Skip to main content

License: MIT Tests codecov Code style: black Docs pages-build-deployment GitHub Repo stars GitHub last commit

agenet

Agenet is an open-source Python package designed to estimate the Age of Information (AoI) in cooperative wireless networks. By implementing a system model that combines finite blocklength information theory and AoI analysis over Rayleigh fading channels, Agenet provides researchers and practitioners with a comprehensive tool for studying short packet-based communication networks. This package is particularly valuable for those working on mission-critical wireless systems where the freshness of information is crucial.

System model

The following figure illustrates the wireless communication system that is proposed in this application.

System model.

Agenet implements a short packet decode-and-forward (DF) cooperative wireless relaying system. This system consists of three key nodes: a source node (S) that generates and transmits new updates, a relay node (R) that receives, decodes, and forwards data, and a destination node (D) that receives the forwarded data. The communication process is structured into two time slots within each transmission block, with the source transmitting data to the relay in the first slot, and the relay decoding and forwarding the data to the destination in the second slot. This model accounts for both small-scale and large-scale channel gains, considering Rayleigh fading and path loss to provide a realistic representation of wireless communication environments.

Features

The agenet package allows the user to study the Age of Information (AoI) in cooperative wireless networks, which can be used as a basis for implementing mission-critical wireless communication applications. This application can be used as a study tool to analyze the age of information in cooperative wireless networks under short packet communications scenarios to maintain URLLC (ultra-reliable low-latency communication). In this application, various parameters such as power allocation, block length, packet size and transmission power can be adjusted to analyze how the age of information varies.

The agenet package contains several functions that can be used to study the AoI in a cooperative wireless networks. These functions allow the user to:

  • Calculate the Signal-to-Noise Ratio (SNR) at each receiving node in the network, which is an important factor in determining the quality of the communication link;

  • Calculate the Block Error Rate (BER) for each destination in the network, which is an important metric for assessing the reliability of the network;

  • Calculate the theoretical AoI and simulate the AoI for a given network configuration, allowing the comparison of both measures to verify the accuracy of the simulation, as well as analyzing the performance of the network and assessing the impact of various parameters on the AoI;

  • Estimate the average AoI value for a given update generation time and receiving time, which is a useful metric for evaluating the performance of any network.

Additionally, the agenet command-line script is included in the package, allowing for easy experimentation with the model with default or user-defined parameters. The simulation can generate both theoretical and simulated values for various factors such as block lengths, power allocations, packet sizes and transmission power in the network.

How to install

Install from PyPI:

pip install agenet

Or directly from GitHub:

pip install git+https://github.com/cahthuranag/agenet.git#egg=agenet

Installing for development and/or improving the package

git clone https://github.com/cahthuranag/agenet.git
cd agenet
pip install -e .[dev]

This way, the package is installed in development mode. As a result, development dependencies are also installed.

Documentation

For more detailed information about Agenet's features and usage, please refer to the Agenet package documentation.

License

MIT License

References

  1. Y. Polyanskiy, H. V. Poor, and S. Verdu, "Channel coding rate in the finite blocklength regime," IEEE Trans. Inf. Theory, vol. 56, no. 5, pp. 2307–2359, 2010.
  2. C. M. Wijerathna Basnayaka, D. N. K. Jayakody, T. D. Ponnimbaduge Perera, and M. Vidal Ribeiro, "Age of information in an urllc-enabled decode-and-forward wireless communication system," in 2021 IEEE 93rd Vehicular Technology Conference (VTC2021-Spring), 2021, pp. 1–6.
  3. R. D. Yates, Y. Sun, D. R. Brown, S. K. Kaul, E. Modiano, and S. Ulukus, "Age of information: An introduction and survey," IEEE Journal on Selected Areas in Communications, vol. 39, no. 5, pp. 1183–1210, 2021.

Metadata

Release files for agenet 1.0.0

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for agenet 1.0.0
File Size Uploaded
agenet-1.0.0.tar.gz 24.2 kB Details

Built distribution (wheel)

Table of built distributions (wheels) for agenet 1.0.0
File Interpreter ABI Platform
agenet-1.0.0-py3-none-any.whl Python 3 none any Details

Total release size: 41.0 kB

Release files / agenet-1.0.0.tar.gz

Download URL agenet-1.0.0.tar.gz
Size 24.2 kB
Tags Source
SHA-256 checksum
How to use checksums
91f83c9f9a03a56a65c1af2919006bf5760b7361d6f994bc24d71d2f3b3697e3
BLAKE2b-256 checksum
How to use checksums
6260faefdd4292f765bd91a0baef088afe6f575ba632462cd8515aa74b102832
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/5.1.1 CPython/3.12.7

Release files / agenet-1.0.0-py3-none-any.whl

Download URL agenet-1.0.0-py3-none-any.whl
Size 16.8 kB
Tags Python 3
SHA-256 checksum
How to use checksums
38e37b683a953959a2e00081ca83d6f83bd20101aa4c1da2186bf764c871c23b
BLAKE2b-256 checksum
How to use checksums
69f22fdf0d21366b0068d8061e421d708b020bc7ca52573fe94480514659f767
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/5.1.1 CPython/3.12.7

Release history Release notifications | RSS feed

This release

1.0.0 This release

2 release files

0.2.0

2 release files

0.1.0

2 release files

0.0.1

2 release files

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page