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Optimization problems with low SWaP tactical Computing
lib:1314a5bf724a8884 (v1.0.0)
Authors: Mee Seong Im,Venkat R. Dasari,Lubjana Beshaj,Dale Shires
ArXiv: 1902.05070
Document: PDF DOI
Abstract URL: http://arxiv.org/abs/1902.05070v1
In a resource-constrained, contested environment, computing resources need to be aware of possible size, weight, and power (SWaP) restrictions. SWaP-aware computational efficiency depends upon optimization of computational resources and intelligent time versus efficiency tradeoffs in decision making. In this paper we address the complexity of various optimization strategies related to low SWaP computing. Due to these restrictions, only a small subset of less complicated and fast computable algorithms can be used for tactical, adaptive computing.
ArXiv: 1902.05070
Document: PDF DOI
Abstract URL: http://arxiv.org/abs/1902.05070v1
In a resource-constrained, contested environment, computing resources need to be aware of possible size, weight, and power (SWaP) restrictions. SWaP-aware computational efficiency depends upon optimization of computational resources and intelligent time versus efficiency tradeoffs in decision making. In this paper we address the complexity of various optimization strategies related to low SWaP computing. Due to these restrictions, only a small subset of less complicated and fast computable algorithms can be used for tactical, adaptive computing.
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