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Optimal and efficient adaptation in distributed real-time systems with discrete rates

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Abstract

Many distributed real-time systems face the challenge of dynamically maximizing system utility and meeting stringent resource constraints in response to fluctuations in system workload. Thus, online adaptation must be adopted in face of workload changes in such systems. We present the MultiParametric Rate Adaptation (MPRA) algorithm for discrete rate adaptation in distributed real-time systems with end-to-end tasks. The key novelty and advantage of MPRA is that it can efficiently produce optimal solutions in response to workload variations caused by dynamic task arrivals and departures. Through offline preprocessing MPRA transforms an NP-hard utility optimization problem to the evaluation of a piecewise linear function of the CPU utilization. At run time MPRA produces optimal solutions by evaluating the function based on the CPU utilization. Analysis and simulation results show that MPRA maximizes system utility in the presence of varying workloads, while reducing the online computation complexity to polynomial time. The advantages of MPRA have been validated through the implementation in a real-time middleware system and experiments on a physical testbed.

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Notes

  1. A non-greedy synchronization protocol (Sun and Liu 1996) can be used to remove release jitter of subtasks.

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Authors and Affiliations

  1. Department of Computer Science and Engineering, Washington University in St. Louis, One Brookings Drive, St. Louis, MO, 63130, USA

    Yingming Chen & Chenyang Lu

  2. Department of EECS, Vanderbilt University, Box 1679, Station B, Nashville, TN, 37235, USA

    Xenofon D. Koutsoukos

Authors
  1. Yingming Chen
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  2. Chenyang Lu
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  3. Xenofon D. Koutsoukos
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Correspondence to Chenyang Lu.

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Chen, Y., Lu, C. & Koutsoukos, X.D. Optimal and efficient adaptation in distributed real-time systems with discrete rates. Real-Time Syst 49, 339–366 (2013). https://doi.org/10.1007/s11241-012-9168-7

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