TY - GEN
T1 - Distributed scheduling for real-time data collection in wireless sensor networks
AU - Xu, Xiaohua
AU - Li, Xiang Yang
AU - Song, Min
PY - 2013
Y1 - 2013
N2 - We study real time periodic query scheduling for data collection in multihop Wireless Sensor Networks (WSNs). Given a set of heterogenous data collection queries in WSNs, each query requires the data from the source sensor nodes to be collected to the control center within a certain end-to-end delay. We first propose almost-tight necessary conditions for a set of different queries to be schedulable by a WSN. We then develop a family of efficient and effective data collection algorithms that can meet the real-time requirement under resource constraints by addressing three tightly coupled tasks: (1) routing tree construction for data collection, (2) link activity scheduling, and (3) packet-level scheduling. Our theoretical analysis for the schedulability of these algorithms show that they can achieve a constant fraction of the maximum schedulable load. For the case of overloaded networks where not all queries can be possibly satisfied, we propose an efficient approximation algorithm to select queries to maximize the total weight of selected schedulable queries. The simulations corroborate our theoretical analysis.
AB - We study real time periodic query scheduling for data collection in multihop Wireless Sensor Networks (WSNs). Given a set of heterogenous data collection queries in WSNs, each query requires the data from the source sensor nodes to be collected to the control center within a certain end-to-end delay. We first propose almost-tight necessary conditions for a set of different queries to be schedulable by a WSN. We then develop a family of efficient and effective data collection algorithms that can meet the real-time requirement under resource constraints by addressing three tightly coupled tasks: (1) routing tree construction for data collection, (2) link activity scheduling, and (3) packet-level scheduling. Our theoretical analysis for the schedulability of these algorithms show that they can achieve a constant fraction of the maximum schedulable load. For the case of overloaded networks where not all queries can be possibly satisfied, we propose an efficient approximation algorithm to select queries to maximize the total weight of selected schedulable queries. The simulations corroborate our theoretical analysis.
UR - http://www.scopus.com/inward/record.url?scp=84904122602&partnerID=8YFLogxK
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U2 - 10.1109/GLOCOM.2013.6831108
DO - 10.1109/GLOCOM.2013.6831108
M3 - Conference contribution
AN - SCOPUS:84904122602
SN - 9781479913534
SN - 9781479913534
T3 - Proceedings - IEEE Global Communications Conference, GLOBECOM
SP - 426
EP - 431
BT - 2013 IEEE Global Communications Conference, GLOBECOM 2013
T2 - 2013 IEEE Global Communications Conference, GLOBECOM 2013
Y2 - 9 December 2013 through 13 December 2013
ER -