G. Hartl and B. Li, “Loss Inference in Wireless Sensor Networks Based on Data Aggregation,” Proceedings of International Symposium on Information Processing in Sensor Networks (IPSN), Berkeley, 2004, pp. 396-404.

has been cited by the following article:

• TITLE: Passive Loss Inference in Wireless Sensor Networks Using EM Algorithm

  AUTHORS: Yu Yang, Zhulin An, Yongjun Xu, Xiaowei Li, Canfeng Che

  KEYWORDS: Wireless Sensor Networks, Passive Measurement, Network Tomography, Data Aggregation, EM Algorithm

  JOURNAL NAME: Wireless Sensor Network, Vol.2 No.7, July 9, 2010

  ABSTRACT: Wireless Sensor Networks (WSNs) are mainly deployed for data acquisition, thus, the network performance can be passively measured by exploiting whether application data from various sensor nodes reach the sink. In this paper, therefore, we take into account the unique data aggregation communication paradigm of WSNs and model the problem of link loss rates inference as a Maximum-Likelihood Estimation problem. And we propose an inference algorithm based on the standard Expectation-Maximization (EM) techniques. Our algorithm is applicable not only to periodic data collection scenarios but to event detection scenarios. Finally, we validate the algorithm through simulations and it exhibits good performance and scalability.