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

Dan Wang, Qian Zhang, Jiangchuan Liu

Research output: Journal article publicationJournal articleAcademic researchpeer-review

23 Citations (Scopus)

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.
Original languageEnglish
Article number14
JournalACM Transactions on Sensor Networks
Volume4
Issue number3
DOIs
Publication statusPublished - 1 May 2008

Keywords

  • Network coding
  • Random linear coding
  • Sensor networks

ASJC Scopus subject areas

  • Computer Networks and Communications

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