Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Buffer Effectiveness

Buffer Effectiveness

Buffer solutions do not have an unlimited capacity to keep the pH relatively constant . Instead, the ability of a buffer solution to resist changes in pH relies on the presence of appreciable amounts of its conjugate weak acid-base pair. When enough strong acid or base is added to substantially lower the concentration of either member of the buffer pair, the buffering action within the solution is compromised.
The buffer capacity is the amount of acid or base that can be added to a given volume...

Propagation of Uncertainty from Random Error

Propagation of Uncertainty from Random Error

An experiment often consists of more than a single step. In this case, measurements at each step give rise to uncertainty. Because the measurements occur in successive steps, the uncertainty in one step necessarily contributes to that in the subsequent step. As we perform statistical analysis on these types of experiments, we must learn to account for the propagation of uncertainty from one step to the next. The propagation of uncertainty depends on the type of arithmetic operation performed on...

Uniform Depth Channel Flow: Problem Solving

Uniform Depth Channel Flow: Problem Solving

To calculate the flow rate for a trapezoidal channel, first, identify the bottom width, side slope, and flow depth of the channel. The cross-sectional area (A) corresponding to the depth of flow (y), channel bottom width (B), and side slope (θ) is determined by:Next, calculate the wetted perimeter, which includes the bottom width and the sloped side lengths in contact with the water. Using the values of the cross-sectional area and the wetted perimeter, determine the hydraulic radius by...

Censoring Survival Data

Censoring Survival Data

Survival analysis is a statistical method used to analyze time-to-event data, often employed in fields such as medicine, engineering, and social sciences. One of the key challenges in survival analysis is dealing with incomplete data, a phenomenon known as "censoring." Censoring occurs when the event of interest (such as death, relapse, or system failure) has not occurred for some individuals by the end of the study period or is otherwise unobservable, and it might have many different...

Buffers: Buffer Capacity

Buffers: Buffer Capacity

Buffer capacity is the quantitative measure of a buffer to resist the change in pH. As shown in the following equation, the buffer capacity, denoted by 'beta', is expressed as the number of moles of acid or base needed to change the pH of a one-liter buffer solution by 1 unit. Here, Ca and Cb indicate the number of moles of acid and base, respectively. Note that dpH represents the change in pH.
In the graph, pH is plotted as a function of the number of moles of base (Cb) added to a weak...

Uniform Depth Channel Flow

Uniform Depth Channel Flow

Uniform depth channel flow keeps fluid depth consistent along channels such as irrigation canals. In natural channels, such as rivers, approximate uniform flow is often assumed. This condition occurs when the channel’s bottom slope matches the energy slope, balancing potential energy lost from gravity with head loss due to shear stress. This balance prevents depth changes along the channel length, resulting in a steady, uniform flow.Uniform flow in open channels with a constant cross-section...

You might also read

Related Articles

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

Sort by

Same author

DOC-IDS: A Deep Learning-Based Method for Feature Extraction and Anomaly Detection in Network Traffic.

Sensors (Basel, Switzerland)·2022

Same author

Extracting the Secrets of OpenSSL with RAMBleed.

Sensors (Basel, Switzerland)·2022

See all related articles

Search research articles

Related Experiment Video

Updated: Mar 15, 2026

Microfluidic Platform with Multiplexed Electronic Detection for Spatial Tracking of Particles

Microfluidic Platform with Multiplexed Electronic Detection for Spatial Tracking of Particles

Published on: March 13, 2017

Buffering and Adaptive Coding for Flooding with Randomized Network Coding on Multi-Hop Wireless Broadcasting.

Youji Fukuta¹, Yoshiaki Shiraishi², Masanori Hirotomo³

¹Faculty of Informatics, Cyber Informatics Research Institute, Kindai University, Higashiosaka-shi 577-8502, Japan.

Sensors (Basel, Switzerland)

|March 14, 2026

Summary

This study introduces new buffer management and adaptive coding for broadcast flooding in wireless networks. These methods significantly improve data reception rates by reducing redundant packets and enhancing resilience.

Keywords:

adaptive coding broadcast flooding buffer management randomized network coding wireless ad hoc networks

More Related Videos

Transmission of Multiple Signals through an Optical Fiber Using Wavefront Shaping

Transmission of Multiple Signals through an Optical Fiber Using Wavefront Shaping

Published on: March 20, 2017

Related Experiment Videos

Last Updated: Mar 15, 2026

Microfluidic Platform with Multiplexed Electronic Detection for Spatial Tracking of Particles

Microfluidic Platform with Multiplexed Electronic Detection for Spatial Tracking of Particles

Published on: March 13, 2017

Transmission of Multiple Signals through an Optical Fiber Using Wavefront Shaping

Transmission of Multiple Signals through an Optical Fiber Using Wavefront Shaping

Published on: March 20, 2017

Area of Science:

Computer Science
Electrical Engineering
Network Engineering

Background:

Broadcast flooding in wireless ad hoc networks suffers from the broadcast storm problem, leading to excessive transmissions, collisions, and link losses.
Randomized network coding (RNC) improves resilience to packet losses, but efficient buffer management and adaptive transmission are critical for optimal performance.

Purpose of the Study:

To propose novel buffering mechanisms and adaptive coding strategies to enhance data unit reception rates in RNC-based broadcast flooding.
To address the limitations of existing First-In-First-Out (FIFO) buffer policies that can prematurely discard essential data.

Main Methods:

A hybrid buffering mechanism combining Last-In-First-Out (LIFO) and Least Recently Used (LRU) discard policies is proposed.
An adaptive coding strategy dynamically adjusts transmitted coded packets based on data unit duplication rates without inter-node coordination.
Simulations were conducted using the OMNeT++ and INET framework, specifically for Vehicular Ad Hoc Networks (VANETs).

Main Results:

The LIFO+LRU buffering mechanism significantly increased received data units and prevented redundant receptions compared to traditional methods.
Adaptive coding further improved reception rates, especially under challenging network conditions with high packet loss or duplication.
The proposed methods demonstrated enhanced performance in VANET simulations, mitigating broadcast storm issues.

Conclusions:

The novel LIFO+LRU buffering and adaptive coding strategies effectively improve data reception in RNC-based broadcast flooding.
These techniques offer a robust solution for enhancing communication reliability in wireless ad hoc networks, particularly in dynamic environments like VANETs.
The findings suggest a practical approach to overcoming broadcast storm challenges and improving network efficiency.