On Collaboration in Distributed Parameter Estimation with Resource Constraints

We study sensor/agent data collection and collaboration policies for parameter estimation, accounting for resource constraints and correlation between observations collected by distinct sensors/agents. Specifically, we consider a group of sensors/agents each samples from different variables of a multivariate Gaussian distribution and has different estimation objectives, and we formulate a sensor/agent's data collection and collaboration policy design problem as a Fisher information maximization (or Cramer-Rao bound minimization) problem. When the knowledge of correlation between variables is available, we analytically identify two particular scenarios: (1) where the knowledge of the correlation between samples cannot be leveraged for collaborative estimation purposes and (2) where the optimal data collection policy involves investing scarce resources to collaboratively sample and transfer information that is not of immediate interest and whose statistics are already known, with the sole goal of increasing the confidence on the estimate of the parameter of interest. When the knowledge of certain correlation is unavailable but collaboration may still be worthwhile, we propose novel ways to apply multi-armed bandit algorithms to learn the optimal data collection and collaboration policy in our distributed parameter estimation problem and demonstrate that the proposed algorithms, DOUBLE-F, DOUBLE-Z, UCB-F, UCB-Z, are effective through simulations

Rejuvenation and the Age of Information

International audienc

Aging and Rejuvenation Models of Load Changing Attacks in Micro-Grids

Recent cyber-attacks in critical infrastructures have highlighted the importance of investigating how to improve Smart-Grids (SG) resiliency. In the future, it is envisioned that grid connected micro-grids would have the ability of operating in 'islanded mode’ in the event of a grid-level failure. In this work, we propose a method for unfolding aging and rejuvenation models into their sequential counterparts to enable the computation of transient state probabilities in the proposed models. We have applied our methodology to one specific security attack scenario and four large campus micro-grids case studies. We have shown how to convert the software aging and rejuvenation, with cycles, to its unfolded counterpart. We then used the unfolded counterpart to support the survivability computation. We were able to analytically evaluate the transient failure probability and the associated Instantaneous Expected Energy Not Supplied metric, for each of the four case studies, from one specific attack. We envision several practical applications of the proposed methodology. First, because the micro-grid model is solved analytically, the approach can be used to support micro-grid engineering optimizations accounting for security intrusions. Second, micro-grid engineers could use the approach to detect security attacks by monitoring for unexpected deviations of the Energy Not Supplied metric