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

Maximum Power Transfer01:16

Maximum Power Transfer

1.0K
Numerous practical applications within engineering disciplines, such as telecommunications, necessitate optimizing power delivery to a connected load. This pursuit, however, entails inherent internal losses, which can either equal or exceed the power supplied to the load. The Thevenin equivalent circuit is helpful in finding the maximum power a linear circuit can deliver to a load. It is assumed in this context that the load resistance can be adjusted.
By substituting the entire circuit with...
1.0K
Frequency-Domain Interpretation of PD Control01:24

Frequency-Domain Interpretation of PD Control

397
Proportional-Derivative (PD) controllers are widely used in fan control systems to improve stability and performance. A fan control system can be effectively represented using a Bode plot to illustrate the impact of a PD controller through its transfer function. The Bode plot visually conveys how PD control modifies the fan's response across various frequencies, providing a frequency domain interpretation of the controller's behavior.
The proportional control gain, combined with the...
397
Maximum Power Flow and Line Loadability01:23

Maximum Power Flow and Line Loadability

653
The maximum power flow for lossy transmission lines is derived using ABCD parameters in phasor form. These parameters create a matrix relationship between the sending-end and receiving-end voltages and currents, allowing the determination of the receiving-end current. This relationship facilitates calculating the complex power delivered to the receiving end, from which real and reactive power components are derived.
653
Time-Domain Interpretation of PD Control01:07

Time-Domain Interpretation of PD Control

421
Proportional-Derivative (PD) control is a widely used control method in various engineering systems to enhance stability and performance. In a system with only proportional control, common issues include high maximum overshoot and oscillation, observed in both the error signal and its rate of change. This behavior can be divided into three distinct phases: initial overshoot, subsequent undershoot, and gradual stabilization.
Consider the example of control of motor torque. Initially, a positive...
421
Radial System Protection01:23

Radial System Protection

461
Radial systems employ time-delay overcurrent relays to reduce load interruptions. When a fault occurs, the nearest breaker opens first, while upstream breakers remain closed due to longer delay settings. This approach ensures minimal disruption to the rest of the system.
In a radial system with a fault downstream of the third breaker, ideally, only the third breaker will open, isolating the fault and interrupting the load connected beyond it. The second breaker has a longer delay setting,...
461
Receiver Operating Characteristic Plot01:15

Receiver Operating Characteristic Plot

518
A ROC (Receiver Operating Characteristic) plot is a graphical tool used to assess the performance of a binary classification model by illustrating the trade-off between sensitivity (true positive rate) and specificity (false positive rate). By plotting sensitivity against 1 - specificity across various threshold settings, the ROC curve shows how well the model distinguishes between classes, with a curve closer to the top-left corner indicating a more accurate model. The area under the ROC curve...
518

You might also read

Related Articles

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

Sort by
Same author

Multimodal Biometric Framework for Evaluating Emotional Impact of Chromatic Manipulation in Cinematic Content.

Sensors (Basel, Switzerland)·2026
Same author

A Dataset of University Students' Stress and Anxiety Levels based on Questionnaires and Wearable Sensors.

Scientific data·2026
Same author

A Systematic Review and Energy-Centric Taxonomy of Jamming Attacks and Countermeasures in Wireless Sensor Networks.

Sensors (Basel, Switzerland)·2026
Same author

Enhancing survival prediction for COVID-19 in diabetic patients in Mexico: integrating RMST, propensity score matching, and ensemble machine learning.

Frontiers in endocrinology·2026
Same author

Forehead and In-Ear EEG Acquisition and Processing: Biomarker Analysis and Memory-Efficient Deep Learning Algorithm for Sleep Staging with Optimized Feature Dimensionality.

Sensors (Basel, Switzerland)·2025
Same author

Adaptive Jamming Mitigation for Clustered Energy-Efficient LoRa-BLE Hybrid Wireless Sensor Networks.

