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

Vector Algebra: Graphical Method01:10

Vector Algebra: Graphical Method

11.7K
Vectors can be multiplied by scalars, added to other vectors, or subtracted from other vectors. The vector sum of two (or more) vectors is called the resultant vector or, for short, the resultant.
We use the laws of geometry to construct resultant vectors, followed by trigonometry to find vector magnitudes and directions. For a geometric construction of the sum of two vectors in a plane, we follow the parallelogram rule. Suppose two vectors are at arbitrary positions. Translate either one of...
11.7K
Network Function of a Circuit01:25

Network Function of a Circuit

251
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.
251
Signal Flow Graphs01:18

Signal Flow Graphs

154
Signal-flow graphs offer a streamlined and intuitive approach to representing control systems, providing an alternative to traditional block diagrams. These graphs use branches to symbolize systems and nodes to represent signals, effectively illustrating the relationships and interactions within the system.
In a signal-flow graph, branches denote the system's transfer functions, while nodes represent the signals. The direction of signal flow is indicated by arrows, with the corresponding...
154
Levels of Use of a GIS01:29

Levels of Use of a GIS

39
Geographic Information Systems (GIS) operate across three levels of application, each representing an increasing degree of complexity: data management, analysis, and prediction. These levels reflect the expanding functionality and versatility of GIS technology in handling spatial data for diverse purposes.Data ManagementAt its foundational level, GIS serves as a tool for data management, enabling the input, storage, retrieval, and organization of spatial data. This level is often employed in...
39
Block Diagram Reduction01:22

Block Diagram Reduction

149
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...
149
Manipulation and Analysis01:21

Manipulation and Analysis

17
GIS manipulation and analysis functions are vital for decision-making and planning. These activities range from data retrieval tasks, such as selecting information based on specific criteria, to advanced analytical techniques that address complex spatial problems.One critical GIS analysis method is overlaying, which combines multiple data layers to examine impacts. For example, overlaying a river-dammed lake boundary with road networks can identify affected infrastructure. Another common...
17

You might also read

Related Articles

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

Sort by
Same author

A self-supervised learning framework with hierarchical residual cross fusion network for sleep apnea detection.

Artificial intelligence in medicine·2026
Same author

Physical exercise therapy as an anti-aging strategy for osteosarcopenia: a narrative review.

Frontiers in aging·2026
Same author

Structural and dynamic insights into SPDT for phosphorus allocation in rice.

Science China. Life sciences·2026
Same author

Insights into the effects of gut microbiota and circulating metabolites on oral cancer: Mendelian randomization analysis and clinical validation.

Frontiers in nutrition·2026
Same author

Cargo-Adaptor Cooperation Programs Retromer Coat Architecture.

bioRxiv : the preprint server for biology·2026
Same author

Gut microbiota orchestrates bone homeostasis: a multi-pathway network from intestine to skeleton.

Frontiers in endocrinology·2026
Same journal

DARUMA: a gateway to fast and easy prediction of intrinsically disordered regions.

PeerJ. Computer science·2026
Same journal

Alzheimer's disease detection using a quantum deep neural network with Haralick feature extraction and simulated annealing optimization.

PeerJ. Computer science·2026
Same journal

Network anomaly detection using Deep Autoencoder and parallel Artificial Bee Colony algorithm-trained neural network.

PeerJ. Computer science·2026
Same journal

An anomaly detection model for multivariate time series with anomaly perception.

PeerJ. Computer science·2026
Same journal

Retraction: A wormhole attack detection method for tactical wireless sensor networks.

PeerJ. Computer science·2026
Same journal

Evaluation of mental disorder with prioritization of its type by utilizing the bipolar complex fuzzy decision-making approach based on Schweizer-Sklar prioritized aggregation operators.

PeerJ. Computer science·2026
See all related articles

Related Experiment Video

Updated: May 23, 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

8.0K

Construction of a user-friendly software-defined networking management using a graph-based abstraction layer.

Yufeng Jia1,2, Jiadong Ren2, Xianshan Li2

  • 1School of Information Science and Engineering, Xinjiang College of Science and Technology, Korla, Xinjiang, China.

Peerj. Computer Science
|March 10, 2025
PubMed
Summary
This summary is machine-generated.

This study introduces a graph-based abstraction for software-defined networking (SDN), simplifying network management. This approach offers a global view for efficient resource scheduling and application development.

Keywords:
Abstraction layerGraph modelNetwork application managementSoftware-defined networking (SDN)

More Related Videos

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

3.7K
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

472

Related Experiment Videos

Last Updated: May 23, 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

8.0K
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

3.7K
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

472

Area of Science:

  • Computer Science
  • Network Engineering

Background:

  • Software-defined networking (SDN) decouples control and data planes for centralized network management.
  • Northbound interfaces are crucial for implementing network services and application-oriented abstractions in SDN.

Purpose of the Study:

  • To present a graph-based architecture for abstracting SDN controllers at the application plane.
  • To virtualize network elements into a graph model for simplified resource management.

Main Methods:

  • Representing network elements and their attributes as a graph.
  • Implementing a virtualized logical abstraction layer independent of the physical network.
  • Validating the graph abstraction through experiments in topological display, dynamic routing, access control, and data persistence.

Main Results:

  • The graph abstraction layer enables direct scheduling of network resources via a global view.
  • Performance analysis, particularly shortest path calculations, validates the necessity and efficiency of the graph abstraction.
  • Demonstrated feasibility in topological display, dynamic route calculation, access control, and data persistence.

Conclusions:

  • The graph-based abstraction layer facilitates network slicing and maintains an accurate network depiction.
  • Streamlines network administration and application development by providing a sophisticated, understandable abstraction.
  • Empowers network administrators with enhanced control and visibility over network resources.