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

Setting Time of Cement01:12

Setting Time of Cement

337
The setting time of cement refers to the process of cement paste transitioning from a plastic state to a solid state. This process is crucial in construction as it dictates the timeframe for concrete placement, compaction, and finishing. The onset of this solidification is termed the initial set, indicating when the paste becomes unworkable. The final set is when the paste has solidified completely, and further handling or manipulation can no longer affect its shape. The cement strength is...
337
Time and frequency -Domain Interpretation of Phase-lag Control01:21

Time and frequency -Domain Interpretation of Phase-lag Control

164
Phase-lag controllers are widely used in control systems to improve stability and reduce steady-state errors. A dimmer switch controlling the brightness of a light bulb serves as a practical example of phase-lag control, gradually adjusting the bulb's brightness. Mathematically, phase-lag control or low-pass filtering is represented when the factor 'a' is less than 1.
Phase-lag controllers do not place a pole at zero, but instead influence the steady-state error by amplifying any...
164
Maximum Power Flow and Line Loadability01:23

Maximum Power Flow and Line Loadability

225
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.
225
Linear time-invariant Systems01:23

Linear time-invariant Systems

533
A system is linear if it displays the characteristics of homogeneity and additivity, together termed the superposition property. This principle is fundamental in all linear systems. Linear time-invariant (LTI) systems include systems with linear elements and constant parameters.
The input-output behavior of an LTI system can be fully defined by its response to an impulsive excitation at its input. Once this impulse response is known, the system's reaction to any other input can be...
533
Reinforcement Schedules01:24

Reinforcement Schedules

274
Positive reinforcement is a powerful method for teaching new behaviors to both animals and humans. B.F. Skinner demonstrated this with his experiments using rats in a Skinner box. When a rat pressed a lever, it received a food pellet. This immediate reward encouraged the rat to repeat the behavior. This method, where a reward follows every instance of the behavior, is known as continuous reinforcement. It is highly effective for establishing new behaviors quickly.
Once a behavior is learned,...
274
Short-distance Transport of Resources02:12

Short-distance Transport of Resources

16.8K
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.
16.8K

You might also read

Related Articles

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

Sort by
Same author

Trace-LogVector-Based Relational Retrieval for Conversational System Log Analysis.

Sensors (Basel, Switzerland)·2026
Same author

Distributed Event-Driven Serverless Platform for Multicluster IoT Environments.

Sensors (Basel, Switzerland)·2026
Same author

An Efficient Distributed Content Store-Based Caching Policy for Information-Centric Networking.

Sensors (Basel, Switzerland)·2022
Same author

An Energy Reward-Based Caching Mechanism for Information-Centric Internet of Things.

Sensors (Basel, Switzerland)·2022
Same journal

RETRACTED: Zhang et al. A Novel Framework for Reconstruction and Imaging of Target Scattering Centers via Wide-Angle Incidence in Radar Networks. <i>Sensors</i> 2025, <i>25</i>, 6802.

Sensors (Basel, Switzerland)·2026
Same journal

Enhancing Unsupervised Multi-Source Domain Adaptation for Person Re-Identification via Mixture of Experts and Graph-Based Relation.

Sensors (Basel, Switzerland)·2026
Same journal

Development of an Instrumented Glove for Palmar Pressure Assessment in Kayakers.

Sensors (Basel, Switzerland)·2026
Same journal

Development and Experimental Validation of an Autonomous IoT-Based Monitoring System for Real-Time Water Quality Assessment in the Amazon River.

Sensors (Basel, Switzerland)·2026
Same journal

Semi-Supervised Adversarial Learning Framework for Controller Area Network Bus Intrusion Detection.

Sensors (Basel, Switzerland)·2026
Same journal

Smart Optimization Method for Safety Signs in Innovative Manufacturing Environments Integrating Industrial Field IoT Sensors and Knowledge Graphs.

Sensors (Basel, Switzerland)·2026
See all related articles

Related Experiment Video

Updated: Oct 20, 2025

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

QoS-Based Service-Time Scheduling in the IoT-Edge Cloud.

Briytone Mutichiro1, Minh-Ngoc Tran1, Young-Han Kim1

  • 1School of Electronic Engineering, Soongsil University, Seoul 06978, Korea.

Sensors (Basel, Switzerland)
|September 10, 2021
PubMed
Summary
This summary is machine-generated.

This study introduces STaSA, a novel scheduling algorithm for edge computing environments. STaSA minimizes Quality of Service (QoS) violations and enhances resource utilization for heterogeneous workloads in edge cloud clusters.

Keywords:
IoT-edge cloudant colony optimization (ACO)quality of service (QoS)resource scheduling

More Related Videos

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

823
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

8.2K

Related Experiment Videos

Last Updated: Oct 20, 2025

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
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

823
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

8.2K

Area of Science:

  • Computer Science
  • Distributed Systems
  • Cloud Computing

Background:

  • Edge computing faces challenges in scheduling diverse workloads due to limited resources and varying application requirements.
  • Overwhelmed servers and network congestion can lead to lengthy task queues and impact Quality of Service (QoS).
  • Internet of Things (IoT) and Edge applications have unique characteristics affecting deadline satisfaction and user QoS.

Purpose of the Study:

  • To propose a mechanism that enhances cluster resource utilization and Quality of Service (QoS) in edge cloud environments.
  • To address the limitations of scheduling heterogeneous workloads with diverse resource requirements in edge computing.
  • To minimize QoS violations by optimizing task scheduling under real-time constraints.

Main Methods:

  • Proposing STaSA (Service Time Aware scheduler), an algorithm for edge environments.
  • Utilizing containerization to manage task dependencies and heterogeneous application resource demands.
  • Implementing the STaSA scheduling model on KubeEdge, a Kubernetes-based container orchestration platform.

Main Results:

  • STaSA automatically assigns requests to processing nodes and schedules execution under real-time constraints.
  • Experimental results demonstrate significantly fewer QoS violations compared to existing methods.
  • The proposed model shows improved performance in edge cloud cluster scheduling.

Conclusions:

  • STaSA effectively improves resource utilization and QoS in edge cloud clusters.
  • The service time-aware scheduling approach minimizes QoS violations for heterogeneous workloads.
  • Containerization and STaSA offer a robust solution for demanding IoT/Edge applications.