Distributed Resilient Estimation over Directed Graphs.
Shamik Bhattacharyya, Kiran Rokade, Rachel Kalpana Kalaimani · arXiv (Cornell University) · 2021
This paper addresses the problem of estimating an unknown static parameter by a network of sensor nodes in a distributed manner over a directed communication network in the presence of adversaries. We introduce an algorithm, Resilient Estimation through Weight Balancing (REWB), which ensures that all the nodes, both normal and malicious, asymptotically converge to the value to be estimated provided less than half of them are affected by adversaries. We discuss how our REWB algorithm is developed using the concepts of weight balancing of directed graphs, and the consensus+innovations approach for linear estimation. Numerical simulations are presented to show the performance of our algorithm over directed graphs and its resilience to sensor attacks.