  This paper examines dynamic energy consumption caused by data during software
execution on deeply embedded microprocessors, which can be significant on some
devices. In worst-case energy consumption analysis, energy models are used to
find the most costly execution path. Taking each instruction's worst case
energy produces a safe but overly pessimistic upper bound. Algorithms for safe
and tight bounds would be desirable. We show that finding exact worst-case
energy is NP-hard, and that tight bounds cannot be approximated with guaranteed
safety. We conclude that any energy model targeting tightness must either
sacrifice safety or accept overapproximation proportional to data-dependent
energy.
