摘要：Architectures and systems to avoid obsolescence, promote reusability, and enable longer lifetimes for saving CO2, GHGs

期刊全称：IEEE Transactions on Computers

所属领域：数据库/数据挖掘/内容检索

CCF分级：A类

期刊分区：JCR Q2、中科院2区

影响因子：3.6（2024年6月发布）

H指数（H-index）：110

期刊官网：https://www.Computer.org/csdl/journal/tc

专题截稿：2024年12月1日

专题名称：Carbon Efficient Computer Architectures and Systems

征文主题：

New models and metrics for carbon-efficient or sustainable computing architectures and systems including both embodied and operational greenhouse gas emissions (GHGs) including CO2

Architectures and systems to avoid obsolescence, promote reusability, and enable longer lifetimes for saving CO2, GHGs

Advances in edge and cloud technologies broadly to address provisioning and disaggregated computing to minimize CO2, GHGs

Carbon efficient accelerators for computationally complex algorithms such as machine learning, blockchain, homomorphic encryption, among others

Advances in architectures and systems leveraging emerging technologies targeting reduction of CO2, GHGs

Techniques to advance computing within the circular economy that considers manufacturing, operation, reuse, recycling, and disposal phases of systems

Architectures and systems that collaboratively enable sustainability in an application domain and through their ICT equipment

期刊全称：Computer Networks

所属领域：计算机网络

CCF分级：B类

期刊分区：JCR Q1、中科院3区

影响因子：4.4（2024年6月发布）

H指数（H-index）：119

First decision：8 days（来自期刊官网）

期刊官网：https://www.sciencedirect.com/journal/computer-networks/about/call-for-papers

This journal offers authors the option to publish their research via subscription (without Article Publishing Charge) or open access. To publish open access, a publication fee (APC) needs to be met by the author or research funder.

Generative AI, Explainable AI, AI-driven Network Traffic Analysis, Internet Traffic Analysis, Network Architectures, Network Management, Network Security, Network Analytics

来源：老齐的科学讲堂