Abstract

Distributed Computing and Networking In this paper, we focus on applications having quantitative QoS (Quality of Service) requirements on their end-to-end response time (or jitter). We propose a solution allowing the coexistence of two types of quantitative QoS garantees, deterministic and probabilistic, while providing a high resource utilization. Our solution combines the advantages of the deterministic approach and the probabilistic one. The deterministic approach is based on a worst case analysis. The probabilistic approach uses a mathematical model to obtain the probability that the response time exceeds a given value. We assume that flows are scheduled according to non-preemptive FP/FIFO. The packet with the highest fixed priority is scheduled first. If two packets share the same priority, the packet arrived first is scheduled first. We make no particular assumption concerning the flow priority and the nature of the QoS guarantee requested by the flow. An admission control derived from these results is then proposed, allowing each flow to receive a quantitative QoS guarantee adapted to its QoS requirements. An example illustrates the merits of the coexistence of deterministic and probabilistic QoS guarantees.

Highlights

  • To cite this version: Pascale Minet, Steven Martin, Leila Azouz Saidane, Skander Azzaz

  • We propose a solution allowing the coexistence of two types of quantitative QoS guarantees, deterministic and probabilistic, while providing high resource utilization

  • An admission control derived from these results is proposed, allowing each flow to receive a quantitative QoS guarantee adapted to its QoS requirements

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Summary

Context and motivations

We are interested in providing quantitative QoS (Quality of Service) guarantees to various types of applications in their end-to-end response time (or jitter). The admission control presented in this paper will allow us to accept more flows and will offer to each of them a quantitative QoS guarantee in accordance with its requirements. Notice that there is no relationship between the nature of the QoS guarantee required by a flow (deterministic or probabilistic) and its fixed priority.

Problematic of providing quantitative QoS guarantees
Scheduling model
Network model
Traffic model
Related work
Notations
Study of the trajectory of packet m
Delay due to higher priority packets
Delay due to non-preemption
Latest starting time expression
Worst case end-to-end response time
Computation algorithm
Node response time distribution
End-to-end response time distribution
Probabilistic QoS guarantee
Admission control
Model validation
Example
Coexistence benefits
Extended example
Perspectives
Findings
Conclusion
Full Text
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