Collecting data in ad-hoc networks with reduced uncertainty

Liron Levin, Alon Efrat, Michael Segal

Research output: Contribution to journalArticlepeer-review

17 Scopus citations


We consider the data gathering problem in wireless ad-hoc networks where a data mule traverses a set of sensors, each with vital information on its surrounding, and collects their data. The mule goal is to collect as much information as possible thereby reducing the information uncertainty but in the same time avoid visiting some of the nodes to minimize its travel distance. We study the problem when the mule travels over a tree or a tour and propose a 3-approximation algorithm that minimizes both the information uncertainty and travel distance. We also show the applicability of our approach for solving data collection problems in varying domains such as temperature monitoring, surveillance systems and sensor placement. Simulation results show that the proposed solution converges to the optimal for varying set of topologies, such as grids, stars, linear and random networks.

Original languageEnglish (US)
Pages (from-to)71-81
Number of pages11
JournalAd Hoc Networks
StatePublished - Jun 2014


  • Approximation algorithm
  • Data gathering
  • Mule traversal
  • Optimization

ASJC Scopus subject areas

  • Software
  • Hardware and Architecture
  • Computer Networks and Communications


Dive into the research topics of 'Collecting data in ad-hoc networks with reduced uncertainty'. Together they form a unique fingerprint.

Cite this