Supporting end-to-end internet QoS for DDS-based large-scale distributed simulation

ABSTRACT

Supporting end-to-end quality-of-service (QoS) in Large-scale distributed interactive simulations (DIS) is hard due to the heterogeneity and scale of communication networks, transient behavior, and the lack of mechanisms that holistically schedule different resources end-to-end. This paper aims to cope with these problems in the context of wide area network (WAN)-based DIS applications that use the OMG Data Distribution Service (DDS) QoS-enabled publish/subscribe middleware. First, we show the design and implementation of the QoS framework, which is a policy-driven architecture that shields DDS-based DIS applications from the details of network QoS mechanisms by specifying per-flow network QoS requirements, performing resource allocation and validation decisions (such as admission control), and enforcing per-flow network QoS at runtime. Second, we evaluate the capabilities of the framework in an experimental large-scale multi-domains environment. The evaluation of the architecture shows that the proposed QoS framework improves the delivery of DDS services over heterogeneous IP networks, and confirms its potential impact for providing network-level differentiated performance.

References

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Index Terms

• Computer systems organization

  • Architectures

    • Distributed architectures

• Computing methodologies

  • Machine learning

    • Machine learning approaches

      • Stochastic games

  • Modeling and simulation

    • Simulation types and techniques

      • Distributed simulation

• Networks

  • Network architectures

• Theory of computation

  • Theory and algorithms for application domains

    • Algorithmic game theory and mechanism design