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

Network Function of a Circuit01:25

Network Function of a Circuit

440
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.
440
Ampere-Maxwell's Law: Problem-Solving01:17

Ampere-Maxwell's Law: Problem-Solving

828
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...
828
Fast Decoupled and DC Powerflow01:24

Fast Decoupled and DC Powerflow

361
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:
361
Distributed Loads: Problem Solving01:21

Distributed Loads: Problem Solving

828
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...
828
Block Diagram Reduction01:22

Block Diagram Reduction

335
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...
335
Parallel Processing01:20

Parallel Processing

373
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...
373

You might also read

Related Articles

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

Sort by
Same author

NONAN GaitPrint: An IMU gait database of healthy older adults.

Scientific data·2025
Same author

NONAN GaitPrint: An IMU gait database of healthy young adults.

Scientific data·2023
Same author

An Optimized IoT-enabled Big Data Analytics Architecture for Edge-Cloud Computing.

IEEE internet of things journal·2023
Same author

Trustworthy and Reliable Deep Learning-based Cyberattack Detection in Industrial IoT.

IEEE transactions on industrial informatics·2023
Same author

Hash-MAC-DSDV: Mutual Authentication for Intelligent IoT-Based Cyber-Physical Systems.

IEEE internet of things journal·2023
Same authorSame journal

LightIoT: Lightweight and secure communication for energy-efficient IoT in health informatics.

IEEE transactions on green communications and networking·2022

Related Experiment Video

Updated: Oct 22, 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

849

CoxNet: A Computation Reuse Architecture at the Edge.

Zouhir Bellal1, Boubakr Nour2, Spyridon Mastorakis3

  • 1Ecole Superieure en Informatique, Sidi Bel Abbes, Algeria.

IEEE Transactions on Green Communications and Networking
|August 30, 2021
PubMed
Summary
This summary is machine-generated.

Edge computing faces challenges with intensive mobile applications. CoxNet architecture enables edge servers to reuse computations, significantly reducing task execution time for improved performance.

Keywords:
Computation ReuseEdge ComputingServerless ComputingService Offloading

More Related Videos

Closed-loop Neuro-robotic Experiments to Test Computational Properties of Neuronal Networks
11:18

Closed-loop Neuro-robotic Experiments to Test Computational Properties of Neuronal Networks

Published on: March 2, 2015

10.5K
Integration of 5G Experimentation Infrastructures into a Multi-Site NFV Ecosystem
10:15

Integration of 5G Experimentation Infrastructures into a Multi-Site NFV Ecosystem

Published on: February 3, 2021

3.9K

Related Experiment Videos

Last Updated: Oct 22, 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

849
Closed-loop Neuro-robotic Experiments to Test Computational Properties of Neuronal Networks
11:18

Closed-loop Neuro-robotic Experiments to Test Computational Properties of Neuronal Networks

Published on: March 2, 2015

10.5K
Integration of 5G Experimentation Infrastructures into a Multi-Site NFV Ecosystem
10:15

Integration of 5G Experimentation Infrastructures into a Multi-Site NFV Ecosystem

Published on: February 3, 2021

3.9K

Area of Science:

  • Computer Science
  • Distributed Systems
  • Edge Computing

Background:

  • Edge computing extends cloud capabilities for low-latency applications.
  • Intensive mobile applications create high demand and pressure on edge servers.
  • Interconnected computations in modern applications require efficient processing.

Purpose of the Study:

  • To introduce CoxNet, an efficient computation reuse architecture for edge computing.
  • To address the challenges of computation-intensive and delay-sensitive services on edge servers.
  • To enable edge servers to reuse previous computations for dependent tasks.

Main Methods:

  • Developed an analytical model for computation reuse with dependent task offloading.
  • Designed a novel computing offloading scheduling scheme within the CoxNet architecture.
  • Evaluated CoxNet's performance using both synthetic and real-world datasets.

Main Results:

  • CoxNet demonstrated significant reduction in task execution time.
  • Up to 66% reduction in task execution time observed with synthetic datasets.
  • Up to 50% reduction in task execution time observed with real-world datasets.

Conclusions:

  • CoxNet effectively reduces task execution time in edge computing environments.
  • The architecture enhances efficiency by enabling computation reuse for dependent tasks.
  • CoxNet offers a viable solution for managing computation-intensive services on edge servers.