The κ factor: inferring protocol performance using inter-link reception correlation

  • Authors:

  • Kannan Srinivasan;Mayank Jain;Jung Il Choi;Tahir Azim;Edward S. Kim;Philip Levis;Bhaskar Krishnamachari

  • Affiliations:

  • Stanford University, Stanford, CA, USA;Stanford University, Stanford, CA, USA;Stanford University, Stanford, CA, USA;Stanford University, Stanford, CA, USA;University of Southern California, Los Angeles, CA, USA;Stanford University, Stanford, CA, USA;University of Southern California, Los Angeles, CA, USA

  • Venue:
  • Proceedings of the sixteenth annual international conference on Mobile computing and networking
  • Year:
  • 2010

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Abstract

This paper explores metrics that capture to what degree packet reception on different links is correlated. Specifically, it explores metrics that shed light on when and why opportunistic routing and network coding protocols perform well (or badly). It presents a new metric, κ that, unlike existing widely used metrics, has no bias based on the packet reception ratios of links. This lack of bias makes κ a better predictor of performance of opportunistic routing and network coding protocols. Comparing Deluge and Rateless Deluge, Deluge's network coding counterpart, we find that κ can predict which of the two is best suited for a given environment. For example, irrespective of the packet reception ratios of the links, if the average κ of the link pairs is very high (close to 1.0), then using a protocol that does not code works better than using a network coding protocol. Measuring κ on several 802.15.4 and 802.11 testbeds, we find that it varies significantly across network topologies and link layers. κ can be a metric for quantifying what kind of a network is present and help decide which protocols to use for that network.