Realizing the benefits of wireless network coding in multirate settings

Tae Suk Kim, Ioannis Broustis, Serdar Vural, Dimitris Syrivelis, Shailendra Singh, Srikanth V. Krishnamurthy, Thomas F. La Porta

Research output: Contribution to journalArticlepeer-review

6 Scopus citations

Abstract

Network coding has been proposed as a technique that can potentially increase the transport capacity of a wireless network via mixing data packets at intermediate routers. However, most previous studies either assume a fixed transmission rate or do not consider the impact of using diverse rates on the network coding gain. Since in many cases, network coding implicitly relies on overhearing, the choice of the transmission rate has a big impact on the achievable gains. The use of higher rates works in favor of increasing the native throughput. However, it may in many cases work against effective overhearing. In other words, there is a tension between the achievable network coding gain and the inherent rate gain possible on a link. In this paper, our goal is to drive the network toward achieving the best tradeoff between these two contradictory effects. We design a distributed framework that: 1) facilitates the choice of the best rate on each link while considering the need for overhearing; and 2) dictates the choice of which decoding recipient will acknowledge the reception of an encoded packet. We demonstrate that both of these features contribute significantly toward gains in throughput. We extensively simulate our framework in a variety of topological settings. We also fully implement it on real hardware and demonstrate its applicability and performance gains via proof-of-concept experiments on our wireless testbed. We show that our framework yields throughput gains of up to 390% as compared to what is achieved in a rate-unaware network coding framework.

Original languageEnglish (US)
Article number6296731
Pages (from-to)950-962
Number of pages13
JournalIEEE/ACM Transactions on Networking
Volume21
Issue number3
DOIs
StatePublished - Jan 1 2013

All Science Journal Classification (ASJC) codes

  • Software
  • Computer Science Applications
  • Computer Networks and Communications
  • Electrical and Electronic Engineering

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