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Energy saving on DTN using trajectory inference model

Published: 09 April 2018 Publication History

Abstract

Delay or Disruption Tolerant Networks (DTN) are characterized by long delays and intermittent connectivity, requiring efficient energy consumption for increasing the mobile nodes lifetime. The movements of nodes modify the network topology, changing the number of connection opportunities between nodes. This paper proposes a new technique for energy saving on DTN by using a trajectory inference model for mobile nodes powered by machine learning techniques. The objective of this work is to reduce the energy consumption of DTN using a mobility prediction method. Experimental results indicate more than 47% of energy saving on data communication applying the trajectory inference model.

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Cited By

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  • (2022)Non-Terrestrial Networks with UAVs: A Projection on Flying Ad-Hoc NetworksDrones10.3390/drones61103346:11(334)Online publication date: 31-Oct-2022
  • (2021)A Trajectory Inference-based Technique for Energy Efficient Store-and-Forward Technology2021 Wireless Days (WD)10.1109/WD52248.2021.9508277(1-5)Online publication date: 30-Jun-2021
  • (2019)Delay Tolerant Network assisted flying Ad-Hoc network scenario: modeling and analytical perspectiveWireless Networks10.1007/s11276-019-01987-825:5(2675-2695)Online publication date: 1-Jul-2019

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cover image ACM Conferences
SAC '18: Proceedings of the 33rd Annual ACM Symposium on Applied Computing
April 2018
2327 pages
ISBN:9781450351911
DOI:10.1145/3167132
Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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Association for Computing Machinery

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Publication History

Published: 09 April 2018

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Author Tags

  1. delay or disruption tolerant network
  2. energy saving
  3. opportunistic networking
  4. trajectory inference model

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SAC 2018
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SAC 2018: Symposium on Applied Computing
April 9 - 13, 2018
Pau, France

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Overall Acceptance Rate 1,650 of 6,669 submissions, 25%

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Cited By

View all
  • (2022)Non-Terrestrial Networks with UAVs: A Projection on Flying Ad-Hoc NetworksDrones10.3390/drones61103346:11(334)Online publication date: 31-Oct-2022
  • (2021)A Trajectory Inference-based Technique for Energy Efficient Store-and-Forward Technology2021 Wireless Days (WD)10.1109/WD52248.2021.9508277(1-5)Online publication date: 30-Jun-2021
  • (2019)Delay Tolerant Network assisted flying Ad-Hoc network scenario: modeling and analytical perspectiveWireless Networks10.1007/s11276-019-01987-825:5(2675-2695)Online publication date: 1-Jul-2019

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