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Sensors 2011, 11(1), 341-361; doi:10.3390/s110100341
Article

On-Demand Information Retrieval in Sensor Networks with Localised Query and Energy-Balanced Data Collection

*  and
Received: 29 October 2010; in revised form: 8 December 2010 / Accepted: 27 December 2010 / Published: 30 December 2010
(This article belongs to the Section Physical Sensors)
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Abstract: On-demand information retrieval enables users to query and collect up-to-date sensing information from sensor nodes. Since high energy efficiency is required in a sensor network, it is desirable to disseminate query messages with small traffic overhead and to collect sensing data with low energy consumption. However, on-demand query messages are generally forwarded to sensor nodes in network-wide broadcasts, which create large traffic overhead. In addition, since on-demand information retrieval may introduce intermittent and spatial data collections, the construction and maintenance of conventional aggregation structures such as clusters and chains will be at high cost. In this paper, we propose an on-demand information retrieval approach that exploits the name resolution of data queries according to the attribute and location of each sensor node. The proposed approach localises each query dissemination and enable localised data collection with maximised aggregation. To illustrate the effectiveness of the proposed approach, an analytical model that describes the criteria of sink proxy selection is provided. The evaluation results reveal that the proposed scheme significantly reduces energy consumption and improves the balance of energy consumption among sensor nodes by alleviating heavy traffic near the sink.
Keywords: on-demand information retrievals; localised data query; data collection; attribute-object name; sink proxy; balancing of energy consumption on-demand information retrievals; localised data query; data collection; attribute-object name; sink proxy; balancing of energy consumption
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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MDPI and ACS Style

Teng, R.; Zhang, B. On-Demand Information Retrieval in Sensor Networks with Localised Query and Energy-Balanced Data Collection. Sensors 2011, 11, 341-361.

AMA Style

Teng R, Zhang B. On-Demand Information Retrieval in Sensor Networks with Localised Query and Energy-Balanced Data Collection. Sensors. 2011; 11(1):341-361.

Chicago/Turabian Style

Teng, Rui; Zhang, Bing. 2011. "On-Demand Information Retrieval in Sensor Networks with Localised Query and Energy-Balanced Data Collection." Sensors 11, no. 1: 341-361.


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