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Cellular automata based models of wireless sensor networks

Authors:

Wei Li,

Albert Y. Zomaya,

Adel Al-JumailyAuthors Info & Claims

MobiWAC '09: Proceedings of the 7th ACM international symposium on Mobility management and wireless access

Pages 1 - 6

https://doi.org/10.1145/1641776.1641777

Published: 26 October 2009 Publication History

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Abstract

Large scale wireless sensor networks present interesting challenges in many applications due to a number of factors, such as, energy constraints, the dynamic nature of the network topology and various application needs. An important issue is how the sensor nodes can achieve efficient global behavior under distributed control mechanisms? One of many possible solutions is to construct a self-organized wireless sensor network to deal with this challenge. This paper presents an algorithm to construct a self-organized wireless sensor network based on two dimensional cellular automata that can provide better understanding for how local behavior at node level influences the overall system behavior and affect the system performance. Two types of Cellular Automata (CA) are considered; for the synchronous CA based system; the regular patterns are identified and discussed. To overcome some limitations arising from the use of a synchronous CA implementation an asynchronous CA is employed.

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Cited By

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Phong Truong T(2022)Simulating Dispersion of Field-burning Smoke with Cellular AutomataProceedings of the 2022 5th International Conference on Electronics, Communications and Control Engineering10.1145/3531028.3531050(135-140)Online publication date: 25-Mar-2022
https://dl.acm.org/doi/10.1145/3531028.3531050
Li CTsai C(2020)Skin Impedance Measurement in Wearable Non-invasive Optical Blood Glucose Monitors2020 IEEE 2nd International Workshop on System Biology and Biomedical Systems (SBBS)10.1109/SBBS50483.2020.9314947(1-4)Online publication date: Dec-2020
https://doi.org/10.1109/SBBS50483.2020.9314947
Hassan MHussain FChoudhury S(2018)Connectivity preserving obstacle avoidance localized motion planning algorithms for mobile wireless sensor networksPeer-to-Peer Networking and Applications10.1007/s12083-018-0656-yOnline publication date: 4-May-2018
https://doi.org/10.1007/s12083-018-0656-y
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Index Terms

Cellular automata based models of wireless sensor networks
1. Networks
  1. Network properties
    1. Network structure

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Information & Contributors

Information

Published In

MobiWAC '09: Proceedings of the 7th ACM international symposium on Mobility management and wireless access

October 2009

168 pages

ISBN:9781605586175

DOI:10.1145/1641776

General Chair:
Albert Y. Zomaya
University of Sydney, Australia
,
Program Chair:
Bjorn Landfeldt
University of Sydney, Australia

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 26 October 2009

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Invited-talk

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MSWiM '09

Sponsor:

SIGSIM

MSWiM '09: The 12th ACM International Conference on Modeling, Analysis and Simulation of Wireless and Mobile Systems

October 26 - 27, 2009

Tenerife, Canary Islands, Spain

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Overall Acceptance Rate 83 of 272 submissions, 31%

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Cited By

View all

Phong Truong T(2022)Simulating Dispersion of Field-burning Smoke with Cellular AutomataProceedings of the 2022 5th International Conference on Electronics, Communications and Control Engineering10.1145/3531028.3531050(135-140)Online publication date: 25-Mar-2022
https://dl.acm.org/doi/10.1145/3531028.3531050
Li CTsai C(2020)Skin Impedance Measurement in Wearable Non-invasive Optical Blood Glucose Monitors2020 IEEE 2nd International Workshop on System Biology and Biomedical Systems (SBBS)10.1109/SBBS50483.2020.9314947(1-4)Online publication date: Dec-2020
https://doi.org/10.1109/SBBS50483.2020.9314947
Hassan MHussain FChoudhury S(2018)Connectivity preserving obstacle avoidance localized motion planning algorithms for mobile wireless sensor networksPeer-to-Peer Networking and Applications10.1007/s12083-018-0656-yOnline publication date: 4-May-2018
https://doi.org/10.1007/s12083-018-0656-y
Choudhury S(2016)Cellular Automata and Wireless Sensor NetworksEmergent Computation10.1007/978-3-319-46376-6_14(321-335)Online publication date: 5-Nov-2016
https://doi.org/10.1007/978-3-319-46376-6_14
Choudhury SSalomaa KAkl S(2015)Cellular automata and object monitoring in mobile wireless sensor networks2015 IEEE Wireless Communications and Networking Conference (WCNC)10.1109/WCNC.2015.7127664(1344-1349)Online publication date: Mar-2015
https://doi.org/10.1109/WCNC.2015.7127664
Byun HYu J(2014)Cellular-Automaton-Based Node Scheduling Control for Wireless Sensor NetworksIEEE Transactions on Vehicular Technology10.1109/TVT.2014.230380363:8(3892-3899)Online publication date: Oct-2014
https://doi.org/10.1109/TVT.2014.2303803
Athanassopoulos SKaklamanis CKalfountzos GKatsikouli PPapaioannou E(2013)Simulation of Topology Control Algorithms in Wireless Sensor Networks Using Cellular AutomataInternational Journal of Communications, Network and System Sciences10.4236/ijcns.2013.6703606:07(333-345)Online publication date: 2013
https://doi.org/10.4236/ijcns.2013.67036
Ko SKim HHan Y(2013)A CA model for target tracking in distributed mobile wireless sensor network2013 13th International Conference on Control, Automation and Systems (ICCAS 2013)10.1109/ICCAS.2013.6704167(1356-1361)Online publication date: Oct-2013
https://doi.org/10.1109/ICCAS.2013.6704167
Choudhury SAkl SSalomaa K(2012)Energy efficient cellular automaton based algorithms for mobile wireless sensor networks2012 IEEE Wireless Communications and Networking Conference (WCNC)10.1109/WCNC.2012.6214185(2341-2346)Online publication date: Apr-2012
https://doi.org/10.1109/WCNC.2012.6214185
Choudhury SSalomaa KAkl S(2012)A cellular automaton model for connectivity preserving deployment of mobile wireless sensors2012 IEEE International Conference on Communications (ICC)10.1109/ICC.2012.6364914(6545-6549)Online publication date: Jun-2012
https://doi.org/10.1109/ICC.2012.6364914
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