IEEE INTERNET COMPUTING
Scope & Guideline
Advancing Knowledge in Digital Networks
Introduction
Aims and Scopes
- Data Economy and Market Dynamics:
The journal frequently publishes research on data marketplaces, privacy, and trust management, exploring how data is exchanged and utilized in various sectors. - Artificial Intelligence (AI) and Machine Learning:
A significant focus is placed on AI and machine learning, particularly in the context of responsible AI governance, federated learning, and the development of trustworthy AI systems. - Edge and Cloud Computing:
Research on edge computing and cloud technologies is prevalent, with discussions on optimizing performance, enhancing security, and exploring the integration of these technologies with IoT. - Digital Twin Technologies:
The journal highlights the emerging field of digital twins, focusing on their applications across industries, including healthcare, manufacturing, and smart cities. - 6G and Future Networking Technologies:
There is a consistent emphasis on next-generation networks, particularly 6G technologies, exploring their potential applications and the challenges they pose. - Cybersecurity and Privacy:
Cybersecurity is a core area of research, with papers addressing issues such as privacy threats, data integrity, and ethical considerations in technology use. - Sociotechnical Systems and Ethics:
The journal examines the sociotechnical aspects of computing, emphasizing the ethical implications of technology deployment and the importance of accountability.
Trending and Emerging
- Trust and Accountability in AI:
The importance of trust, accountability, and ethics in AI systems is gaining momentum, highlighting the need for frameworks that ensure responsible AI governance. - Federated Learning and Privacy-Preserving Techniques:
Federated learning is becoming increasingly relevant as researchers focus on privacy-preserving methods that enable collaborative learning without compromising user data. - Digital Twin Applications Across Industries:
The application of digital twin technologies is on the rise, with a growing body of work exploring their potential in diverse fields such as healthcare, smart cities, and manufacturing. - 6G Technologies and Their Implications:
With the upcoming rollout of 6G, research is intensifying around its implications for networking, including new architectures, applications, and challenges. - Edge Computing Innovations:
Innovations in edge computing are emerging, particularly in the context of IoT and real-time data processing, as demand for low-latency solutions grows. - Cybersecurity in Complex Systems:
The focus on cybersecurity is evolving, with an increasing emphasis on addressing security challenges in complex, interconnected systems, particularly in the context of IoT and smart environments.
Declining or Waning
- Traditional Cloud Computing Models:
Research focusing solely on traditional cloud computing models has decreased as the community shifts towards more integrated approaches that combine cloud with edge and IoT technologies. - Basic Data Mining Techniques:
There is a noticeable decline in papers centered on basic data mining techniques without integration into broader frameworks or applications, as the field moves towards more complex and contextualized data analytics. - General Internet of Things (IoT) Applications:
While IoT remains a crucial area, the focus has shifted from generic applications to more specialized uses, particularly those involving security, privacy, and advanced data management. - Static Security Frameworks:
The emphasis on static security frameworks has waned, as researchers are increasingly interested in dynamic and adaptable security measures that address evolving threats. - Legacy Networking Protocols:
There is a decline in research related to legacy networking protocols, with a growing interest in innovative solutions that align with the demands of emerging technologies like 6G.
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