Multi-sensor activation for temporally correlated event monitoring with renewable energy sources

Future sensor networks would comprise sensing devices with energy-harvesting capabilities from renewable energy sources, such as solar power. This paper focuses on design of efficient algorithms for multi-sensor activation to optimise overall event detection probability in presence of uncertainties in event and recharge processes. We formulate the dynamic multisensor activation question in a stochastic optimisation framework, and show that a time-invariant threshold policy, which maintains an appropriately chosen number of sensors active at all times, is optimal in absence of temporal correlations. Moreover, the same energy-balancing timeinvariant threshold policy approaches optimality in presence of temporal correlations as well, albeit under certain limiting assumptions. We also analyse the class of correlation-dependent threshold policies and derive the range for energy-balancing thresholds. Through simulations, we compare the proposed time-invariant policy with energy-balancing correlation-dependent policies, and observe that although the latter may perform better, the performance difference is rather small in the cases studied.