Abstract

Effective runtime power management requires hardware activity to be tracked at a very fine granularity in both space and time in order to meet diverse workload performance requirements within a tight power budget. As the available instantaneous power budget itself represents a shared resource, this practically translates into finding the optimal allocation of the power budget among active tasks of execution. Covert communication over a previously unexplored class of channels thereby becomes possible, which forms the focus of this paper.

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