Congestion control in IPTV over PON using Digital Fountain forward error correction

  • Authors:
  • Sajjad Zare;Akbar Ghaffarpour Rahbar

  • Affiliations:
  • Computer Networks Research Lab, Sahand University of Technology, Tabriz, Iran;Computer Networks Research Lab, Sahand University of Technology, Tabriz, Iran

  • Venue:
  • Journal of Network and Computer Applications
  • Year:
  • 2014

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Abstract

In a passive optical network (PON), the optical line terminal (OLT) is a bottleneck and congestion prone. Although bit error rate (BER) is ignorable in a PON, but PON may suffer from congestion problem that causes packet loss. Our problem is to reduce packet loss due to congestion. In this paper, two novel frameworks are proposed based on the Digital-Fountain (DF) forward error correction (FEC) with erasure coding approach at IP layer combined with Weighted Round Robin (WRR) and multicast property of PONs in order to achieve efficient video multicasting over PON. The first framework is called Digital-Fountain (DF) Forward Error Correction (FEC) with erasure coding Congestion control (DFC). The second framework is based on the nature of video coding and intelligent packet drop mechanism (called Intelligent Packet Drop with Digital Fountain Correction (IDFC)) to overcome packet-loss due to congestion in the OLT. In DFC, an IPTV service provider uses the DF coding and generates redundant packets from regular IPTV packets in such a way that an optical network unit (ONU) can recover lost packets from received packets, thus resulting in a better video quality. In IDFC, we use the nature of video coding to maintain video quality under congestion. In video coding by a codec, several types of frames can be produced. These types of frames are different based on their scale of information, and therefore, they have different importances. Under congestion state, our DFC and IDFC first drop packets with less importance. Simulation results show that using the proposed frameworks, an ONU can recover lost packets and achieve better video quality under different traffic loads.