Optimal Energy Allocation Policies for a High Altitude Flying Wireless Access Point

TL;DR

This paper develops and compares online energy allocation policies for a high altitude flying wireless access point powered by renewable energy, addressing a complex dynamic knapsack problem with both deterministic and stochastic models.

Contribution

It introduces novel online approximation policies based on adaptive thresholds for energy allocation in high altitude wireless access points, extending the dynamic knapsack problem.

Findings

Proposed threshold-based policies perform close to optimal in simulations.

Adaptive policies effectively handle short-term dynamics and stochastic variations.

The stochastic model's threshold policy is proven optimal via dynamic programming.

Abstract

Inspired by recent industrial efforts toward high altitude flying wireless access points powered by renewable energy, an online resource allocation problem for a mobile access point (AP) travelling at high altitude is formulated. The AP allocates its resources (available energy) to maximize 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, the solution of which is quite open in the literature. We address the problem through deterministic and stochastic formulations. For the deterministic problem, several online approximations 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 (DP) formulation, an approximate threshold based policy is obtained. The performances of proposed policies are compared with that of the optimal solution obtained through DP.