Show simple item record

dc.contributor.authorHua, Guogang
dc.contributor.authorChen, Chang Wen
dc.date.accessioned2017-06-06T15:55:38Z
dc.date.available2017-06-06T15:55:38Z
dc.date.issued2006-05-10
dc.identifier.citationHua, G., & Chen, C. W. (2006). An adaptive distributed data aggregation based on RCPC for wireless sensor networks 62010D-1. Paper presented at the Proceedings of SPIE - the International Society for Optical Engineering, 6201 doi:10.1117/12.666548en_US
dc.identifier.urihttp://hdl.handle.net/11141/1468
dc.description.abstractOne of the most important design issues in wireless sensor networks is energy efficiency. Data aggregation has significant impact on the energy efficiency of the wireless sensor networks. With massive deployment of sensor nodes and limited energy supply, data aggregation has been considered as an essential paradigm for data collection in sensor networks. Recently, distributed source coding has been demonstrated to possess several advantages in data aggregation for wireless sensor networks. Distributed source coding is able to encode sensor data with lower bit rate without direct communication among sensor nodes. To ensure reliable and high throughput transmission with the aggregated data, we proposed in this research a progressive transmission and decoding of Rate-Compatible Punctured Convolutional (RCPC) coded data aggregation with distributed source coding. Our proposed 1/2 RSC codes with Viterbi algorithm for distributed source coding are able to guarantee that, even without any correlation between the data, the decoder can always decode the data correctly without wasting energy. The proposed approach achieves two aspects in adaptive data aggregation for wireless sensor networks. First, the RCPC coding facilitates adaptive compression corresponding to the correlation of the sensor data. When the data correlation is high, higher compression ration can be achieved. Otherwise, lower compression ratio will be achieved. Second, the data aggregation is adaptively accumulated. There is no waste of energy in the transmission; even there is no correlation among the data, the energy consumed is at the same level as raw data collection. Experimental results have shown that the proposed distributed data aggregation based on RCPC is able to achieve high throughput and low energy consumption data collection for wireless sensor networks.en_US
dc.language.isoen_USen_US
dc.rightsThis published article is made available in accordance with publishers policy. It may be subject to U.S. copyright law.en_US
dc.rights.urihttp://spie.org/publications/journals/guidelines-for-authors#Terms_of_Useen_US
dc.titleAn Adaptive Distributed Data Aggregation based on RCPC for Wireless Sensor Networksen_US
dc.typeConference Proceedingen_US
dc.identifier.doi10.1117/12.666548


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record