Research Article
Fair workload distribution for multi-server systems with pulling strategies
@INPROCEEDINGS{10.4108/eai.25-10-2016.2267058, author={Sabina Rossi and Andrea Marin}, title={Fair workload distribution for multi-server systems with pulling strategies}, proceedings={10th EAI International Conference on Performance Evaluation Methodologies and Tools}, publisher={ACM}, proceedings_a={VALUETOOLS}, year={2017}, month={5}, keywords={markov models fork-join queueing systems load balancing rate adaptation}, doi={10.4108/eai.25-10-2016.2267058} }
- Sabina Rossi
Andrea Marin
Year: 2017
Fair workload distribution for multi-server systems with pulling strategies
VALUETOOLS
ACM
DOI: 10.4108/eai.25-10-2016.2267058
Abstract
We consider systems with a single queue and multiple parallel servers. Each server fetches a job from the queue immediately after completing its current work. We propose a pulling strategy that aims at achieving a fair distribution of the number of processed jobs among the servers. We show that if the service times are exponentially distributed then our strategy ensures that in the long run the expected difference among the processed jobs at each server is finite while maintaining a reasonable throughput. We give the analytical expressions for the stationary distribution and the relevant stationary performance indices like the throughput and the system’s balance. Interestingly, the proposed strategy can be used to control the join-queue length in fork-join queues and the analytical model gives the closed form expression of the performance indices in saturation.