Analysis of computer job control under uncertainty

Authors:
P. E. Golosov;M. V. Kozlov;Yu. E. Malashenko;I. A. Nazarova;A. F. Ronzhin
Affiliations:
Lebedev Institute of Precision Mechanics and Computer Engineering, Russian Academy of Sciences, Moscow, Russia 119991;Dorodnicyn Computing Center, Russian Academy of Sciences, Moscow, Russia 119333;Dorodnicyn Computing Center, Russian Academy of Sciences, Moscow, Russia 119333;Dorodnicyn Computing Center, Russian Academy of Sciences, Moscow, Russia 119333;Dorodnicyn Computing Center, Russian Academy of Sciences, Moscow, Russia 119333
Venue:
Journal of Computer and Systems Sciences International
Year:
2012

Citing 17
Cited 2

Job scheduling to minimize expected weighted flowtime on uniform processors

Systems & Control Letters
Approximation results in parallel machines stochastic scheduling

Annals of Operations Research
Sequencing Tasks with Exponential Service Times to Minimize the Expected Flow Time or Makespan

Journal of the ACM (JACM)
Handbook of Scheduling: Algorithms, Models, and Performance Analysis

Handbook of Scheduling: Algorithms, Models, and Performance Analysis
DIRAC: A Scalable Lightweight Architecture for High Throughput Computing

GRID '04 Proceedings of the 5th IEEE/ACM International Workshop on Grid Computing
A study of meta-scheduling architectures for high throughput computing: Pull versus Push

ISPDC '05 Proceedings of the The 4th International Symposium on Parallel and Distributed Computing
Stochastic Scheduling With Asymmetric Earliness And Tardiness Penalties Under Random Machine Breakdowns

Probability in the Engineering and Informational Sciences
Models and Algorithms for Stochastic Online Scheduling

Mathematics of Operations Research
Single-machine scheduling to stochastically minimize maximum lateness

Journal of Scheduling
A Stochastic Optimization Algorithm Minimizing Expected Flow Times on Uniforn Processors

IEEE Transactions on Computers
Scheduling: Theory, Algorithms, and Systems

Scheduling: Theory, Algorithms, and Systems
Single machine stochastic scheduling to minimize the expected number of tardy jobs using mathematical programming models

Computers and Industrial Engineering
Setting due dates in a stochastic single machine environment

Computers and Operations Research
Minimizing total tardiness in a stochastic single machine scheduling problem using approximate dynamic programming

Journal of Scheduling
Lower bounds for smith's rule in stochastic machine scheduling

WAOA'10 Proceedings of the 8th international conference on Approximation and online algorithms
Job control in heterogeneous computing systems

Journal of Computer and Systems Sciences International
Minimizing the expected number of tardy jobs when processing times are normally distributed

Operations Research Letters

Controlling computationally intensive heterogeneous computational tasks with directive deadlines

Journal of Computer and Systems Sciences International
Data aggregation for scheduling of resource-intensive computations under uncertainty

Journal of Computer and Systems Sciences International

Quantified Score

Hi-index	0.00

Visualization

Abstract

Various policies for controlling jobs in a problem-oriented computer system are considered. The proposed algorithms belong to the class of search algorithms; they require a large (and, typically, unknown) amount of computations. The problem is to select a dynamic policy for redistributing resources between jobs under uncertainty. The analysis of resource reallocation rules uses probability theory and computer simulation.