Amortized efficiency of list update and paging rules
Communications of the ACM
Approximation results in parallel machines stochastic scheduling
Annals of Operations Research
Turnpike optimality of Smith's Rule in parallel machines stochastic scheduling
Mathematics of Operations Research
Resource scheduling for parallel database and scientific applications
Proceedings of the eighth annual ACM symposium on Parallel algorithms and architectures
Profile-driven instruction level parallel scheduling with application to super blocks
Proceedings of the 29th annual ACM/IEEE international symposium on Microarchitecture
Online computation and competitive analysis
Online computation and competitive analysis
Sequencing Tasks with Exponential Service Times to Minimize the Expected Flow Time or Makespan
Journal of the ACM (JACM)
Approximation in stochastic scheduling: the power of LP-based priority policies
Journal of the ACM (JACM)
A PTAS for Minimizing the Total Weighted Completion Time on Identical Parallel Machines
Mathematics of Operations Research
A new average case analysis for completion time scheduling
STOC '02 Proceedings of the thiry-fourth annual ACM symposium on Theory of computing
SIAM Journal on Computing
Scheduling Unrelated Machines by Randomized Rounding
SIAM Journal on Discrete Mathematics
Optimal On-Line Algorithms for Single-Machine Scheduling
Proceedings of the 5th International IPCO Conference on Integer Programming and Combinatorial Optimization
Approximation Schemes for Minimizing Average Weighted Completion Time with Release Dates
FOCS '99 Proceedings of the 40th Annual Symposium on Foundations of Computer Science
Handbook of Scheduling: Algorithms, Models, and Performance Analysis
Handbook of Scheduling: Algorithms, Models, and Performance Analysis
Online Scheduling of a Single Machine to Minimize Total Weighted Completion Time
Mathematics of Operations Research
Stochastic Machine Scheduling with Precedence Constraints
SIAM Journal on Computing
LP-based online scheduling: from single to parallel machines
IPCO'05 Proceedings of the 11th international conference on Integer Programming and Combinatorial Optimization
Stochastic online scheduling on parallel machines
WAOA'04 Proceedings of the Second international conference on Approximation and Online Algorithms
On-line scheduling to minimize average completion time revisited
Operations Research Letters
Approximation in preemptive stochastic online scheduling
ESA'06 Proceedings of the 14th conference on Annual European Symposium - Volume 14
Stochastic Online Scheduling Revisited
COCOA 2008 Proceedings of the 2nd international conference on Combinatorial Optimization and Applications
Scheduling shared scans of large data files
Proceedings of the VLDB Endowment
Preemptive stochastic online scheduling on two uniform machines
Information Processing Letters
Computers and Operations Research
Mechanism Design for Decentralized Online Machine Scheduling
Operations Research
Average-case competitive analyses for one-way trading
Journal of Combinatorial Optimization
On robust online scheduling algorithms
Journal of Scheduling
A stochastic scheduling algorithm for precedence constrained tasks on Grid
Future Generation Computer Systems
Decentralization and mechanism design for online machine scheduling
SWAT'06 Proceedings of the 10th Scandinavian conference on Algorithm Theory
Analysis of computer job control under uncertainty
Journal of Computer and Systems Sciences International
Learning in stochastic machine scheduling
WAOA'11 Proceedings of the 9th international conference on Approximation and Online Algorithms
A Lagrangian approach to dynamic resource allocation
Proceedings of the Winter Simulation Conference
Scheduling with compressible and stochastic release dates
Computers and Operations Research
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We consider a model for scheduling under uncertainty. In this model, we combine the main characteristics of online and stochastic scheduling in a simple and natural way. Job processing times are assumed to be stochastic, but in contrast to traditional stochastic scheduling models, we assume that jobs arrive online, and there is no knowledge about the jobs that will arrive in the future. The model incorporates both stochastic scheduling and online scheduling as a special case. The particular setting we consider is nonpreemptive parallel machine scheduling, with the objective to minimize the total weighted completion times of jobs. We analyze simple, combinatorial online scheduling policies for that model, and derive performance guarantees that match performance guarantees previously known for stochastic and online parallel machine scheduling, respectively. For processing times that follow new better than used in expectation (NBUE) distributions, we improve upon previously best-known performance bounds from stochastic scheduling, even though we consider a more general setting.