Planning, Scheduling, and Deploying for Computational Ferrying

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Published Jul 1, 2019
https://doi.org/10.47164/ijngc.v10i2.157
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Volume 10, Issue 2, July 2019

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Sebastian A Zanlongo
Alexander C Wilson
Leonardo Bobadilla
School of Computing and Information Sciences Florida International University
Tamim Sookoor

Abstract

Mobile Cyber-Physical Systems are expected to perform resource-intensive tasks that exceed their hardware (storage and computational power) capabilities. One traditional approach to solve this limitation is through cloudbased solutions. However, this approach may fail in scenarios with limited communication connectivity that can arise due to natural or adversarial conditions. One such situation is tactical battlefield missions where soldiers may require access to significant processing and storage capabilities for a task such as tracking or battlefield awareness without sacrificing their mobility capabilities. In this paper, we extend previous work on computational ferrying, where Mobile High-Performance Computers (MHPCs) can physically move the necessary hardware into the proximity of mobile units. Our extension proposes several improvements over state of the art. First, we present path planning algorithms to find reliable a priori estimation of distances between locations to obtain accurate scheduling. Second, we model MHPCs as autonomous vehicles which leads to more realistic scenarios in environments with obstacles. Third, we explicitly characterize the computational complexity of our proposed work. Finally, we implemented and tested in computer simulation all our algorithms to understand the effect of different obstacles, processors, number of MHPCs in completion time and deadlines met.

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How to Cite
Sebastian A Zanlongo, Alexander C Wilson, Leonardo Bobadilla, & Tamim Sookoor. (2019). Planning, Scheduling, and Deploying for Computational Ferrying. International Journal of Next-Generation Computing, 10(2), 66–80. https://doi.org/10.47164/ijngc.v10i2.157
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