Resilience in distributed sensor networks

Kiril Ratmanski; Sergey Vecherin

doi:10.1117/12.2632868

27 May 2022 Resilience in distributed sensor networks

Kiril Ratmanski, Sergey Vecherin

Proceedings Volume 12106, Infrared Imaging Systems: Design, Analysis, Modeling, and Testing XXXIII; 121060Q (2022) https://doi.org/10.1117/12.2632868
Event: SPIE Defense + Commercial Sensing, 2022, Orlando, Florida, United States

Abstract

With the advent of cheap and available sensors, there is a need for intelligent sensor selection and placement for various purposes. While previous research was focused on the most efficient sensor networks, we present a new mathematical framework for efficient and resilient sensor network installation. Specifically, in this work we formulate and solve a sensor selection and placement problem when network resilience is also a factor in the optimization problem. Our approach is based on the binary linear programming problem. The generic formulation is probabilistic and applicable to any sensor types, line-of-site and non-line-of-site, and any sensor modality. It also incorporates several realistic constraints including finite sensor supply, cost, energy consumption, as well as specified redundancy in coverage areas that require resilience. While the exact solution is computationally prohibitive, we present a fast algorithm that produces a near-optimal solution that can be used in practice. We show how such formulation works on 2D examples, applied to infrared (IR) sensor networks designed to detect and track human presence and movements in a specified coverage area. Analysis of coverage and comparison of sensor placement with and without resilience considerations is also performed.

Conference Presentation

Citation Download Citation

Kiril Ratmanski and Sergey Vecherin "Resilience in distributed sensor networks", Proc. SPIE 12106, Infrared Imaging Systems: Design, Analysis, Modeling, and Testing XXXIII, 121060Q (27 May 2022); https://doi.org/10.1117/12.2632868

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