TY - GEN
T1 - Delay-efficient data aggregation scheduling in duty-cycled wireless sensor networks
AU - Ha, Nguyen Phan Khanh
AU - Zalyubovskiy, Vyacheslav
AU - Choo, Hyunseung
PY - 2012
Y1 - 2012
N2 - Data aggregation is an essential operation in wireless sensor networks (WSNs) in which sensed data are aggregated and transmitted to the sink. In many applications, reducing the latency of data aggregation is an important target. In addition, one of the primary challenges in WSNs is energy scarcity and reducing energy consumption is a problem. Recently, duty cycling, i.e., periodically switching on and off communication and sensing capabilities, has been considered to significantly reduce the sensor's energy consumption and extend a network lifetime. In this paper, we consider the minimum-latency aggregation scheduling problem in dutycycled WSNs. We propose a Delay-Efficient Data Aggregation Scheduling (DEDAS) scheme to generate a collisionfree schedule and minimize the delay for data aggregation in duty-cycled WSNs. Our analysis and comprehensive simulation results indicate that our solution performs better than existing schemes.
AB - Data aggregation is an essential operation in wireless sensor networks (WSNs) in which sensed data are aggregated and transmitted to the sink. In many applications, reducing the latency of data aggregation is an important target. In addition, one of the primary challenges in WSNs is energy scarcity and reducing energy consumption is a problem. Recently, duty cycling, i.e., periodically switching on and off communication and sensing capabilities, has been considered to significantly reduce the sensor's energy consumption and extend a network lifetime. In this paper, we consider the minimum-latency aggregation scheduling problem in dutycycled WSNs. We propose a Delay-Efficient Data Aggregation Scheduling (DEDAS) scheme to generate a collisionfree schedule and minimize the delay for data aggregation in duty-cycled WSNs. Our analysis and comprehensive simulation results indicate that our solution performs better than existing schemes.
KW - Data aggregation scheduling
KW - Duty cycle
KW - Minimum-latency
KW - Wireless sensor networks
UR - https://www.scopus.com/pages/publications/84871637438
U2 - 10.1145/2401603.2401649
DO - 10.1145/2401603.2401649
M3 - Conference contribution
AN - SCOPUS:84871637438
SN - 9781450314923
T3 - Proceeding of the 2012 ACM Research in Applied Computation Symposium, RACS 2012
SP - 203
EP - 208
BT - Proceeding of the 2012 ACM Research in Applied Computation Symposium, RACS 2012
T2 - 2012 ACM Research in Applied Computation Symposium, RACS 2012
Y2 - 23 October 2012 through 26 October 2012
ER -