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

Distributed Loads01:19

Distributed Loads

915
Distributed loads are a common type of load that engineers and scientists encounter in various practical situations. Distributed loads often refer to a type of load spread over a surface or a structure and can be modeled as continuous force per unit area.
For example, consider a bookshelf filled with books stacked vertically adjacent to each other. The weight of the books is evenly distributed over the length of the shelf. As a result, the pressure at different locations on the surface of the...
915
Distributed Loads: Problem Solving01:21

Distributed Loads: Problem Solving

1.1K
Beams are structural elements commonly employed in engineering applications requiring different load-carrying capacities. The first step in analyzing a beam under a distributed load is to simplify the problem by dividing the load into smaller regions, which allows one to consider each region separately and calculate the magnitude of the equivalent resultant load acting on each portion of the beam. The magnitude of the equivalent resultant load for each region can be determined by calculating...
1.1K
Fast Decoupled and DC Powerflow01:24

Fast Decoupled and DC Powerflow

705
The fast decoupled power flow method addresses contingencies in power system operations, such as generator outages or transmission line failures. This method provides quick power flow solutions, essential for real-time system adjustments. Fast decoupled power flow algorithms simplify the Jacobian matrix by neglecting certain elements, leading to two sets of decoupled equations:
705
PI Controller: Design01:24

PI Controller: Design

1.1K
Proportional Integral (PI) controllers are a fundamental component in modern control systems, widely used to enhance performance and mitigate steady-state errors. They are particularly effective in applications such as automatic brightness adjustment on smartphones, where they excel at mitigating steady-state errors for step-function inputs. Unlike PD controllers, which require time-varying errors to function optimally, PI controllers leverage their integral component to address residual...
1.1K
PD Controller: Design01:26

PD Controller: Design

582
In automotive engineering, car suspension systems often employ Proportional Derivative (PD) controllers to enhance performance. PD controllers are utilized to adjust the damping force in response to road conditions. A controller, acting as an amplifier with a constant gain, demonstrates proportional control, with output directly mirroring input.
Designing a continuous-data controller requires selecting and linking components like adders and integrators, which are fundamental in Proportional,...
582
Controller Configurations01:22

Controller Configurations

330
Controller configurations are crucial in a car's cruise control system because they manage speed over time to maintain a consistent pace regardless of road conditions, thereby meeting design goals. In traditional control systems, fixed-configuration design involves predetermined controller placement. System performance modifications are known as compensation.
Control-system compensation involves various configurations, most commonly series or cascade compensation, in which the controller...
330

You might also read

Related Articles

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

Sort by
Same author

Coral-CRCA: A Color-Reference Chart Automation algorithm for coral bleaching visualization and severity assessment.

Marine pollution bulletin·2026
Same author

RAUM-GANs: a multi-layer GAN-enhanced framework for accurate multiple sclerosis lesion segmentation in MRI.

Scientific reports·2025
Same author

SFARP: a multi-layered real-time security framework for hybrid ARP and DDoS attack defense in SD-IoT networks.

Scientific reports·2025
Same author

Underwater SLAM Meets Deep Learning: Challenges, Multi-Sensor Integration, and Future Directions.

Sensors (Basel, Switzerland)·2025
Same author

A new medical image encryption using modular integrated logistic exponential map and multi-level Q-Sequence matrix.

Scientific reports·2025
Same author

Poisonous Plant Prediction Using Explainable Deep Inherent Learning Model.

Sensors (Basel, Switzerland)·2025
Same journal

Therapeutic potential of crude protein extracts from two Egyptian freshwater snails Lanistes carinatus and Bellamya unicolor.

Scientific reports·2026
Same journal

Microbial contamination of donor corneas and post-keratoplasty endophthalmitis: a comparison between Japanese and U.S. eye banks using cold storage.

Scientific reports·2026
Same journal

Prevalence and contributing factors of virological non-suppression among adult patients on first-line antiretroviral therapy in tertiary hospitals in Ethiopia.

Scientific reports·2026
Same journal

An in vitro comparison of color stability between alkasite and different restorative materials in various staining solutions.

