8 research outputs found
Games and Mechanism Design in Machine Scheduling – An Introduction
In this paper, we survey different models, techniques, and some recent results to tackle machine scheduling problems within a distributed setting. In traditional optimization, a central authority is asked to solve a (computationally hard) optimization problem. In contrast, in distributed settings there are several agents, possibly equipped with private information that is not publicly known, and these agents need to interact in order to derive a solution to the problem. Usually the agents have their individual preferences, which induces them to behave strategically in order to manipulate the resulting solution. Nevertheless, one is often interested in the global performance of such systems. The analysis of such distributed settings requires techniques from classical Optimization, Game Theory, and Economic Theory. The paper therefore briefly introduces the most important of the underlying concepts, and gives a selection of typical research questions and recent results, focussing on applications to machine scheduling problems. This includes the study of the so-called price of anarchy for settings where the agents do not possess private information, as well as the design and analysis of (truthful) mechanisms in settings where the agents do possess private information.computer science applications;
Competitive Kill-and-Restart and Preemptive Strategies for Non-Clairvoyant Scheduling
We study kill-and-restart and preemptive strategies for the fundamental
scheduling problem of minimizing the sum of weighted completion times on a
single machine in the non-clairvoyant setting. First, we show a lower bound
of~ for any deterministic non-clairvoyant kill-and-restart strategy. Then,
we give for any a tight analysis for the natural -scaling
kill-and-restart strategy as well as for a randomized variant of it. In
particular, we show a competitive ratio of for the
deterministic and of for the randomized strategy, by making use
of the largest eigenvalue of a Toeplitz matrix. In addition, we show that the
preemptive Weighted Shortest Elapsed Time First (WSETF) rule is -competitive
when jobs are released online, matching the lower bound for the unit weight
case with trivial release dates for any non-clairvoyant algorithm. Using this
result as well as the competitiveness of round-robin for multiple machines, we
prove performance guarantees smaller than for adaptions of the -scaling
strategy to online release dates and unweighted jobs on identical parallel
machines.Comment: An extended abstract occurred in the Proceedings of the 24th
International Conference on Integer Programming and Combinatorial
Optimizatio