Markovian-based traffic modeling for mobile ad hoc networks

  • Authors:
  • Carlos T. Calafate;P. Manzoni;Juan-Carlos Cano;M. P. Malumbres

  • Affiliations:
  • Universidad Politécnica de Valencia, Camino de Vera, S/N, 46022 Valencia, Spain;Universidad Politécnica de Valencia, Camino de Vera, S/N, 46022 Valencia, Spain;Universidad Politécnica de Valencia, Camino de Vera, S/N, 46022 Valencia, Spain;Universidad Politécnica de Valencia, Camino de Vera, S/N, 46022 Valencia, Spain

  • Venue:
  • Computer Networks: The International Journal of Computer and Telecommunications Networking
  • Year:
  • 2009

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Abstract

Mobile ad hoc networks (MANETs) show very significant difference with respect to other computer networks due to the presence of extremely large packet loss bursts. The development of protocols for mobile ad hoc networks, especially multimedia protocols, require extensive evaluation either through simulation or real-life tests. Such testing consumes a great amount of resources both in terms of time and trace file sizes. Therefore, finding efficient means of reducing the amount of data that is stored and processed is quite important to accelerate the evaluation of different audio/video streaming applications. If, moreover, we are able to model the loss pattern experienced, we can further accelerate the evaluation process. In this work we propose two models based on hidden Markov chains that are able to grasp both packet arrivals and packet loss patterns in MANETs. A simpler two-state model is proposed to model losses when proactive routing protocols are used, while a more complex three-state model is proposed for reactive routing protocols. We also introduce a new set for packet loss pattern measurements that can be of interest for the evaluation of audio/video streaming applications. Experimental results show that the proposed models can adequately reproduce extremely long packet loss patterns, typical of MANET environments, with a high degree of accuracy. Overall, we find that the proposed models are able to significantly reduce both the simulation time and the trace file sizes required.