  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.
