Dover: An Optimal On-Line Scheduling Algorithm for Overloaded Uniprocessor Real-Time Systems
SIAM Journal on Computing
The complexity of mean payoff games on graphs
Theoretical Computer Science
Scheduling for Overload in Real-Time Systems
IEEE Transactions on Computers
Online computation and competitive analysis
Online computation and competitive analysis
Competitive On-Line Scheduling of Imprecise Computations
IEEE Transactions on Computers
Scheduler Modeling Based on the Controller Synthesis Paradigm
Real-Time Systems
A resource allocation model for QoS management
RTSS '97 Proceedings of the 18th IEEE Real-Time Systems Symposium
Power-Aware Scheduling for Periodic Real-Time Tasks
IEEE Transactions on Computers
Competitive Algorithms for Fine-Grain Real-Time Scheduling
RTSS '04 Proceedings of the 25th IEEE International Real-Time Systems Symposium
Algorithmic Game Theory
Faster algorithms for mean-payoff games
Formal Methods in System Design
SAGT'11 Proceedings of the 4th international conference on Algorithmic game theory
Half-Positional determinacy of infinite games
ICALP'06 Proceedings of the 33rd international conference on Automata, Languages and Programming - Volume Part II
The complexity of mean-payoff automaton expression
ICALP'12 Proceedings of the 39th international colloquium conference on Automata, Languages, and Programming - Volume Part II
A note on the approximation of mean-payoff games
Information Processing Letters
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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 partial-observation 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.