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

Short-distance Transport of Resources02:12

Short-distance Transport of Resources

16.3K
Short-distance transport refers to transport that occurs over a distance of just 2-3 cells, crossing the plasma membrane in the process. Small uncharged molecules, such as oxygen, carbon dioxide, and water, can diffuse across the plasma membrane on their own. In contrast, ions and larger molecules require the assistance of transport proteins due to their charge or size. Transport across membranes also occurs within individual cells, playing a variety of essential roles for the plant as a whole.
16.3K
Modeling and Similitude01:12

Modeling and Similitude

323
Scaled modeling is a fundamental technique in engineering, enabling the study of large and complex systems by creating smaller, manageable replicas that recreate critical characteristics of the original. In hydrology and civil infrastructure, for example, scaled models of dams help analyze water flow, turbulence, and pressure. This method allows for accurate predictions of real-world behavior within a controlled environment, significantly reducing the cost and time involved in full-scale...
323
Ampere-Maxwell's Law: Problem-Solving01:17

Ampere-Maxwell's Law: Problem-Solving

722
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...
722
Xylem and Transpiration-driven Transport of Resources02:03

Xylem and Transpiration-driven Transport of Resources

24.3K
The xylem of vascular plants distributes water and dissolved minerals that are taken up by the roots to the rest of the plant. The cells that transport xylem sap are dead upon maturity, and the movement of xylem sap is a passive process.
24.3K
Distributed Loads: Problem Solving01:21

Distributed Loads: Problem Solving

696
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...
696
Energy Budgets00:51

Energy Budgets

9.6K
Organisms must balance energy intake with the energy required for growth, maintenance and reproduction. These trade-offs result in a variety of survivorship and reproductive strategies, including semelparity and iteroparity. Semelparous species, like annual plants, have only one reproductive episode in their lifetimes and consequently have short lifespans. Iteroparous species, by contrast, have many reproductive events during their lifetimes but have relatively few offspring. These two...
9.6K

You might also read

Related Articles

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

Sort by
Same author

The future of fundamental science led by generative closed-loop artificial intelligence.

Frontiers in artificial intelligence·2026
Same author

Artificial intelligence in sport: A narrative review of applications, challenges and future trends.

Journal of sports sciences·2025
Same author

Trustworthy human-AI partnerships.

iScience·2021
Same author

OptiSpot: minimizing application deployment cost using spot cloud resources.

Cluster computing·2020
Same author

The Shapley value for a fair division of group discounts for coordinating cooling loads.

PloS one·2020
Same author

Machine behaviour.

Nature·2019

Related Experiment Video

Updated: Aug 22, 2025

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

SimTune: bridging the simulator reality gap for resource management in edge-cloud computing.

Shreshth Tuli1, Giuliano Casale2, Nicholas R Jennings3

  • 1Imperial College London, London, UK. s.tuli20@imperial.ac.uk.

Scientific Reports
|November 10, 2022
PubMed
Summary
This summary is machine-generated.

SimTune enhances edge-cloud resource management by improving simulator accuracy, reducing data saturation and the reality-gap problem for deep neural networks. This leads to better quality of service in Internet of Things environments.

More Related Videos

Knowledge Based Cloud FE Simulation of Sheet Metal Forming Processes
11:05

Knowledge Based Cloud FE Simulation of Sheet Metal Forming Processes

Published on: December 13, 2016

12.3K
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

3.8K

Related Experiment Videos

Last Updated: Aug 22, 2025

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
Knowledge Based Cloud FE Simulation of Sheet Metal Forming Processes
11:05

Knowledge Based Cloud FE Simulation of Sheet Metal Forming Processes

Published on: December 13, 2016

12.3K
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

3.8K

Area of Science:

  • Computer Science
  • Artificial Intelligence
  • Distributed Systems

Background:

  • The Internet of Things (IoT) drives massive multi-modal data generation, necessitating low-latency processing via edge and cloud computing.
  • Efficient resource management in hybrid edge-cloud platforms is challenged by large-scale computation and the limitations of data-driven models like deep neural networks (DNNs).
  • DNNs suffer from data saturation with volatile data, while coupled simulators face a reality-gap problem due to abstraction inaccuracies.

Purpose of the Study:

  • To address data saturation and the reality-gap problem in edge-cloud resource management for Internet of Things (IoT) environments.
  • To introduce SimTune, a framework that enhances the accuracy of high-fidelity simulators using low-fidelity surrogate models.
  • To enable data-driven resource management methods to generalize to unknown edge-cloud configurations.

Main Methods:

  • Developed the SimTune framework, employing a low-fidelity surrogate model to iteratively update parameters of a high-fidelity simulator.
  • Utilized SimTune to improve the accuracy of simulators used for generating out-of-distribution training data.
  • Evaluated SimTune against state-of-the-art solutions on a real edge-cloud platform.

Main Results:

  • SimTune effectively reduces the reality-gap problem by increasing simulation accuracy.
  • Co-simulated methods utilizing SimTune demonstrated improved generalization to diverse edge-cloud configurations.
  • Quality of service metrics, including energy consumption and response time, improved by up to 14.7% and 7.6% respectively.

Conclusions:

  • Simulator tuning, as implemented by SimTune, is a viable approach to enhance the performance of data-driven resource management in hybrid edge-cloud systems.
  • SimTune offers a practical solution for overcoming limitations of traditional simulators and data-driven models in dynamic IoT environments.
  • The framework facilitates more efficient and accurate resource allocation, leading to significant improvements in key performance indicators.