Performance Evaluation
PhFit: A General Phase-Type Fitting Tool
TOOLS '02 Proceedings of the 12th International Conference on Computer Performance Evaluation, Modelling Techniques and Tools
Turning back time in Markovian process algebra
Theoretical Computer Science
Analysis and Algorithms for Restart
QEST '04 Proceedings of the The Quantitative Evaluation of Systems, First International Conference
Compositional reversed Markov processes, with applications to G-networks
Performance Evaluation
A Novel Approach for Phase-Type Fitting with the EM Algorithm
IEEE Transactions on Dependable and Secure Computing
Analysis of Restart Mechanisms in Software Systems
IEEE Transactions on Software Engineering
A unifying approach to product-forms in networks with finite capacity constraints
Proceedings of the ACM SIGMETRICS international conference on Measurement and modeling of computer systems
Networks of symmetric multi-class queues with signals changing classes
ASMTA'10 Proceedings of the 17th international conference on Analytical and stochastic modeling techniques and applications
G-networks with synchronised arrivals
Performance Evaluation
HyperStar: Phase-Type Fitting Made Easy
QEST '12 Proceedings of the 2012 Ninth International Conference on Quantitative Evaluation of Systems
Electronic Notes in Theoretical Computer Science (ENTCS)
| Hi-index | 0.00 |
Restart is a common technique for improving response-times in complex systems where the causes of delays can either not be discerned, or not be addressed by the user. With restart, the user aborts a running job that exceeds a deadline, and resubmits it to the system immediately. In many common scenarios, this approach can reduce the response-times that the user experiences. Restart has been well-studied for scenarios where only one user applies restart, and typically in cases where queueing effects can be neglected. In this paper we approach the question of restart in a scenario where restart is applied by many users in a system that can be modelled as an open queueing network. We apply the G-Networks formalism to this problem. We use negative customers to model the abortion and retry of a request. The open G-network uses multiple classes with phase-type distributed service times. This allows the approximation of a preemptive repeat different behaviour as it is natural for multiple restarts of a request. We compute the response time of a request and show that an optimal restart interval can be found. The results are compared with simulation.