1st International ICST Conference on Performance Evaluation Methodologies and Tools

Research Article

A novel approach to scalable CAC for real-time traffic in sink-tree networks with aggregate scheduling

  • @INPROCEEDINGS{10.1145/1190095.1190106,
        author={Luciano  Lenzini and Linda  Martorini and Enzo  Mingozzi and Giovanni  Stea},
        title={A novel approach to scalable CAC for real-time traffic in sink-tree networks with aggregate scheduling},
        proceedings={1st International ICST Conference on Performance Evaluation Methodologies and Tools},
        publisher={ACM},
        proceedings_a={VALUETOOLS},
        year={2012},
        month={4},
        keywords={Admission Control Network Calculus Aggregate Scheduling.},
        doi={10.1145/1190095.1190106}
    }
    
  • Luciano Lenzini
    Linda Martorini
    Enzo Mingozzi
    Giovanni Stea
    Year: 2012
    A novel approach to scalable CAC for real-time traffic in sink-tree networks with aggregate scheduling
    VALUETOOLS
    ACM
    DOI: 10.1145/1190095.1190106
Luciano Lenzini1,*, Linda Martorini1,*, Enzo Mingozzi1,*, Giovanni Stea1,*
  • 1: Dipartimento di Ingegneria dell’Informazione, University of Pisa, Italy. Via Diotisalvi, 2 56122 Pisa, Italy - Ph. +39 050 2217599
*Contact email: l.lenzini@iet.unipi.it, l.martorini@iet.unipi.it, e.mingozzi@iet.unipi.it, g.stea@iet.unipi.it

Abstract

In this paper we investigate the problem of scalable admission control for real-time traffic in sink-tree networks employing per-aggregate resource management policies, like MPLS or DiffServ. Every traffic flow entering the network at an ingress node, and flowing towards a given egress node, specifies its leaky-bucket parameters and a required delay bound for traversing the network. We propose an algorithm that admits a new flow if a guarantee can be given that the required delay bound, besides those of other already established flows, are not exceeded. We identify properties of sink-tree networks based on which we considerably reduce the complexity of the proposed algorithm, and we show that the latter approaches the theoretical lower bound on the worst case complexity of any algorithm working under the same hypotheses. Finally, we show that the algorithm lends itself to a distributed implementation, thus allowing for better scalability.