Energy-Aware Stochastic UAV-Assisted Surveillance

With the ease of deployment, capabilities evading jammers and obscuring their existence, unmanned aerial vehicles (UAVs) are one most suitable candidates to perform surveillance. There exists a body literature in which inspectors follow deterministic trajectory conduct surveillance, results predictable environment for malicious entities. Thus, introducing randomness surveillance is particular interest. In this work, we propose novel framework stochastic UAV-assisted that i) inherently considers battery constraints UAVs, ii) proposes random moving patterns modeled via walks, iii) adds another degree system considering probabilistic inspections. We formulate problem interest, i.e., obtaining energy-efficient walk inspection policies UAVs subject on criteria sites consumption turns out be signomial programming highly non-convex. To solve it, centralized distributed algorithm along with performance guarantee. This work contributes both classic by designing walks weighted graphs energy limited walkers.