4,065 research outputs found
Profitable Scheduling on Multiple Speed-Scalable Processors
We present a new online algorithm for profit-oriented scheduling on multiple
speed-scalable processors. Moreover, we provide a tight analysis of the
algorithm's competitiveness. Our results generalize and improve upon work by
\textcite{Chan:2010}, which considers a single speed-scalable processor. Using
significantly different techniques, we can not only extend their model to
multiprocessors but also prove an enhanced and tight competitive ratio for our
algorithm.
In our scheduling problem, jobs arrive over time and are preemptable. They
have different workloads, values, and deadlines. The scheduler may decide not
to finish a job but instead to suffer a loss equaling the job's value. However,
to process a job's workload until its deadline the scheduler must invest a
certain amount of energy. The cost of a schedule is the sum of lost values and
invested energy. In order to finish a job the scheduler has to determine which
processors to use and set their speeds accordingly. A processor's energy
consumption is power \Power{s} integrated over time, where
\Power{s}=s^{\alpha} is the power consumption when running at speed .
Since we consider the online variant of the problem, the scheduler has no
knowledge about future jobs. This problem was introduced by
\textcite{Chan:2010} for the case of a single processor. They presented an
online algorithm which is -competitive. We provide an
online algorithm for the case of multiple processors with an improved
competitive ratio of .Comment: Extended abstract submitted to STACS 201
Dagstuhl Reports : Volume 1, Issue 2, February 2011
Online Privacy: Towards Informational Self-Determination on the Internet (Dagstuhl Perspectives Workshop 11061) : Simone Fischer-Hübner, Chris Hoofnagle, Kai Rannenberg, Michael Waidner, Ioannis Krontiris and Michael Marhöfer Self-Repairing Programs (Dagstuhl Seminar 11062) : Mauro Pezzé, Martin C. Rinard, Westley Weimer and Andreas Zeller Theory and Applications of Graph Searching Problems (Dagstuhl Seminar 11071) : Fedor V. Fomin, Pierre Fraigniaud, Stephan Kreutzer and Dimitrios M. Thilikos Combinatorial and Algorithmic Aspects of Sequence Processing (Dagstuhl Seminar 11081) : Maxime Crochemore, Lila Kari, Mehryar Mohri and Dirk Nowotka Packing and Scheduling Algorithms for Information and Communication Services (Dagstuhl Seminar 11091) Klaus Jansen, Claire Mathieu, Hadas Shachnai and Neal E. Youn
Energy-Efficient Multiprocessor Scheduling for Flow Time and Makespan
We consider energy-efficient scheduling on multiprocessors, where the speed
of each processor can be individually scaled, and a processor consumes power
when running at speed , for . A scheduling algorithm
needs to decide at any time both processor allocations and processor speeds for
a set of parallel jobs with time-varying parallelism. The objective is to
minimize the sum of the total energy consumption and certain performance
metric, which in this paper includes total flow time and makespan. For both
objectives, we present instantaneous parallelism clairvoyant (IP-clairvoyant)
algorithms that are aware of the instantaneous parallelism of the jobs at any
time but not their future characteristics, such as remaining parallelism and
work. For total flow time plus energy, we present an -competitive
algorithm, which significantly improves upon the best known non-clairvoyant
algorithm and is the first constant competitive result on multiprocessor speed
scaling for parallel jobs. In the case of makespan plus energy, which is
considered for the first time in the literature, we present an
-competitive algorithm, where is the total number of
processors. We show that this algorithm is asymptotically optimal by providing
a matching lower bound. In addition, we also study non-clairvoyant scheduling
for total flow time plus energy, and present an algorithm that achieves -competitive for jobs with arbitrary release time and
-competitive for jobs with identical release time. Finally,
we prove an lower bound on the competitive ratio of
any non-clairvoyant algorithm, matching the upper bound of our algorithm for
jobs with identical release time
05031 Abstracts Collection -- Algorithms for Optimization with Incomplete Information
From 16.01.05 to 21.01.05, the Dagstuhl Seminar 05031 ``Algorithms for Optimization with Incomplete Information\u27\u27 was held
in the International Conference and Research Center (IBFI),
Schloss Dagstuhl.
During the seminar, several participants presented their current
research, and ongoing work and open problems were discussed. Abstracts of
the presentations given during the seminar as well as abstracts of
seminar results and ideas are put together in this paper. The first section
describes the seminar topics and goals in general.
Links to extended abstracts or full papers are provided, if available
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