Efficient Data Collection Trees in Sensor Networks with Redundancy Removal

Zou, Shoudong; Nikolaidis, Ioanis; Harms, Janelle

doi:10.1007/978-3-540-28634-9_20

Cited by 6 publications

(1 citation statement)

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“…The route(s) for a sensor node to reply with data can be selected based on various criteria, for example, using a small hopcount in [ 21 – 23 ], minimum energy cost of data delivery in [ 17 ], adopting reliable routes from multiple candidates to avoid route failure in [ 3 ], or using an alternative path obtained from neighbouring nodes to improve security [ 24 ]. The reverse-tree-based data collection is simple to construct and imposes little additional overhead, as it is built on the basis of query dissemination.…”

Section: Related Workmentioning

confidence: 99%

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

Teng

Zhang²

2010

Sensors

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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.

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