Dynamic itinerary planning for mobile agents with a content-specific approach in wireless sensor networks

Kaoru Ota, Mianxiong Dong, Junbo Wang, Song Guo, Zixue Cheng, Minyi Guo

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

15 Citations (Scopus)


We study data fusion in sensor networks using mobile agents (MAs),which are capable of saving energy of sensor nodes and performing advanced computation functions based on the requests of various applications. Research on MAs still remains unfledged in development of application-oriented data fusion, which is highly desired in wireless sensor networks (WSNs) deployed in recent days for environmental and disaster monitoring. In this paper, we propose a dynamic itinerary planning for MAs (DIPMA) to collect data from sensor networks with an application-oriented approach. In particular, the DIPMA algorithm is applied to the data collection for frost prediction which is a real-world application in agriculture using next-generation sensor networks. The performance of the DIPMA is evaluated by simulations and the experimental results show that the total execution time of MA can be reduced significantly with our approach while sound prediction accuracy is maintained.
Original languageEnglish
Title of host publication2010 IEEE 72nd Vehicular Technology Conference Fall, VTC2010-Fall - Proceedings
Publication statusPublished - 1 Dec 2010
Externally publishedYes
Event2010 IEEE 72nd Vehicular Technology Conference Fall, VTC2010-Fall - Ottawa, ON, Canada
Duration: 6 Sep 20109 Sep 2010


Conference2010 IEEE 72nd Vehicular Technology Conference Fall, VTC2010-Fall
CityOttawa, ON


  • Application-oriented data fusion
  • Itinerary planning
  • Mobile agent
  • Wireless sensor network

ASJC Scopus subject areas

  • Computer Science Applications
  • Electrical and Electronic Engineering
  • Applied Mathematics

Cite this