An artificial bee colony algorithm for data collection path planning in sparse wireless sensor networks

Wei Lun Chang, Deze Zeng, Rung Ching Chen, Song Guo

Research output: Journal article publicationJournal articleAcademic researchpeer-review

58 Citations (Scopus)

Abstract

In sparse wireless sensor networks, a mobile robot is usually exploited to collect the sensing data. Each sensor has a limited transmission range and the mobile robot must get into the coverage of each sensor node to obtain the sensing data. To minimize the energy consumption on the traveling of the mobile robot, it is significant to plan a data collection path with the minimum length to complete the data collection task. In this paper, we observe that this problem can be formulated as traveling salesman problem with neighborhoods, which is known to be NP-hard. To address this problem, we apply the concept of artificial bee colony (ABC) and design an ABC-based path planning algorithm. Simulation results validate the correctness and high efficiency of our proposal.
Original languageEnglish
Pages (from-to)375-383
Number of pages9
JournalInternational Journal of Machine Learning and Cybernetics
Volume6
Issue number3
DOIs
Publication statusPublished - 1 Jun 2015
Externally publishedYes

Keywords

  • Artificial bee colony algorithm
  • Sparse wireless sensor network
  • Traveling salesman problem with neighborhoods

ASJC Scopus subject areas

  • Software
  • Computer Vision and Pattern Recognition
  • Artificial Intelligence

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