Scientific reports·2026
Same journal

Toward accessible mRNA LNP formulation: systematic evaluation of mixing strategies and key parameters.

Scientific reports·2026
Same journal

A network analysis of personality traits, mentalizing, and psychological health in Chinese college students.

Scientific reports·2026
See all related articles

Related Experiment Video

Updated: Jan 7, 2026

Experimental Investigation of the Hierarchical Control in DC Microgrids Using a Real-time Simulator
06:04

Experimental Investigation of the Hierarchical Control in DC Microgrids Using a Real-time Simulator

Published on: February 14, 2025

974

MC-LBTO: secure and resilient state-aware multi-controller framework with adaptive load balancing for SD-IoT

Ashraf Alyanbaawi1, Ameer El-Sayed2, Nihal Salah3

  • 1College of Computer Science and Engineering, Taibah University, Yanbu, 966144, Saudi Arabia.

Scientific Reports
|December 26, 2025
PubMed
Summary
This summary is machine-generated.

MC-LBTO offers a modular multi-controller framework for Software-Defined IoT (SD-IoT) networks, enhancing scalability and efficiency through intelligent traffic management and adaptive control. This system optimizes load balancing and network resilience for demanding IoT environments.

Keywords:
Adaptive load balancingIoTMulti-controller resilienceSDNState-aware monitoringTrusted failover

More Related Videos

The Modular Design and Production of an Intelligent Robot Based on a Closed-Loop Control Strategy
11:53

The Modular Design and Production of an Intelligent Robot Based on a Closed-Loop Control Strategy

Published on: October 14, 2017

12.1K

Related Experiment Videos

Last Updated: Jan 7, 2026

Experimental Investigation of the Hierarchical Control in DC Microgrids Using a Real-time Simulator
06:04

Experimental Investigation of the Hierarchical Control in DC Microgrids Using a Real-time Simulator

Published on: February 14, 2025

974
The Modular Design and Production of an Intelligent Robot Based on a Closed-Loop Control Strategy
11:53

The Modular Design and Production of an Intelligent Robot Based on a Closed-Loop Control Strategy

Published on: October 14, 2017

12.1K

Area of Science:

  • Computer Science
  • Network Engineering
  • Internet of Things (IoT)

Background:

  • Conventional Software-Defined Networking (SDN) struggles with the dynamic and data-intensive demands of large, heterogeneous Internet of Things (IoT) systems.
  • Centralized control and static forwarding in traditional SDN architectures limit scalability and real-time adaptability for IoT networks.

Purpose of the Study:

  • To propose MC-LBTO, a modular multi-controller framework designed to enhance scalability, efficiency, and resilience in Software-Defined IoT (SD-IoT) networks.
  • To integrate programmable data plane intelligence with secure, adaptive coordination among distributed controllers for optimized load balancing and network performance.

Main Methods:

  • Developed MC-LBTO, a framework comprising three cooperative modules: PDSM (P4-enabled Dynamic State Monitoring), PALB (P4-based Adaptive Load Balancer), and STAM (Secure Trusted Adaptive Multi-Control).
  • Utilized P4 programming for in-switch traffic monitoring, adaptive load balancing, and secure inter-controller communication.
  • Conducted experimental evaluations to assess the performance of individual modules and the integrated framework.

Main Results:

  • PDSM module reduced controller CPU utilization by 35.7% and improved flow-state detection accuracy to 98.3%.
  • PALB module achieved a 36% reduction in request latency and a 25% throughput increase with low load distribution variance (5.5%).
  • STAM module enhanced control-plane robustness, reducing Mean Time to Recovery (MTTR) to 75 ms and packet loss by 70%.

Conclusions:

  • MC-LBTO provides a scalable, secure, and self-adaptive SD-IoT architecture.
  • The framework maintains low overhead, balanced resource utilization, and fast recovery, ensuring dependable and high-performance IoT networking.
  • MC-LBTO offers a technically grounded solution for the challenges posed by the rapid expansion of IoT.