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ITU Journal: NexGen Computer Communications & Networks

This special issue started as an effort to expand some of the best papers presented in the IEEE International Symposium on Computers and Communications (ISCC) 2022 and 2023 editions. It also includes several other papers that were accepted through an open call after a rigorous reviewing process.
The addressed topics highlighted the dynamics of the field and provided ideas for the future. The traditional issues of optimal scheduling are addressed in innovative ways that consider the current size of the networks and the interplay and synergies between software and hardware when designing appropriate algorithms.
The long-established neural networks and artificial intelligence approaches are now seen from a different perspective due to the availability of the appropriate hardware and software both at the provided and the malicious user sides. The need for security is expressed in various forms and different environments and uses innovative solutions from the tools that the current AI landscape provides
The rapid expansion and transformation of the communication and networking industries requires creative solutions to ensure efficient performance and the delivery of advanced services to users.

These solutions can include network optimization, effective data management, cognitive computing, block-chain solutions, and unconventional hardware and software design and implementation.

Such innovative approaches can be beneficial not only in the operation of existing networks but also in the design of future network architecture, whether it be evolutionary or disruptive.
Here are some examples of creative solutions that can help ensure efficient performance and the delivery of advanced services to users in the communication and networking industries:
Network optimization:
This can involve using techniques such as traffic engineering, load balancing, and caching to improve the performance of networks.
Effective data management:
This can involve using techniques such as data compression, data encryption, and data analytics to improve the efficiency and security of data storage and transmission.
Cognitive computing:
This can involve using techniques such as machine learning and artificial intelligence to improve the ability of networks to learn from data and make decisions autonomously.
Block-chain solutions:
This can involve using techniques such as distributed ledgers and smart contracts to improve the security and transparency of networks.
Unconventional hardware and software design and implementation:
This can involve using techniques such as open source software, software-defined networking, and network function virtualization to improve the flexibility and scalability of networks.
These innovative approaches can be beneficial not only in the operation of existing networks but also in the design of future network architecture, whether it be evolutionary or disruptive.
For example, network optimization techniques can be used to improve the performance of existing networks, while cognitive computing techniques can be used to develop new and innovative network services. Similarly, block-chain solutions can be used to improve the security of existing networks, while unconventional hardware and software design and implementation techniques can be used to develop new and innovative network architectures.
The rapid expansion and transformation of the communication and networking industries is creating a need for creative solutions to ensure efficient performance and the delivery of advanced services to users. The solutions discussed above are just a few examples of the many innovative approaches that can be used to address this challenge.
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Issue 1 – Editorial
Volume 5 (2024), Issue 1

Enhancing user experience in home networks with machine learning-based classification
Rushat Rai, Thomas Basikolo
Volume 5 (2024), Issue 1, Pages 158-171

Adaptive HELLO protocol for vehicular networks
Nathalie Mitton, Yasir Saleem, Valeria Loscri, Christophe Bureau
Volume 5 (2024), Issue 1, Pages 147-157

On the extraction of RF fingerprints from LSTM hidden-state values for robust open-set detection
Luke Puppo, Weng-Keen Wong, Bechir Hamdaoui, Abdurrahman Elmaghbub, Lucy Lin
Volume 5 (2024), Issue 1, Pages 134-146

Unsupervised representation learning for BGP anomaly detection using graph auto-encoders
Kevin Hoarau, Pierre Ugo Tournoux, Tahiry Razafindralambo
Volume 5 (2024), Issue 1, Pages 120-133

A framework for automating environmental vulnerability analysis of network services
Dimitris Koutras, Panayiotis Kotzanikolaou, Evangelos Paklatzis, Christos Grigoriadis, Christos Douligeris
Volume 5 (2024), Issue 1, Pages 104-119

Automated Wi-Fi intrusion detection tool on 802.11 networks
Dimitris Koutras, Panos Dimitrellos, Panayiotis Kotzanikolaou, Christos Douligeris
Volume 5 (2024), Issue 1, Pages 88-103

Optimizing IoT security via TPM integration: An energy efficiency case study for node authentication
Anestis Papakotoulas, Theodoros Mylonas, Kakia Panagidi, Stathes Hadjiefthymiades
Volume 5 (2024), Issue 1, Pages 73-87

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