Optimization problems with low SWaP tactical Computing
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.
Artificial Intelligence, Computational Complexity, Computation and Language, Networking and Internet Architecture
Im et al., “Optimization Problems with Low SWaP Tactical Computing.” 2019.