Wireless sensor networks for habitat monitoring
WSNA '02 Proceedings of the 1st ACM international workshop on Wireless sensor networks and applications
Poster abstract: cooperative tracking with binary-detection sensor networks
Proceedings of the 1st international conference on Embedded networked sensor systems
Reliable bursty convergecast in wireless sensor networks
Proceedings of the 6th ACM international symposium on Mobile ad hoc networking and computing
Wireless Remote Healthcare Monitoring with Motes
ICMB '05 Proceedings of the International Conference on Mobile Business
Reliability-Latency tradeoffs for data gathering in random-access wireless sensor networks
GCC'05 Proceedings of the 4th international conference on Grid and Cooperative Computing
Distributed rate adaptive packet access (DRAPA) for multicell wireless networks
IEEE Transactions on Wireless Communications
Energy efficient data gathering in multi-hop hierarchical wireless ad hoc networks
FOMC '11 Proceedings of the 7th ACM ACM SIGACT/SIGMOBILE International Workshop on Foundations of Mobile Computing
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Data gathering is a critical operation in wireless sensor networks for extracting useful information from the operating environment. In this paper, we study the problem of data gathering in multi-hop linear sensor networks. We employ a simple model based on random channel access scheme to tackle the high degree of channel contention and high probability of packet collision induced by bursty traffic. In our model, each node optimally attempts a transmission, and our goal is to tune the attempt probability for each sensor node with the objective to minimize the data gathering duration on condition that each link can provide guaranteed per-hop packet delivery reliability. We formulate this problem as an optimization problem and propose a distributed solution which relies on only two hop neighbors information. Based on this model, a simple and scalable protocol RADG (Random Access Data Gathering) is designed. Simulation results show that our algorithm has fast convergence speed. Moreover, RADG is robust to link error in essence and particularly suitable to monitor environments with high degree of interference.