Proceedings of the 10th annual international conference on Mobile computing and networking
Distributed Cross-Layer Scheduling for In-Network Sensor Query Processing
PERCOM '06 Proceedings of the Fourth Annual IEEE International Conference on Pervasive Computing and Communications
Partially overlapped channels not considered harmful
SIGMETRICS '06/Performance '06 Proceedings of the joint international conference on Measurement and modeling of computer systems
A control theory approach to throughput optimization in multi-channel collection sensor networks
Proceedings of the 6th international conference on Information processing in sensor networks
Exploiting partially overlapping channels in wireless networks: turning a peril into an advantage
IMC '05 Proceedings of the 5th ACM SIGCOMM conference on Internet Measurement
Structure-Free Data Aggregation in Sensor Networks
IEEE Transactions on Mobile Computing
Dynamic Conflict-free Query Scheduling for Wireless Sensor Networks
ICNP '06 Proceedings of the Proceedings of the 2006 IEEE International Conference on Network Protocols
Dynamic Forwarding over Tree-on-DAG for Scalable Data Aggregation in Sensor Networks
IEEE Transactions on Mobile Computing
A hybrid method of CSMA/CA and TDMA for real-time data aggregation in wireless sensor networks
Computer Communications
MC-MLAS: Multi-channel Minimum Latency Aggregation Scheduling in Wireless Sensor Networks
Computer Networks: The International Journal of Computer and Telecommunications Networking
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Existing works on data aggregation in sensor networks usually use a single channel, which results in a long latency due to high interference, especially in high-density networks. In this paper, we present a novel approach to minimize the latency of data aggregation by using partially overlapped channels. We first propose a joint tree construction, channel assignment and scheduling algorithm for this problem. The basic idea is to select a parent and assign a feasible channel to each node such that it can be scheduled in a timeslot that has been used by other nodes, meanwhile leaving unconsidered nodes more chances to avoid conflicts. Next, we give a distributed implementation of this joint scheme. Finally, we compare the performance of our algorithm with two heuristic algorithms that solve this problem in three separate steps, and another multi-channel protocol that only considers orthogonal channels in sensor networks. Simulation results demonstrate that our joint scheme can significantly reduce the data aggregation latency, especially in high-density sensor networks. To our best knowledge, this is the first work in the literature that minimizes the data aggregation latency by using partially overlapped channels.