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Related Concept Videos

Distributed Loads: Problem Solving01:21

Distributed Loads: Problem Solving

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...
Distributed Loads01:19

Distributed Loads

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...
Ampere-Maxwell's Law: Problem-Solving01:17

Ampere-Maxwell's Law: Problem-Solving

A parallel-plate capacitor with capacitance C, whose plates have area A and separation distance d, is connected to a resistor R and a battery of voltage V. The current starts to flow at t = 0. What is the displacement current between the capacitor plates at time t? From the properties of the capacitor, what is the corresponding real current?
To solve the problem, we can use the equations from the analysis of an RC circuit and Maxwell's version of Ampère's law.
For the first part of the problem,...
Statically Indeterminate Problem Solving01:16

Statically Indeterminate Problem Solving

Statically indeterminate problems are those where statics alone can not determine the internal forces or reactions. Consider a structure comprising two cylindrical rods made of steel and brass. These rods are joined at point B and restrained by rigid supports at points A and C. Now, the reactions at points A and C and the deflection at point B are to be determined. This rod structure is classified as statically indeterminate as the structure has more supports than are necessary for maintaining...
Fast Decoupled and DC Powerflow01:24

Fast Decoupled and DC Powerflow

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:
Parallel Processing01:20

Parallel Processing

The brain processes sensory information rapidly due to parallel processing, which involves sending data across multiple neural pathways at the same time. This method allows the brain to manage various sensory qualities, such as shapes, colors, movements, and locations, all concurrently. For instance, when observing a forest landscape, the brain simultaneously processes the movement of leaves, the shapes of trees, the depth between them, and the various shades of green. This enables a quick and...

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Related Experiment Videos

Secure task offloading framework for industrial edge computing using reconfigurable intelligent surfaces and spectrum

Asma A Alhashmi1, Wajdan Al Malwi2, Monir Abdullah3

  • 1Department of Computer Science, College of Science, Northern Border University, Arar, 73213, Saudi Arabia.

Scientific Reports
|June 19, 2026
PubMed
Summary
This summary is machine-generated.

This study introduces a secure Industrial Internet of Things (IIoT) offloading framework using reconfigurable intelligent surfaces (RIS), frequency hopping spread spectrum (FHSS), and nonorthogonal multiple access (NOMA). The novel approach enhances security, reduces latency, and boosts energy efficiency in challenging industrial settings.

Keywords:
Industrial IoTIoT safety monitoringMobile edge computingPhysical layer securityReconfigurable intelligent surfacesSaudi vision 2030Smart mining

Related Experiment Videos

Area of Science:

  • Engineering
  • Computer Science
  • Cybersecurity

Background:

  • Industrial Internet of Things (IIoT) deployments face challenges with secure, low-latency task offloading in environments with signal blockage.
  • Existing schemes struggle to balance scalability, resilience to eavesdropping, and low latency under harsh industrial conditions.

Purpose of the Study:

  • To propose a unified secure offloading framework integrating RIS, FHSS, and NOMA for scalable, low-latency, and eavesdropping-resilient IIoT task offloading.
  • To maximize the minimum secrecy rate while adhering to strict latency and minimum rate constraints in a multiple MEC architecture.

Main Methods:

  • Formulated a mixed-integer nonconvex max-min problem optimizing device-server association, computation, power, FHSS carrier selection, and RIS phase shifts.
  • Developed a block coordinate descent algorithm with successive convex approximation to solve the optimization problem.
  • Integrated spatial control (RIS), spectral agility (FHSS), and massive access (NOMA) for enhanced IIoT offloading.

Main Results:

  • Improved minimum secrecy rate by 18.75% compared to benchmarks.
  • Reduced average latency by 41%.
  • Enhanced energy efficiency by up to 30%.

Conclusions:

  • The proposed framework effectively leverages RIS, FHSS, and NOMA for secure and reliable IIoT offloading in obstructed industrial environments.
  • This research supports the digital transformation of sectors like mining through secure IoT monitoring and automated systems, aligning with national visions.