Sustainable computing is a rapidly expanding research area spanning the fields of computer science and engineering, electrical engineering as well as other engineering disciplines. The aim of Sustainable Computing: Informatics and Systems (SUSCOM) is to publish the myriad research findings related to energy-aware and thermal-aware management of computing resource. Equally important is a spectrum of related research issues such as applications of computing that can have ecological and societal impacts. SUSCOM publishes original and timely research papers and survey articles in current areas of power, energy, temperature, and environment related research areas of current importance to readers. SUSCOM has an editorial board comprising prominent researchers from around the world and selects competitively evaluated peer-reviewed papers.

Making computing sustainable - Software systems perspective:
• Power-aware software
• Code profiling and transformation for power management
• Power-aware middleware
• Multimedia systems
• Scheduling and allocation

Computing for sustainability - Use of computing to make the world a sustainable place:
• Use of sensors for environmental monitoring
• Smart control for eco-friendly buildings
• Green Data Centers and Enterprise Computing

Re-inventing algorithms and applications for sustainability:
• Theoretical aspect of energy, power, and temperature
• Power-aware applications
• Resource management to optimize performance and power
• Power implications for portable and mobile computing
• Algorithms for reduced power, energy and heat for high-performance computing

Modeling and evaluation of sustainable systems:
• Reliability of Power-aware computers
• Runtime systems that assist in power saving
• Models for collective optimization of power and performance
• Monitoring tools for power and performance of parallel and distributed systems

Sustainable hardware platforms and devices - Hardware and architecture perspective:
• Power aware networking
• Real-time systems
• Power-efficient architectures
• Efficient circuit design for energy harvesting
• Power management in memory, disk, storage and other peripheral devices
• Configurable and renewable energy
• Low power electronics
• Embedded systems, ASICs and FPGSs
• Power leakage and dissipation

Please submit your article via https://www.editorialmanager.com/suscom/default.aspx.

Special Issue on Distributed Machine Learning for Sustainable Edge Service Provisioning
Submission Date: 2024-08-31

This issue aims to cover all the emerging trends and technologies in mobile edge computing for future-generation IoT applications. Papers related to distributedmachine learning, distributed deep learning, sustainable computing, optimization, blockchain, authentication, service provisioning technique, 5G or beyond 5G solutions, especially for domain-specific edge computing supported applications such as healthcare, agriculture, Industry 4.0/5.0, and intelligent transportation systems, are strongly encouraged for this issue.

Guest editors:

Prof. Schahram Dustdar, TU Wien, Vienna, Austria
Prof. Praveen Kumar Donta, TU Wien, Vienna, Austria
Prof. Sindri Magnússon, Stockholm University, Stockholm, Sweden
Prof. Abhishek Hazra, IIIT Sri city, Chittoor, India

Special issue information:

Topics of interest for this issue include, but are not limited to:• Distributed Machine Learning for Security and Privacy Provisioning for Sustainable Edge Computing
• Distributed Machine Learning for Resource management to optimize performance and power
• Distributed Machine Learning methods for reliable resource provisioning in Sustainable edge-cloud computing
• Orchestrating Distributed Machine Learning for power-aware edge service provisioning
• Distributed Machine Learning methods for failure recovery in Sustainable Edge Computing
• Intelligence techniques for reduced power, energy and heat for distributed computing continuum systems
• Quantum machine learning for power-aware 6G communication and Sustainable networking
• Energy-Efficient Distributed Machine learning for 6G Networks
• The convergence and interplay of Sustainable edge, fog, and cloud in the distributed machine learning-driven
• Building Intelligent & Sustainable Internet-based Ecosystems
• Power-efficient Distributed machine learning architectures for sustainable edge networks
• Causal inference for Sustainable Edge Service Provisioning
• Eco-friendly Edge computing for distributed machine learning
• Distributed machine learning for energy-aware & thermal-aware management of computing continuum
resource
• Renewable energy configurations for Energy-efficient Compute continuum systems for DML
• Power implications for Generative AI for resource constrained sustainable computing continuum
• Power implications for Distributed computing systems for Large Language Models or Generative AI
• Use case, Case study, applications, or eco-friendly developments of sustainable distributed ML at the edge

Manuscript submission information:

Important Dates:

Submission Open Date: 02/05/2024
Manuscript Submission Deadline: 31/08/2024
Editorial notification: 15/01/2025

You are invited to submit your manuscript at any time before the submission deadline. For any inquiries about the appropriateness of contribution topics, please contact the executive guest editor: 

Prof. Schahram Dustdar, dustdar@dsg.tuwien.ac.at

The journal’s submission platform (Editorial Manager®) is now available for receiving submissions to this Special Issue. Please refer to the Guide for Authors to prepare your manuscript and select the article type of “VSI: SUSCOM_ Sustainable-Edge” when submitting your manuscript online. Both the Guide for Authors and the submission portal could be found on the Journal Homepage here: Sustainable Computing: Informatics and Systems | Journal | ScienceDirect.com by Elsevier

Keywords:

    Sustainable Edge/Fog Computing
    Distributed Systems
    Compute Continuum
    Distributed Machine Learning
    Sustainable Internet of Things
    Service Provisioning