Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Discrete Event System Specification for IoT Applications.

Sensors (Basel, Switzerland)·2024
Same authorSame journal

Mitigating the negative impact of new buildings on existing buildings' user comfort-a case study analysis.

Simulation·2023
Same author

Advanced models for centroidal particle dynamics: short-range collision avoidance in dense crowds.

Simulation·2021
Same author

A DEVS-based engine for building digital quadruplets.

Simulation·2021

Related Experiment Video

Updated: Aug 29, 2025

Finite Element Modelling of a Cellular Electric Microenvironment
08:23

Finite Element Modelling of a Cellular Electric Microenvironment

Published on: May 18, 2021

3.5K

A grid-shaped cellular modeling approach for wireless sensor networks.

Khaldoon Al-Zoubi1, Gabriel A Wainer2

  • 1Faculty of Computer & Information Technology, Jordan University of Science and Technology (JUST), Jordan.

Simulation
|September 12, 2022
PubMed
Summary
This summary is machine-generated.

This study introduces a novel spatial modeling method for Wireless Sensor Networks (WSNs) using Cell-Discrete-Event Systems Specification (DEVS). The approach simplifies WSN modeling to enhance network lifetime through efficient energy management strategies.

Keywords:
Cell-Discrete-Event Systems SpecificationModeling and simulationenergy modelingspatial modelingwireless sensor network

More Related Videos

Creating a Structurally Realistic Finite Element Geometric Model of a Cardiomyocyte to Study the Role of Cellular Architecture in Cardiomyocyte Systems Biology
08:54

Creating a Structurally Realistic Finite Element Geometric Model of a Cardiomyocyte to Study the Role of Cellular Architecture in Cardiomyocyte Systems Biology

Published on: April 18, 2018

9.8K
Computational Modeling of Retinal Neurons for Visual Prosthesis Research - Fundamental Approaches
10:50

Computational Modeling of Retinal Neurons for Visual Prosthesis Research - Fundamental Approaches

Published on: June 21, 2022

1.8K

Related Experiment Videos

Last Updated: Aug 29, 2025

Finite Element Modelling of a Cellular Electric Microenvironment
08:23

Finite Element Modelling of a Cellular Electric Microenvironment

Published on: May 18, 2021

3.5K
Creating a Structurally Realistic Finite Element Geometric Model of a Cardiomyocyte to Study the Role of Cellular Architecture in Cardiomyocyte Systems Biology
08:54

Creating a Structurally Realistic Finite Element Geometric Model of a Cardiomyocyte to Study the Role of Cellular Architecture in Cardiomyocyte Systems Biology

Published on: April 18, 2018

9.8K
Computational Modeling of Retinal Neurons for Visual Prosthesis Research - Fundamental Approaches
10:50

Computational Modeling of Retinal Neurons for Visual Prosthesis Research - Fundamental Approaches

Published on: June 21, 2022

1.8K

Area of Science:

  • Computer Science
  • Network Engineering
  • Simulation Modeling

Background:

  • Wireless Sensor Networks (WSNs) are increasingly prevalent in various applications.
  • Existing WSN modeling methods can be complex and inefficient.
  • Optimizing WSN energy consumption is crucial for extending network operational life.

Purpose of the Study:

  • To introduce a new, simplified spatial modeling method for Wireless Sensor Networks (WSNs).
  • To demonstrate the conversion of spatial WSN models into the Cell-Discrete-Event Systems Specification (DEVS) formalism.
  • To analyze energy consumption patterns and propose control methods for prolonging WSN lifetime.

Main Methods:

  • Partitioning the WSN space into cells with defined behaviors (sensors, obstacles).
  • Automatic runtime conversion of spatial models to DEVS models.
  • Case studies analyzing node-level energy use (routing, transmission) and cluster-level residual energy control.

Main Results:

  • The proposed spatial modeling method simplifies the creation of WSN models.
  • Analysis of energy consumption at node and cluster levels provides insights for optimization.
  • The DEVS-based approach facilitates efficient WSN simulation and analysis.

Conclusions:

  • Spatial modeling offers a simple yet efficient approach to building WSN models.
  • Understanding and controlling energy usage at different network levels is key to extending WSN lifetime.
  • The Cell-DEVS formalism provides a robust framework for WSN simulation and analysis.