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Distributed Loads: Problem Solving01:21

Distributed Loads: Problem Solving

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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...
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Parallel Processing01:20

Parallel Processing

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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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Maxwell-Boltzmann Distribution: Problem Solving01:20

Maxwell-Boltzmann Distribution: Problem Solving

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Individual molecules in a gas move in random directions, but a gas containing numerous molecules has a predictable distribution of molecular speeds, which is known as the Maxwell-Boltzmann distribution, f(v).
This distribution function f(v) is defined by saying that the expected number N (v1,v2) of particles with speeds between v1 and v2 is given by
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Laminar Flow: Problem Solving01:24

Laminar Flow: Problem Solving

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Laminar flow occurs when a fluid moves smoothly in parallel layers with minimal mixing and turbulence. In fluid mechanics, ensuring laminar flow within a pipe is essential for precise control of flow characteristics, especially in engineering applications. The key factor in determining whether flow remains laminar is the Reynolds number, a dimensionless quantity that depends on the fluid's velocity, density, viscosity, and the pipe's diameter. A Reynolds number of 2100 or lower...
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Ampere-Maxwell's Law: Problem-Solving01:17

Ampere-Maxwell's Law: Problem-Solving

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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...
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Distributed Loads01:19

Distributed Loads

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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...
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Related Experiment Video

Updated: Mar 15, 2026

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit
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LITO: Lemur-Inspired Task Offloading for Edge-Fog-Cloud Continuum Systems.

Asma Almulifi1, Heba Kurdi1

  • 1Computer Science Department, College of Computer and Information Sciences, King Saud University, Riyadh 11451, Saudi Arabia.

Sensors (Basel, Switzerland)
|March 14, 2026
PubMed
Summary
This summary is machine-generated.

This study introduces LITO, a novel lemur-inspired task offloading algorithm for edge, fog, and cloud systems. LITO enhances energy efficiency and resource utilization by mimicking lemur social behaviors for task assignment and scheduling.

Keywords:
Internet of Thingsedge computingedge–fog–cloud continuumfog computingresource managementsupervised policy learningtask offloading

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Area of Science:

  • Computer Science
  • Distributed Systems
  • Artificial Intelligence

Background:

  • Edge, fog, and cloud continuum architectures face challenges with heterogeneous, latency-sensitive workloads, energy consumption, and resource utilization.
  • Classical task offloading methods lack adaptability or incur high computational overhead and centralized coordination.

Purpose of the Study:

  • To propose LITO, a lemur-inspired task offloading algorithm for edge, fog, and cloud continuum systems.
  • To address challenges in energy consumption, resource utilization, and latency for dynamic workloads.

Main Methods:

  • LITO models the infrastructure as a social system with nodes assuming distinct roles.
  • It incorporates lemur-inspired mechanisms: energy-aware task assignment (sun basking) and cooperative scheduling (huddling).
  • A continual supervised policy-learning layer with contextual bandit feedback refines offloading decisions.

Main Results:

  • LITO jointly minimizes energy consumption and deadline violations while maximizing resource utilization and throughput.
  • Simulations show LITO outperforms existing multi-objective offloading baselines.
  • The algorithm excels in energy consumption, resource utilization, latency, SLA violations, and throughput under congested scenarios.

Conclusions:

  • LITO offers an effective, bio-inspired approach to task offloading in complex continuum environments.
  • The lemur-inspired mechanisms provide adaptability and efficiency in dynamic, high-load conditions.
  • LITO demonstrates significant improvements over traditional offloading strategies.