Optimizing System Reward in Battery-Powered Spacecrafts and Rovers / 54-58
Albert M. K. Cheng
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Abstract--Rechargeable batteries are used to operate many spacecrafts and autonomous rovers. Their operational periods are limited, however, by their battery supplies before the next recharge. How to use this battery-supplied energy efficiently is a critical issue. Most existing energy-conserving techniques are based on dynamic voltage scaling (DVS) and consider only timing or energy constraints. In a more realistic scenario, we should simultaneously consider three constraints: time, energy, and reward (quality-of-service). This project investigates two static methods (Greedy and Dynamic Programming) and an on-line method for selecting tasks to optimize system reward while meeting timing constraints and conserving energy. We use simulation experiments to compare the performance of these methods with existing techniques. We study three static methods to select tasks from the task sets: (1) Simplified REW-Pack, (2) Greedy, and (3) REW-Pack. We have compared the reward gained by these three methods. We found that our Greedy method often yields a larger total reward value than the gain with REW-Pack. The Greedy method, we find, is more efficient than REW-Pack.