On the infeasibility of analysing worst-case dynamic energy

Jeremy C M Morse, Steve Kerrison, Kerstin I Eder

Research output: Contribution to journalArticle (Academic Journal)

175 Downloads (Pure)


In this paper we study the sources of dynamic energy during the execution of software on microprocessors suited for the Internet of Things (IoT) domain. Estimating the energy consumed by executing software is typically achieved by determining the most costly path through the program according to some energy model of the processor. Few models, however, adequately tackle the matter of dynamic energy caused by operand data. We find that the contribution of operand data to overall energy can be significant, prove that finding the worst-case input data is NP-hard, and further, that it cannot be estimated to any useful factor. Our work shows that accurate worst-case analysis of data dependent energy is infeasible, and that other techniques for energy estimation should be considered.
Original languageEnglish
Number of pages19
Publication statusSubmitted - 7 Mar 2016


  • cs.CC
  • cs.AR
  • cs.DC


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