Optimal energy allocation policies for a high altitude flying wireless access point

Inspired by recent industrial efforts towards high altitude flying wireless access points powered by renewable energy, an online resource allocation problem for a mobile access point travelling at high altitude is formulated. The access point allocates its resources (available energy) to maximise the total utility (reward) provided to a sequentially observed set of users demanding service. The problem is formulated as a 0/1 dynamic knapsack problem with incremental capacity over a finite time horizon, and the solution of which is quite open in the literature. We address the problem through deterministic and stochastic formulations followed by a model where the statistics of the underlying processes are not known and learned through rule‐based and neural network approaches. For the deterministic problem, several online approximations including optimisation via genetic algorithm and rule‐based approach are proposed based on an instantaneous threshold that can adapt to short‐time‐scale dynamics. For the stochastic model, after showing the optimality of a threshold‐based solution on a dynamic programming formulation, an approximate threshold‐based policy is obtained. The performances of proposed policies are compared with that of the optimal solution obtained through dynamic programming. Copyright © 2016 John Wiley & Sons, Ltd. The paper demonstrates mainly a different formulation for the online user admission problem apart from other studies concerned with resource allocation at a mobile access point empowered by (solar) energy harvesting. After mapping the resource allocation problem to a multi constraint knapsack problem, existence of a threshold based optimal policy is exhibited and computationally cost effective heuristics are proposed.