TY - GEN
T1 - Optimal node scheduling for the lifetime maximization of two-tier wireless sensor networks
AU - Lin, Ying
AU - Hu, Xiao Min
AU - Zhang, Jun
AU - Liu, Ou
AU - Liu, Hai Lin
PY - 2010
Y1 - 2010
N2 - Research into maximizing the network lifetime is one of the most significant and challenging areas in wireless sensor networks (WSNs). By arranging sensors and sinks to realize target coverage and network connectivity respectively, an efficient schedule of sensors and sinks can prolong the network lifetime. However, the arrangements of sensors and sinks correlate with each other because each sensor needs to send its data to a sink, making the problem of finding the optimal schedule difficult. Instead of using a single process to optimize the entire schedule of sensors and sinks, this paper proposes a scheduling method which uses two separate processes to schedule operations of sensors and sinks respectively. The first process organizes sensors in the network into disjoint sets, with each set being able to fully cover the targets. Based on the arrangement of sensors, a novel genetic algorithm (GA) is adopted in the second process to allocate sinks to each set of sensors. When the number of full cover sets that ensure both connectivity of sensors to sinks and connectivity of the network composed of sinks is maximized, a schedule that maximizes the network lifetime can be obtained. The proposed method has been applied to a number of WSN cases. Results demonstrate that the method is effective and efficient in prolonging the lifetime of WSNs.
AB - Research into maximizing the network lifetime is one of the most significant and challenging areas in wireless sensor networks (WSNs). By arranging sensors and sinks to realize target coverage and network connectivity respectively, an efficient schedule of sensors and sinks can prolong the network lifetime. However, the arrangements of sensors and sinks correlate with each other because each sensor needs to send its data to a sink, making the problem of finding the optimal schedule difficult. Instead of using a single process to optimize the entire schedule of sensors and sinks, this paper proposes a scheduling method which uses two separate processes to schedule operations of sensors and sinks respectively. The first process organizes sensors in the network into disjoint sets, with each set being able to fully cover the targets. Based on the arrangement of sensors, a novel genetic algorithm (GA) is adopted in the second process to allocate sinks to each set of sensors. When the number of full cover sets that ensure both connectivity of sensors to sinks and connectivity of the network composed of sinks is maximized, a schedule that maximizes the network lifetime can be obtained. The proposed method has been applied to a number of WSN cases. Results demonstrate that the method is effective and efficient in prolonging the lifetime of WSNs.
UR - http://www.scopus.com/inward/record.url?scp=79959415655&partnerID=8YFLogxK
U2 - 10.1109/CEC.2010.5586264
DO - 10.1109/CEC.2010.5586264
M3 - Conference Proceeding
AN - SCOPUS:79959415655
SN - 9781424469109
T3 - 2010 IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 IEEE Congress on Evolutionary Computation, CEC 2010
BT - 2010 IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 IEEE Congress on Evolutionary Computation, CEC 2010
T2 - 2010 6th IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 IEEE Congress on Evolutionary Computation, CEC 2010
Y2 - 18 July 2010 through 23 July 2010
ER -