Partial network coding: Concept, performance, and application for continuous data collection in sensor networks

  • Authors:

  • Dan Wang;Qian Zhang;Jiangchuan Liu

  • Affiliations:

  • The Hong Kong Polytechnic University, Kowloon, Hong Kong;Hong Kong University of Science and Technology, Kowloon, Hong Kong;Simon Fraser University, Burnaby, BC, Canada

  • Venue:
  • ACM Transactions on Sensor Networks (TOSN)
  • Year:
  • 2008

Quantified Score

Hi-index 0.00

Visualization

Abstract

Wireless sensor networks have been widely used for surveillance in harsh environments. In many such applications, the environmental data are continuously sensed, and data collection by a server is only performed occasionally. Hence, the sensor nodes have to temporarily store the data, and provide easy and on-hand access for the most updated data when the server approaches. Given the expensive server-to-sensor communications, the large amount of sensors and the limited storage space at each tiny sensor, continuous data collection becomes a challenging problem. In this article, we present partial network coding (PNC) as a generic tool for these applications. PNC generalizes the existing network coding (NC) paradigm, an elegant solution for ubiquitous data distribution and collection. Yet PNC allows efficient storage replacement for continuous data, which is a deficiency of the conventional NC. We prove that the performance of PNC is quite close to NC, except for a sub-linear overhead on storage and communications. We then address a set of practical concerns toward PNC-based continuous data collection in sensor networks. Its feasibility and superiority are further demonstrated through simulation results.