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 Flow and Line Loadability01:23

Maximum Power Flow and Line Loadability

135
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.
135
Network Function of a Circuit01:25

Network Function of a Circuit

317
Frequency response analysis in electrical circuits provides vital insights into a circuit's behavior as the frequency of the input signal changes. The transfer function, a mathematical tool, is instrumental in understanding this behavior. It defines the relationship between phasor output and input and comes in four types: voltage gain, current gain, transfer impedance, and transfer admittance. The critical components of the transfer function are the poles and zeros.
317
Distributed Loads: Problem Solving01:21

Distributed Loads: Problem Solving

668
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...
668
Mesh Analysis for AC Circuits01:12

Mesh Analysis for AC Circuits

396
In the domain of radio communication, the significance of impedance matching must be considered. It is crucial to ensure the efficient transmission of signals between radio transmitters and receivers. Achieving this balance involves using impedance-matching circuits, with one fundamental configuration comprising a resistor, capacitor, and inductor.
The process of harmonizing these impedances begins with a clear understanding of the input and output signals. Once these signals are known, the...
396
Block Diagram Reduction01:22

Block Diagram Reduction

241
The process of deriving the transfer function of a control system often involves reducing its block diagram to a single block. This simplification can be achieved through a series of strategic operations, including relocating branch points and comparators. These operations preserve the overall function of the system while allowing for easier manipulation and combination of blocks.
The first step in this process is the identification and relocation of a branch point. A branch point, where a...
241
The Power Flow Problem and Solution01:26

The Power Flow Problem and Solution

258
Power flow problem analysis is fundamental for determining real and reactive power flows in network components, such as transmission lines, transformers, and loads. The power system's single-line diagram provides data on the bus, transmission line, and transformer. Each bus k in the system is characterized by four key variables: voltage magnitude Vk​, phase angle δk​, real power Pk​, and reactive power Qk​. Two of these four variables are inputs, while the...
258

You might also read

Related Articles

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

Sort by
Same author

EPRS: Experience-Prioritized Reinforcement Scheduler in Edge Clusters.

Sensors (Basel, Switzerland)·2026
Same author

Graph Neural Networks for Fault Diagnosis in Photovoltaic-Integrated Distribution Networks with Weak Features.

Sensors (Basel, Switzerland)·2025
Same author

Task Offloading with LLM-Enhanced Multi-Agent Reinforcement Learning in UAV-Assisted Edge Computing.

Sensors (Basel, Switzerland)·2025
Same author

Task Assignment and Path Planning Mechanism Based on Grade-Matching Degree and Task Similarity in Participatory Crowdsensing.

Sensors (Basel, Switzerland)·2024
Same author

An Improved SAMP Algorithm for Sparse Channel Estimation in OFDM System.

Sensors (Basel, Switzerland)·2023
Same author

Resource Allocation and Data Offloading Strategy for Edge-Computing-Assisted Intelligent Telemedicine System.

Sensors (Basel, Switzerland)·2023

Related Experiment Video

Updated: Jul 16, 2025

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

598

Arithmetic Optimization AOMDV Routing Protocol for FANETs.

Huamin Wang1, Yongfu Li2, Yubing Zhang3

  • 1School of Microelectronics and Communication Engineering, Chongqing University, Chongqing 401331, China.

Sensors (Basel, Switzerland)
|September 9, 2023
PubMed
Summary
This summary is machine-generated.

A new routing protocol, Arithmetic Optimization-Ad Hoc On-Demand Multipath Distance Vector (AO-AOMDV), improves performance in Flying Ad Hoc Networks (FANETs). This protocol enhances packet delivery, network lifetime, and reduces delay for unmanned aerial vehicles (UAVs).

Keywords:
AO-AOMDVAOMDVFANETsarithmetic optimization

More Related Videos

Design and Optimization Strategies of a High-Performance Vented Box
14:23

Design and Optimization Strategies of a High-Performance Vented Box

Published on: June 9, 2023

1.2K
Automated Deployment of an Internet Protocol Telephony Service on Unmanned Aerial Vehicles Using Network Functions Virtualization
07:49

Automated Deployment of an Internet Protocol Telephony Service on Unmanned Aerial Vehicles Using Network Functions Virtualization

Published on: November 26, 2019

8.1K

Related Experiment Videos

Last Updated: Jul 16, 2025

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

598
Design and Optimization Strategies of a High-Performance Vented Box
14:23

Design and Optimization Strategies of a High-Performance Vented Box

Published on: June 9, 2023

1.2K
Automated Deployment of an Internet Protocol Telephony Service on Unmanned Aerial Vehicles Using Network Functions Virtualization
07:49

Automated Deployment of an Internet Protocol Telephony Service on Unmanned Aerial Vehicles Using Network Functions Virtualization

Published on: November 26, 2019

8.1K

Area of Science:

  • Computer Science
  • Network Engineering
  • Robotics

Background:

  • Flying Ad Hoc Networks (FANETs) using unmanned aerial vehicles (UAVs) offer flexibility and rapid deployment for various applications.
  • FANETs face challenges due to rapid topology changes and limited energy, making existing routing protocols unsuitable.
  • Limited flight endurance (0.5-2 hours) impacts packet delivery, throughput, and delay in UAV networks.

Purpose of the Study:

  • To address the unsuitability of existing routing protocols in dynamic and energy-constrained FANET environments.
  • To propose a novel, energy-efficient routing protocol for FANETs to enhance UAV operational capabilities.
  • To improve key performance metrics such as packet delivery ratio, network lifetime, and end-to-end delay.

Main Methods:

  • Introduction of the Arithmetic Optimization-Ad Hoc On-Demand Multipath Distance Vector (AO-AOMDV) routing protocol.
  • Utilization of a fitness function within AO-AOMDV to assess and select optimal multi-paths.
  • Implementation and simulation of AO-AOMDV using the NS3 network simulator for performance evaluation.

Main Results:

  • AO-AOMDV demonstrated a superior packet delivery ratio compared to AOMDV and AODV.
  • The proposed AO-AOMDV significantly extended the network lifetime in simulated FANET environments.
  • Average end-to-end delay was notably reduced with the AO-AOMDV protocol.

Conclusions:

  • AO-AOMDV offers a high-performance, energy-efficient routing solution for FANETs.
  • The protocol effectively balances network performance and energy constraints in UAV communications.
  • AO-AOMDV presents a promising advancement for the practical deployment of FANETs.