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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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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?
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Cruise control systems in cars are designed as multi-input systems to maintain a driver's desired speed while compensating for external disturbances such as changes in terrain. The block diagram for a cruise control system typically includes two main inputs: the desired speed set by the driver and any external disturbances, such as the incline of the road. By adjusting the engine throttle, the system maintains the vehicle's speed as close to the desired value as possible.
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Related Experiment Video

Updated: Jun 3, 2025

Automated Deployment of an Internet Protocol Telephony Service on Unmanned Aerial Vehicles Using Network Functions Virtualization
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Multi-Objective Optimization for Resource Allocation in Space-Air-Ground Network with Diverse IoT Devices.

Yongnan Xu1, Xiangrong Tang1, Linyu Huang1

  • 1College of Electronics and Information Engineering, Sichuan University, Chengdu 610065, China.

Sensors (Basel, Switzerland)
|January 11, 2025
PubMed
Summary
This summary is machine-generated.

This study addresses remote Internet of Things (IoT) signal transmission using Space-Air-Ground Integrated Networks (SAGIN). A novel algorithm optimizes Unmanned Aerial Vehicle (UAV) deployment and resource allocation for fair, high-capacity data relay to satellites.

Keywords:
UAVinternet of thingsmulti-objective optimization evolutionary algorithmspace–air–ground integrated networksystem capacity

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Area of Science:

  • Communications Engineering
  • Network Optimization
  • Wireless Sensor Networks

Background:

  • The expansion of the Internet of Things (IoT) necessitates robust communication solutions for remote areas lacking traditional infrastructure.
  • Space-Air-Ground Integrated Networks (SAGIN) offer a promising framework by combining aerial, terrestrial, and space components.
  • Unmanned Aerial Vehicles (UAVs) are increasingly utilized as mobile relays in SAGIN for efficient data collection from IoT devices.

Purpose of the Study:

  • To maximize the minimum uplink channel capacity for diverse IoT device categories within a SAGIN framework.
  • To address the multi-objective optimization challenge of fair resource allocation among IoT devices.
  • To develop an effective algorithm for optimizing UAV deployment, bandwidth allocation, and device-UAV association.

Main Methods:

  • Formulation of a multi-objective optimization problem to maximize minimum uplink channel capacity across IoT categories.
  • Proposal of a novel multi-objective evolutionary algorithm designed for equitable resource distribution.
  • Validation through comparative analysis against traditional multi-objective optimization algorithms across eight distinct scenarios.

Main Results:

  • The proposed algorithm achieves superior Pareto fronts (PFs) compared to existing methods, indicating enhanced solution quality.
  • Demonstrated improved convergence rates, signifying greater algorithmic efficiency in resource allocation.
  • Experimental results confirm the algorithm's effectiveness in ensuring equitable resource distribution among competing IoT devices.

Conclusions:

  • The developed multi-objective evolutionary algorithm effectively optimizes resource allocation in SAGIN for enhanced IoT connectivity.
  • The algorithm's ability to generate high-quality Pareto fronts provides adaptable solutions for dynamic signal collection requirements.
  • This research contributes to overcoming signal transmission challenges in remote regions, facilitating broader IoT deployment.