A distributed load-balancing policy for a multicomputer
Software—Practice & Experience
Adaptive load sharing in homogeneous distributed systems
IEEE Transactions on Software Engineering
4.2BSD and 4.3BSD as examples of the UNIX system
ACM Computing Surveys (CSUR) - The MIT Press scientific computation series
Load-balancing heuristics and process behavior
SIGMETRICS '86/PERFORMANCE '86 Proceedings of the 1986 ACM SIGMETRICS joint international conference on Computer performance modelling, measurement and evaluation
An Experimental Assessment of Resource Queue Lengths as Load Indices
An Experimental Assessment of Resource Queue Lengths as Load Indices
A Trace-Driven Simulation Study of Dynamic Load Balancing
A Trace-Driven Simulation Study of Dynamic Load Balancing
An intelligent dynamic load balancer for workstation clusters
ACM SIGOPS Operating Systems Review
Predicting parallel applications performance on non-dedicated cluster platforms
ICS '98 Proceedings of the 12th international conference on Supercomputing
IEEE Transactions on Computers
Implementing a performance forecasting system for metacomputing: the Network Weather Service
SC '97 Proceedings of the 1997 ACM/IEEE conference on Supercomputing
Prediction-Based Dynamic Load-Sharing Heuristics
IEEE Transactions on Parallel and Distributed Systems
Predicting Queue Times on Space-Sharing Parallel Computers
IPPS '97 Proceedings of the 11th International Symposium on Parallel Processing
A Fuzzy Load Balancing Service for Network Computing Based on Jini
Euro-Par '01 Proceedings of the 7th International Euro-Par Conference Manchester on Parallel Processing
HCW '99 Proceedings of the Eighth Heterogeneous Computing Workshop
A Measurement-Based Model for Estimation of Resource Exhaustion in Operational Software Systems
ISSRE '99 Proceedings of the 10th International Symposium on Software Reliability Engineering
A hierarchical adaptive distributed algorithm for load balancing
Journal of Parallel and Distributed Computing
Grid resource management
A new fuzzy-decision based load balancing system for distributed object computing
Journal of Parallel and Distributed Computing
A Predictive, Decentralized Load Balancing Approach
IPDPS '05 Proceedings of the 19th IEEE International Parallel and Distributed Processing Symposium (IPDPS'05) - Workshop 2 - Volume 03
Dual and multiple token based approaches for load balancing
Journal of Systems Architecture: the EUROMICRO Journal
Better performance or better manageability?
DEAS '05 Proceedings of the 2005 workshop on Design and evolution of autonomic application software
Another approach to backfilled jobs: applying virtual malleability to expired windows
Proceedings of the 19th annual international conference on Supercomputing
Backfilling with lookahead to optimize the packing of parallel jobs
Journal of Parallel and Distributed Computing
Exploiting idle cycles to execute data mining applications on clusters of PCs
Journal of Systems and Software
Using historical accounting information to predict the resource usage of grid jobs
Future Generation Computer Systems
Extracting and predicting the communication behaviour of parallel applications
International Journal of Parallel, Emergent and Distributed Systems
Energy aware scheduling on desktop grid environment with static performance prediction
SpringSim '09 Proceedings of the 2009 Spring Simulation Multiconference
Platform-independent modeling and prediction of application resource usage characteristics
Journal of Systems and Software
A novel approach for distributed application scheduling based on prediction of communication events
Future Generation Computer Systems
COSPIM: a program optimization system for tightly-coupled heterogeneous environments
ICCOMP'06 Proceedings of the 10th WSEAS international conference on Computers
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A statistical approach is developed for predicting the CPU time, the file I/O, and the memory requirements of a program at the beginning of its life, given the identity of the program. Initially, statistical clustering is used to identify high-density regions of process resource usage. The identified regions form the states for building a state-transition model to characterize the resource usage of each program in its past executions. The prediction scheme uses the knowledge of the program's resource usage in its last execution together with its state-transition model to predict the resource usage in its next execution. The prediction scheme is shown to work using process resource-usage data collected from a VAX 11/780 running 4.3 BSD Unix. The results show that the predicted values correlate strongly with the actual; the coefficient of correlation between the predicted and actual values for CPU time is 0.84. The errors in prediction are mostly small and are heavily skewed toward small values.