Competitive Algorithms for Fine-Grain Real-Time Scheduling

Palis, Michael A.

doi:10.1109/real.2004.14

Cited by 5 publications

(3 citation statements)

References 16 publications

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“…Algorithmic game theory (Nisan et al 2007) has been applied to classic scheduling problems since decades, primarily in economics and operations research, see e.g. (Koutsoupias 2011) for just one example of some more recent work.…”

Section: Related Workmentioning

confidence: 99%

Automated competitive analysis of real-time scheduling with graph games

et al. 2017

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This paper is devoted to automatic competitive analysis of real-time scheduling algorithms for firm-deadline tasksets, where only completed tasks contribute some utility to the system. Given such a taskset T , the competitive ratio of an on-line scheduling algorithm A for T is the worst-case utility ratio of A over the utility achieved by a clairvoyant algorithm. We leverage the theory of quantitative graph games to address the competitive analysis and competitive synthesis problems. For the competitive analysis case, given any taskset T and any finite-memory online scheduling algorithm A, we show that the competitive ratio of A in T can be computed in polynomial time in the size of the state space of A. Our approach is flexible as it also provides ways to model meaningful constraints on the released task sequences that determine the competitive ratio. We provide an experimental study of many well-known on-line scheduling algorithms, which demonstrates the feasibility of our competitive analysis approach that effectively replaces human ingenuity (required Preliminary versions of this paper have appeared in Chatterjee et al. (2013 for finding worst-case scenarios) by computing power. For the competitive synthesis case, we are just given a taskset T , and the goal is to automatically synthesize an optimal on-line scheduling algorithm A, i.e., one that guarantees the largest competitive ratio possible for T . We show how the competitive synthesis problem can be reduced to a two-player graph game with partial information, and establish that the computational complexity of solving this game is Np-complete. The competitive synthesis problem is hence in Np in the size of the state space of the non-deterministic labeled transition system encoding the taskset. Overall, the proposed framework assists in the selection of suitable scheduling algorithms for a given taskset, which is in fact the most common situation in real-time systems design.

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Section: Related Workmentioning

confidence: 99%

Automated competitive analysis of real-time scheduling with graph games

et al. 2017

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“…Regarding firm deadline task scheduling in general, starting out from [3], classic real-time systems research has studied the competitive factor of both simple and extended real-time scheduling algorithms. The competitive analysis of simple algorithms (see Section 8 for the references) has been extended in various ways later on: Energy consumption [10,11] (including dynamic voltage scaling), imprecise computation tasks (having both a mandatory and an optional part and associated utilities) [12], lower bounds on slack time [13], and fairness [14]. Note that dealing with these extensions involved considerable ingenuity and efforts w.r.t.…”

Section: Introductionmentioning

confidence: 99%

A Framework for Automated Competitive Analysis of On-line Scheduling of Firm-Deadline Tasks

Chatterjee

Pavlogiannis

Kößler

et al. 2014

2014 IEEE Real-Time Systems Symposium

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We present a flexible framework for the automated competitive analysis of on-line scheduling algorithms for firm-deadline real-time tasks based on multi-objective graphs: Given a taskset and an on-line scheduling algorithm specified as a labeled transition system, along with some optional safety, liveness, and/or limit-average constraints for the adversary, we automatically compute the competitive ratio of the algorithm w.r.t. a clairvoyant scheduler. We demonstrate the flexibility and power of our approach by comparing the competitive ratio of several on-line algorithms, including D over , that have been proposed in the past, for various tasksets. Our experimental results reveal that none of these algorithms is universally optimal, in the sense that there are tasksets where other schedulers provide better performance. Our framework is hence a very useful design tool for selecting optimal algorithms for a given application.

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“…Among the additional issues taken into consideration are energy consumption [2,9] (including dynamic voltage scaling), imprecise computation tasks (having both a mandatory and an optional part and associated utilities) [5], lower bounds on slack time [4], and fairness [17]. Note that dealing with these extensions involved considerable ingenuity and efforts w.r.t.…”

Section: Introductionmentioning

confidence: 99%

Automated analysis of real-time scheduling using graph games

Chatterjee

Kößler

Schmid

2013

Proceedings of the 16th International Conference on Hybrid Systems: Computation and Control

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In this paper, we introduce the powerful framework of graph games for the analysis of real-time scheduling with firm deadlines. We introduce a novel instance of a partialobservation game that is suitable for this purpose, and prove decidability of all the involved decision problems. We derive a graph game that allows the automated computation of the competitive ratio (along with an optimal witness algorithm for the competitive ratio) and establish an NP-completeness proof for the graph game problem. For a given on-line algorithm, we present polynomial time solution for computing (i) the worst-case utility; (ii) the worst-case utility ratio w.r.t. a clairvoyant off-line algorithm; and (iii) the competitive ratio. A major strength of the proposed approach lies in its flexibility w.r.t. incorporating additional constraints on the adversary and/or the algorithm, including limited maximum or average load, finiteness of periods of overload, etc., which are easily added by means of additional instances of standard objective functions for graph games.

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Competitive Algorithms for Fine-Grain Real-Time Scheduling

Cited by 5 publications

References 16 publications

Automated competitive analysis of real-time scheduling with graph games

Automated competitive analysis of real-time scheduling with graph games

A Framework for Automated Competitive Analysis of On-line Scheduling of Firm-Deadline Tasks

Automated analysis of real-time scheduling using graph games

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