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Interoperable mobile agents in heterogeneous wireless sensor networks

Published: 11 November 2013 Publication History

Abstract

We demonstrate interoperable mobile agents for language- and platform-independent wireless sensor network programming, with low-power resource-constrained embedded devices as static nodes and Android-based smartphones as mobile nodes, over disparate networks: 6LoWPAN and Wi-Fi. Representational state transfer architectural principles are applied in agent composition, control and migration and exposing the system resources to the Web: the devices, agents, sensor data, tasks and data processing results. The adaptable agent composition includes the task code in any programming language, the agent migrates according to a resource list and the state, i.e. the intermediate task result, represents the agent as a system resource. Mobile agents are then utilized in two tasks: first to collect light sensor data cooperatively in location, saving the mobile node battery whenever possible, and secondly the magnetometer sensor data with the scanned Wi-Fi access points' signal strength is used to detect groups of mobile nodes moving in the same direction in real-time.

References

[1]
F. Aiello, G. Fortino, R. Gravina, and A. Guerrieri. A java-based agent platform for programming wireless sensor networks. Comput. J., 54(3):439--454, 2011.
[2]
J. Alvarez Lacasia, T. Leppänen, M. Iwai, H. Kobayashi, and K. Sezaki. A method for grouping smartphone users based on wi-fi signal strength. In Forum on Information Technology, Tottori, Japan, September 4--6, 2013. {To appear}.
[3]
T. Leppänen, M. Liu, E. Harjula, A. Ramalingam, J. Ylioja, P. Närhi, J. Riekki, and T. Ojala. Mobile agents for integration of internet of things and wireless sensor networks. In IEEE SMC2013, Manchester, UK, October 13--16. {To appear}.
[4]
T. Leppänen, J. Ylioja, P. Närhi, T. Räty, T. Ojala, and J. Riekki. Holistic energy consumption monitoring in buildings with ip-based wireless sensor networks. In BuildSys'12, pages 195--196, Toronto, Canada, November 6, 2012.
[5]
M. Liu, T. Leppänen, E. Harjula, Z. Ou, A. Ramalingam, M. Ylianttila, and T. Ojala. Distributed resource directory architecture in machine-to-machine communications. In IEEE WiMob 2013 Workshop on Internet of Things Communications and Technologies, Lyon, France, October 7--10, 2013. {To appear}.
[6]
I. Satoh. Mobile agents. In H. Nakashima, H. Aghajan, and J. Augusto, editors, Handbook of Ambient Intelligence and Smart Environments, pages 771--791. Springer US, 2010.

Cited By

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  • (2019)Energy efficient opportunistic edge computing for the Internet of ThingsWeb Intelligence10.3233/WEB-19041417:3(209-227)Online publication date: 16-Aug-2019
  • (2017)Mobile crowdsensing with mobile agentsAutonomous Agents and Multi-Agent Systems10.1007/s10458-015-9311-731:1(1-35)Online publication date: 1-Jan-2017

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cover image ACM Conferences
SenSys '13: Proceedings of the 11th ACM Conference on Embedded Networked Sensor Systems
November 2013
443 pages
ISBN:9781450320276
DOI:10.1145/2517351
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

New York, NY, United States

Publication History

Published: 11 November 2013

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Author Tags

  1. constrained application protocol
  2. embedded web services
  3. mobile agents
  4. wireless sensor networks

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SenSys '13 Paper Acceptance Rate 21 of 123 submissions, 17%;
Overall Acceptance Rate 198 of 990 submissions, 20%

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Cited By

View all
  • (2019)Energy efficient opportunistic edge computing for the Internet of ThingsWeb Intelligence10.3233/WEB-19041417:3(209-227)Online publication date: 16-Aug-2019
  • (2017)Mobile crowdsensing with mobile agentsAutonomous Agents and Multi-Agent Systems10.1007/s10458-015-9311-731:1(1-35)Online publication date: 1-Jan-2017

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