Maximizing rewards for real-time applications with energy constraints

  • Authors:
  • Cosmin Rusu;Rami Melhem;Daniel Mossé

  • Affiliations:
  • University of Pittsburgh, Pittsburgh, PA;University of Pittsburgh, Pittsburgh, PA;University of Pittsburgh, Pittsburgh, PA

  • Venue:
  • ACM Transactions on Embedded Computing Systems (TECS)
  • Year:
  • 2003

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Abstract

New technologies have brought about a proliferation of embedded systems, which vary from control systems to sensor networks to personal digital assistants. Many of the portable embedded devices run several applications, which typically have three constraints that need to be addressed: energy, deadline, and reward. However, many of these portable devices do not have powerful enough CPUs and batteries to run all applications within their deadlines. An optimal scheme would allow the device to run the most applications, each using the most amount of CPU cycles possible, without depleting the energy source while still meeting all deadlines. In this paper we propose a solution to this problem; to our knowledge, this is the first solution that combines the three constraints mentioned above. We devise two algorithms, an optimal algorithm for homogeneous applications (with respect to power consumption) and a heuristic iterative algorithm that can also accommodate heterogeneous applications (i.e., those with different power consumption functions). We show by simulation that our iterative algorithm is fast and within 1% of the optimal.