DSCA: A data stream caching algorithm
Antonio A. Rocha, Mostafa Dehghan, et al.
CCDWN 2016
In this paper, we investigate how in-network aggregation approach impacts the target tracking quality in multi-hop wireless sensor networks under network delays. Specifically, we use the mean squared error (MSE) of the target location estimate to quantify the target tracking quality, and investigate how in-network aggregation affects the MSE. To obtain insights without being obscured by onerous mathematical details, we assume a Brownian motion mobility model for the target, Gaussian measurement noise for the sensors, and independent per-hop delays. Under the above assumptions, we first propose an aggregation scheme that preserves a sufficient statistic for optimal tracking under data aggregation at the intermediate nodes and arbitrary network delays. We then analytically study the impact of aggregation in three increasingly more complicated scenarios: single task tracking with only transmission delay, single task tracking with both transmission delay and queueing delay at intermediate nodes, and multi-task tracking. Our results demonstrate that in-network aggregation improves tracking quality in all three scenarios. Furthermore, our analysis provides guidelines on how to choose aggregation parameters in practice. © 1983-2012 IEEE.
Antonio A. Rocha, Mostafa Dehghan, et al.
CCDWN 2016
Bo Jiang, Jian Tan, et al.
Journal of Applied Probability
Shiqiang Wang, Tiffany Tuor, et al.
IEEE J-SAC
Ameya Agaskar, Lang Tong, et al.
CISS 2008