The limited performance benefits of migrating active processes for load sharing
SIGMETRICS '88 Proceedings of the 1988 ACM SIGMETRICS conference on Measurement and modeling of computer systems
The available capacity of a privately owned workstation environment
Performance Evaluation
On the self-similar nature of Ethernet traffic
SIGCOMM '93 Conference proceedings on Communications architectures, protocols and applications
Exploiting process lifetime distributions for dynamic load balancing
Proceedings of the 1996 ACM SIGMETRICS international conference on Measurement and modeling of computer systems
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
Time Series Analysis: Forecasting and Control
Time Series Analysis: Forecasting and Control
ICDCS '97 Proceedings of the 17th International Conference on Distributed Computing Systems (ICDCS '97)
Dome: Parallel Programming in a Heterogeneous Multi-User Environment
Dome: Parallel Programming in a Heterogeneous Multi-User Environment
A Comparison of Queueing, Cluster and Distributed Computing Systems
A Comparison of Queueing, Cluster and Distributed Computing Systems
Characterizing NAS Benchmark Performance on Shared Heterogeneous Networks
IPDPS '02 Proceedings of the 16th International Parallel and Distributed Processing Symposium
Network-Aware Parallel Computing with Remos
LCPC '98 Proceedings of the 11th International Workshop on Languages and Compilers for Parallel Computing
Future Generation Computer Systems
Autonomously improving query evaluations over multidimensional data in distributed hash tables
Proceedings of the 2013 ACM Cloud and Autonomic Computing Conference
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Understanding how host load changes over time is instrumental in predicting the execution time of tasks or jobs, such as in dynamic load balancing and distributed soft real-time systems.To improve this understanding, we collected week-long, 1 Hz resolution Unix load average traces on 38 different machines including production and research cluster machines, compute servers, and desktop workstations Separate sets of traces were collected at two different times of the year. The traces capture all of the dynamic load information available to user-level programs on these machines. We present a detailed statistical analysis of these traces here, including summary statistics, distributions, and time series analysis results. Two significant new results are that load is self-similar and that it displays epochal behavior. All of the traces exhibit a high degree of self similarity with Hurst parameters ranging from .63 to .97, strongly biased toward the top of that range. The traces also display epochal behavior in that the local frequency content of the load signal remains quite stable for long periods of time (150-450 seconds mean) and changes abruptly at epoch boundaries.