.
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