Sustainable Computing-Informatics & Systems
Scope & Guideline
Unleashing the potential of computing for a sustainable future.
Introduction
Aims and Scopes
- Sustainable Computing Practices:
The journal emphasizes research on sustainable computing practices that minimize energy consumption and carbon footprint across various computing environments, including cloud computing, mobile computing, and IoT. - Energy Efficiency Optimization:
A core focus is on optimizing energy usage in computing systems through innovative algorithms, machine learning techniques, and metaheuristic approaches to enhance performance while reducing energy demands. - Green Cloud Computing:
Research topics include strategies for green cloud computing, addressing challenges around resource allocation, task scheduling, and energy management in data centers. - Smart Systems Integration:
The journal explores the integration of smart technologies, such as IoT and AI, in sustainable systems, aiming to improve efficiency and reduce environmental impact in sectors like agriculture, healthcare, and urban management. - Renewable Energy Utilization:
It promotes research on the utilization of renewable energy sources in computing systems, including energy management frameworks for smart grids and renewable-powered data centers.
Trending and Emerging
- AI and Machine Learning for Sustainability:
There is a significant increase in research that utilizes AI and machine learning to optimize energy efficiency and sustainability across various applications, indicating a trend towards intelligent systems. - Blockchain Technology in Energy Management:
Emerging themes include the application of blockchain technology for secure and efficient energy management systems, particularly in smart grids and decentralized energy resources. - Smart Agriculture and Environmental Monitoring:
Research focusing on smart agriculture practices and environmental monitoring using IoT and machine learning has surged, reflecting a growing interest in sustainable farming and resource management. - Multi-Agent Systems for Resource Optimization:
The use of multi-agent systems for optimizing resource allocation and energy management in complex environments is increasingly prominent, showcasing a shift towards decentralized and collaborative approaches. - Resilience in Computing Systems:
Emerging studies are addressing the resilience and reliability of computing systems under dynamic conditions, indicating a growing recognition of the need for robust solutions in sustainability.
Declining or Waning
- Traditional Resource Management Techniques:
Research focusing on conventional resource management techniques without integrating modern optimization strategies or AI is becoming less prevalent, as newer methodologies gain prominence. - Static Energy Consumption Models:
There is a noticeable decline in studies centered around static models for energy consumption, as the field moves towards dynamic and adaptive models that better reflect real-world scenarios. - General Surveys on Sustainable Practices:
Generalized survey papers that do not contribute new insights or methodologies are being published less frequently, indicating a shift towards more innovative and applied research.
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