Session

Poster Session II

Event Website

https://www.smallsat.org/index

Abstract

We derive an autonomous scheduling system for low earth orbiting store-and-forward communications nanosatellites (nanosats). Nanosats receive messages of different sizes and priorities, and the nanosat scheduling system determines when to deliver complete or partial messages to associated destinations. The optimal schedule considers nanosat limitations in terms of size, power, onboard data storage, energy capacity and contact time windows. In this paper, we first formulate a binary linear program to optimize a single-satellite resource-constrained message delivery schedule. Since a large-scale binary integer program is computationally intensive, we develop an approximation algorithm based on a time-indexed formulation and mean busy time objective function for finding quality solutions efficiently. The performance of the approximation algorithm is compared with greedy strategies based on priorities and priority to message size ratios. The results of numerical experiments are shown, and the effectiveness of the approximation algorithm is examined.

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Aug 9th, 4:00 PM Aug 9th, 4:45 PM

Energy-Cognizant Scheduling of Store-and-Forward Communications with Multiple Priority Levels in Nanosatellite Systems

We derive an autonomous scheduling system for low earth orbiting store-and-forward communications nanosatellites (nanosats). Nanosats receive messages of different sizes and priorities, and the nanosat scheduling system determines when to deliver complete or partial messages to associated destinations. The optimal schedule considers nanosat limitations in terms of size, power, onboard data storage, energy capacity and contact time windows. In this paper, we first formulate a binary linear program to optimize a single-satellite resource-constrained message delivery schedule. Since a large-scale binary integer program is computationally intensive, we develop an approximation algorithm based on a time-indexed formulation and mean busy time objective function for finding quality solutions efficiently. The performance of the approximation algorithm is compared with greedy strategies based on priorities and priority to message size ratios. The results of numerical experiments are shown, and the effectiveness of the approximation algorithm is examined.

https://digitalcommons.usu.edu/smallsat/2016/Poster2/13