Rakeness-based compressed sensing and hub spreading to administer short/long-range communication tradeoff in IoT Settings

Mauro Mangia, Fabio Pareschi, Riccardo Rovatti, Gianluca Setti

Research output: Contribution to journalArticlepeer-review

5 Scopus citations

Abstract

In common distributed sensing scenarios, a number of local wireless sensor networks perform sets of acquisitions that must be sent to a central collector which may be far from the measurement fields. Hence, readings from individual nodes may reach their destination by exploiting both local and long-range transmission capabilities. The compressed sensing (CS) paradigm may help finding a convenient mix of the two options, especially if it follows the rakeness-based design flow that has been recently introduced. CS is exploited by identifying local hubs that aggregate many sensor readings in a smaller number of quantities that are then transmitted to the central collector. We here show that, depending on the relative cost of local versus long-range transmission, carefully administering the choice of the hubs, the breadth of the neighborhood from which they collect readings, as well as the coefficients with which those readings a linearly aggregated, one may significantly reduce the energy needed to sample the field. Simulations indicate that savings may be over 50% for values of the parameters modeling nowadays local and long-range transmission technologies.
Original languageEnglish (US)
Pages (from-to)2220-2233
Number of pages14
JournalIEEE Internet of Things Journal
Volume5
Issue number3
DOIs
StatePublished - Jun 1 2018
Externally publishedYes

ASJC Scopus subject areas

  • Signal Processing
  • Information Systems
  • Information Systems and Management
  • Computer Science Applications
  • Hardware and Architecture
  • Computer Networks and Communications

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