Characteristics of a Large Shared Memory Production Workload
JSSPP '01 Revised Papers from the 7th International Workshop on Job Scheduling Strategies for Parallel Processing
A dynamic load distribution strategy for systems under high task variation and heavy traffic
Proceedings of the 2003 ACM symposium on Applied computing
A least flow-time first load sharing approach for distributed server farm
Journal of Parallel and Distributed Computing
Multiple Job Scheduling in a Connection-Limited Data Parallel System
IEEE Transactions on Parallel and Distributed Systems
Resource overbooking and application profiling in a shared Internet hosting platform
ACM Transactions on Internet Technology (TOIT)
Cloudy: heterogeneous middleware for in time queries processing
Proceedings of the 17th International Database Engineering & Applications Symposium
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We consider a distributed server system and ask which policy should be used for assigning tasks to hosts. In our server, tasks are not preemptible. In addition, the task's service demand is not known a priori. We are particularly concerned with the case where the workload is heavy-tailed, as is characteristic of many empirically measured computer workloads. We analyze several natural task assignment policies and propose a new one TAGS (Task Assignment based on Guessing Size).The TAGS algorithm is counterintuitive in many respects, including load unbalancing, non-work-conserving, and fairness. We find that under heavy-tailed workloads, TAGS can outperform all task assignment policies known to us by several orders of magnitude with respect to both mean response time and mean slowdown, provided the system load is not too high.