Scheduling algorithms for multihop radio networks
IEEE/ACM Transactions on Networking (TON)
A wireless sensor network For structural monitoring
SenSys '04 Proceedings of the 2nd international conference on Embedded networked sensor systems
An analysis of a large scale habitat monitoring application
SenSys '04 Proceedings of the 2nd international conference on Embedded networked sensor systems
Minimum-latency aggregation scheduling in multihop wireless networks
Proceedings of the tenth ACM international symposium on Mobile ad hoc networking and computing
A Delay-Efficient Algorithm for Data Aggregation in Multihop Wireless Sensor Networks
IEEE Transactions on Parallel and Distributed Systems
Dynamic Switching-Based Data Forwarding for Low-Duty-Cycle Wireless Sensor Networks
IEEE Transactions on Mobile Computing
Minimum data aggregation time problem in wireless sensor networks
MSN'05 Proceedings of the First international conference on Mobile Ad-hoc and Sensor Networks
IEEE Communications Magazine
Minimum-time aggregation scheduling in duty-cycled wireless sensor networks
Journal of Computer Science and Technology - Special issue on Natural Language Processing
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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 duty-cycled WSNs. We propose a Delay-Efficient Data Aggregation Scheduling (DEDAS) scheme to generate a collision-free 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.