Results 1 
5 of
5
A Pragmatic Analysis of Scheduling Environments on New Computing Platforms
 International Journal of High Performance Computing and Applications
, 2006
"... computing platforms ..."
(Show Context)
Online Scheduling to Minimize Max Flow Time: An Optimal Preemptive Algorithm
, 2004
"... We investigate the problem of online scheduling jobs on m identical parallel machines where preemption is allowed. The goal is to minimize the maximum flow time among all jobs, where the flow time of a job is its completion time minus its release time. We derive an online algorithm with competiti ..."
Abstract

Cited by 2 (0 self)
 Add to MetaCart
(Show Context)
We investigate the problem of online scheduling jobs on m identical parallel machines where preemption is allowed. The goal is to minimize the maximum flow time among all jobs, where the flow time of a job is its completion time minus its release time. We derive an online algorithm with competitive ratio 2 1/m. Moreover, when the algorithm must schedule jobs one by one in the order they are released, we prove that there is no randomized online algorithm with a better competitive ratio. Finally, we investigate the nonpreemptive case and show that the First In First Out heuristic achieves the best possible competitive ratio when m = 2.
Scheduling parallel machines with inclusive processing set restrictions and job release times
 European Journal of Operational Research
, 2010
"... This is the PrePublished Version. We consider the problem of scheduling a set of jobs with different release times on parallel machines so as to minimize the makespan of the schedule. The machines have the same processing speed, but each job is compatible with only a subset of those machines. The m ..."
Abstract

Cited by 2 (0 self)
 Add to MetaCart
(Show Context)
This is the PrePublished Version. We consider the problem of scheduling a set of jobs with different release times on parallel machines so as to minimize the makespan of the schedule. The machines have the same processing speed, but each job is compatible with only a subset of those machines. The machines can be linearly ordered such that a higherindexed machine can process all those jobs that a lowerindexed machine can process. We present an efficient algorithm for this problem with a worstcase performance ratio of 2. We also develop a polynomial time approximation scheme (PTAS) for the problem, as well as a fully polynomial time approximation scheme (FPTAS) for the case in which the number of machines is fixed.
Scheduling search procedures: The wheel of fortune
 J. of Scheduling
"... Suppose that a player can make progress on n jobs, and her goal is to complete a target job among them, as soon as possible. Unfortunately she does not know what the target job is, perhaps not even if the target exists. This is a typical situation in searching and testing. Depending on the player’s ..."
Abstract

Cited by 1 (1 self)
 Add to MetaCart
(Show Context)
Suppose that a player can make progress on n jobs, and her goal is to complete a target job among them, as soon as possible. Unfortunately she does not know what the target job is, perhaps not even if the target exists. This is a typical situation in searching and testing. Depending on the player’s prior knowledge and optimization goals, this gives rise to various optimization problems in the framework of game theory and, sometimes, competitive analysis. Continuing earlier work on this topic we study another two versions. In the first game, the player knows only the job lengths and wants to minimize the completion time. A simple strategy that we call wheeloffortune (WOF) is optimal for this objective. A slight and natural modification however makes this game considerably more difficult: If the player can be sure that the target is present, WOF fails. However we can still construct in polynomial time an optimal strategy based on WOF. We also prove tight absolute bounds on the expected search time. In a final part we study two competitiveratio minimization problems where either the job lengths or the target probabilities are known. We show their equivalence, describe the structure of optimal strategies, and we give a heuristic solution.
507JOB SCHEDULING IN CLUSTERS A PRAGMATIC ANALYSIS OF SCHEDULING ENVIRONMENTS ON NEW COMPUTING PLATFORMS
"... Today, large scale parallel systems are available at relatively low cost. Many powerful such systems have been installed all over the world and the number of users is always increasing. The use of such clusters requires special administration tools, which have been developed recently and most freq ..."
Abstract
 Add to MetaCart
Today, large scale parallel systems are available at relatively low cost. Many powerful such systems have been installed all over the world and the number of users is always increasing. The use of such clusters requires special administration tools, which have been developed recently and most frequently rely on intuitive heuristics to solve the underlying difficult scheduling problems. On the other hand, recent theoretical work has designed a number of models, such as the Parallel Task model, specifically aimed at cluster environments. The objective of this work is to study and analyze the path from theoretical models and algorithms to their implementation on an actual environment on a real platform. We outline in detail the divergences between classical models and a real batch scheduling system, and propose solutions to adapt a theoretically wellfounded algorithm to such a system. Experimental results show that this implementation performs about as well as FCFS with backfilling, and much better in the difficult instances. We hope that further usage of this algorithm in a live system will show that interaction between theory and practice can be fruitful.