Stochastic Process Models for Packet/Analytic-Based Network Simulations

ABSTRACT

We present our preliminary work that develops a new approach to hybrid packet/analytic network simulations for improved network simulation fidelity, scale, and simulation efficiency. Much work in the literature addresses this topic, including [10] [11] [8] [12] [13] and others. Current approaches rely upon models, which we refer to in this paper as Deterministic Fluid Models [9] [12], to address the analytic modeling aspects of these hybrid simulations. Instead we draw upon an extensive literature on stochastic models of queues and (eventually) networks of queues to implement a hybrid stochastic model/packet network simulation. We will refer to our approach as Stochastic Fluid Models throughout this paper. We outline our approach, present test cases, and present simulation results comparing the measured queue metrics from our approach for hybrid simulation to those of a deterministic fluid model hybrid simulation and a full packet–level simulation. We also discuss plans for future areas of research on this approach.

REFERENCES

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INDEX TERMS

Primary Classification:
  I. Computing Methodologies
  I.6 SIMULATION AND MODELING
      I.6.3 Applications

Additional Classification:
  C. Computer Systems Organization
  C.2 COMPUTER-COMMUNICATION NETWORKS
      C.2.1 Network Architecture and Design
          Subjects: Network communications
  C.4 PERFORMANCE OF SYSTEMS
      Subjects: Modeling techniques

  G. Mathematics of Computing
  G.3 PROBABILITY AND STATISTICS
      Subjects: Queueing theory; Stochastic processes

General Terms:
Design

Keywords:
Hybrid Simulation Models, Event Driven Simulations, Network Models, Stochastic Queues and Diffusion Equations