Sensors (Basel, Switzerland)·2025

Related Experiment Video

Updated: Feb 27, 2026

Evaluation of an Exclusive Spur Dike U-Turn Design with Radar-Collected Data and Simulation
11:41

Evaluation of an Exclusive Spur Dike U-Turn Design with Radar-Collected Data and Simulation

Published on: February 1, 2020

21.0K

MPH-M, AODV-M and DSR-M Performance Evaluation under Jamming Attacks.

Carolina Del-Valle-Soto1, Carlos Mex-Perera2, Raul Monroy3

  • 1Universidad Panamericana. Facultad de Ingeniería. Prolongación Calzada Circunvalación Poniente 49, Zapopan, Jalisco 45010, Mexico. cvalle@up.edu.mx.

Sensors (Basel, Switzerland)
|July 6, 2017
PubMed
Summary
This summary is machine-generated.

This study introduces a jamming attack mitigation scheme for wireless routing protocols, enhancing Multi-Parent Hierarchical (MPH) over Ad hoc On Demand Distance Vector (AODV) and Dynamic Source Routing (DSR). MPH-M demonstrates superior performance and resilience against jamming attacks.

Keywords:
Wireless Sensor Networksjammingrouting algorithms

More Related Videos

Continuous-Wave Propagation Channel-Sounding Measurement System - Testing, Verification, and Measurements
09:36

Continuous-Wave Propagation Channel-Sounding Measurement System - Testing, Verification, and Measurements

Published on: June 25, 2021

3.6K
Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit
05:30

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit

Published on: September 8, 2023

1.2K

Related Experiment Videos

Last Updated: Feb 27, 2026

Evaluation of an Exclusive Spur Dike U-Turn Design with Radar-Collected Data and Simulation
11:41

Evaluation of an Exclusive Spur Dike U-Turn Design with Radar-Collected Data and Simulation

Published on: February 1, 2020

21.0K
Continuous-Wave Propagation Channel-Sounding Measurement System - Testing, Verification, and Measurements
09:36

Continuous-Wave Propagation Channel-Sounding Measurement System - Testing, Verification, and Measurements

Published on: June 25, 2021

3.6K
Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit
05:30

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit

Published on: September 8, 2023

1.2K

Area of Science:

  • Computer Science
  • Network Security
  • Wireless Communication

Background:

  • Wireless ad hoc networks are vulnerable to jamming attacks that disrupt communication.
  • Existing routing protocols like AODV and DSR lack robust defenses against such attacks.
  • Effective mitigation strategies are crucial for maintaining network reliability and performance.

Purpose of the Study:

  • To design and evaluate a jamming attack mitigation scheme integrated with MPH, AODV, and DSR routing protocols.
  • To assess the impact of jamming attacks on network performance metrics.
  • To compare the effectiveness of the modified protocols (MPH-M, AODV-M, DSR-M) against jamming.

Main Methods:

  • Developed modified routing protocols: MPH-M, AODV-M, and DSR-M, incorporating a local detection and node isolation mechanism.
  • Utilized metrics such as packet retransmissions, CSMA/CA retries, and energy consumption for attack detection.
  • Evaluated protocol performance based on throughput, system resilience, and energy usage under varying attacker positions.

Main Results:

  • MPH-M significantly outperforms AODV-M and DSR-M in terms of node energy efficiency (138.13% better than AODV-M, 126.07% better than DSR-M).
  • The mitigation scheme provides greater benefits to MPH-M, reducing energy consumption by 34.61%, compared to minimal improvements in AODV-M (3.92%) and DSR-M (3.42%).
  • MPH-M shows superior throughput efficiency (7.7% higher than AODV-M/DSR-M with mitigation) and resilience (15% lower retransmission rate), with faster recovery times.

Conclusions:

  • The proposed mitigation scheme effectively enhances the resilience of wireless routing protocols against jamming attacks.
  • MPH-M demonstrates superior performance and energy efficiency compared to modified AODV-M and DSR-M protocols.
  • The integration of jamming mitigation into MPH routing protocols is a promising approach for secure and reliable wireless networks.