Document Detail

Efficient aggregation of multiple classes of information in wireless sensor networks.
MedLine Citation:
PMID:  22408495     Owner:  NLM     Status:  PubMed-not-MEDLINE    
Congestion in a Wireless Sensor Network (WSN) can lead to buffer overflow, resource waste and delay or loss of critical information from the sensors. In this paper, we propose the Priority-based Coverage-aware Congestion Control (PCC) algorithm which is distributed, priority-distinct, and fair. PCC provides higher priority to packets with event information in which the sink is more interested. PCC employs a queue scheduler that can selectively drop any packet in the queue. PCC gives fair chance to all sensors to send packets to the sink, irrespective of their specific locations, and therefore enhances the coverage fidelity of the WSN. Based on a detailed simulation analysis, we show that PCC can efficiently relieve congestion and significantly improve the system performance based on multiple metrics such as event throughput and coverage fidelity. We generalize PCC to address data collection in a WSN in which the sensor nodes have multiple sensing devices and can generate multiple types of information. We propose a Pricing System that can under congestion effectively collect different types of data generated by the sensor nodes according to values that are placed on different information by the sink. Simulation analysis show that our Pricing System can achieve higher event throughput for packets with higher priority and achieve fairness among different categories. Moreover, given a fixed system capacity, our proposed Pricing System can collect more information of the type valued by the sink.
Xiaoling Qiu; Haiping Liu; Deshi Li; Jennifer Yick; Dipak Ghosal; Biswanath Mukherjee
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Publication Detail:
Type:  Journal Article     Date:  2009-10-14
Journal Detail:
Title:  Sensors (Basel, Switzerland)     Volume:  9     ISSN:  1424-8220     ISO Abbreviation:  Sensors (Basel)     Publication Date:  2009  
Date Detail:
Created Date:  2012-03-12     Completed Date:  2012-09-10     Revised Date:  2013-05-29    
Medline Journal Info:
Nlm Unique ID:  101204366     Medline TA:  Sensors (Basel)     Country:  Switzerland    
Other Details:
Languages:  eng     Pagination:  8083-108     Citation Subset:  -    
Department of Computer Science, University of California, Davis, CA, USA; E-Mails: (H.P.L.); (B.M.).
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