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Analyzing different levels of geographic context awareness in agent ferrying over VANETs

Published: 21 March 2011 Publication History

Abstract

The use of mobile software agents is a promising approach to implement services over ad hoc networks. This paper presents an analysis of mobile autonomous agents with different degrees of intelligence that allow them to make usage of the positioning information of vehicle carried sensor nodes with different depth of complexity, considering the nodes' current and future locations. The agents' intelligence is used to decide their movement during opportunistic connections among the nodes in order to accomplish missions. In this work, the analysis is done over an application of "virtual sensors", implemented by services provided by the mobile agents. These agents run on top of an infrastructure-less Vehicular Ad hoc Network (VANET). Simulation results are presented and discussed to support the proposed ideas.

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Cited By

View all
  • (2021)SafeSmart: A VANET System for Faster Responses and Increased Safety in Time-Critical ScenariosIEEE Access10.1109/ACCESS.2021.31263349(151590-151606)Online publication date: 2021
  • (2018)Learning for adaptive anycast in vehicular delay tolerant networksJournal of Ambient Intelligence and Humanized Computing10.1007/s12652-018-0819-yOnline publication date: 12-May-2018
  • (2015)S-Aframe: Agent-Based Multilayer Framework With Context-Aware Semantic Service for Vehicular Social NetworksIEEE Transactions on Emerging Topics in Computing10.1109/TETC.2015.23959593:1(44-63)Online publication date: Mar-2015
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cover image ACM Conferences
SAC '11: Proceedings of the 2011 ACM Symposium on Applied Computing
March 2011
1868 pages
ISBN:9781450301138
DOI:10.1145/1982185
Permission to make digital or hard copies of all or part 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 components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Publication History

Published: 21 March 2011

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Author Tags

  1. VANETs
  2. ad hoc networks
  3. context awareness
  4. opportunistic communication
  5. software agents

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SAC'11
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SAC'11: The 2011 ACM Symposium on Applied Computing
March 21 - 24, 2011
TaiChung, Taiwan

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

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Cited By

View all
  • (2021)SafeSmart: A VANET System for Faster Responses and Increased Safety in Time-Critical ScenariosIEEE Access10.1109/ACCESS.2021.31263349(151590-151606)Online publication date: 2021
  • (2018)Learning for adaptive anycast in vehicular delay tolerant networksJournal of Ambient Intelligence and Humanized Computing10.1007/s12652-018-0819-yOnline publication date: 12-May-2018
  • (2015)S-Aframe: Agent-Based Multilayer Framework With Context-Aware Semantic Service for Vehicular Social NetworksIEEE Transactions on Emerging Topics in Computing10.1109/TETC.2015.23959593:1(44-63)Online publication date: Mar-2015
  • (2013)Using Mobile Agents in Vehicular Networks for Data ProcessingProceedings of the 2013 IEEE 14th International Conference on Mobile Data Management - Volume 0210.1109/MDM.2013.57(11-14)Online publication date: 3-Jun-2013

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