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SDN-Enabled Sensing in Smart Infrastructure

This special issue belongs to the section “Physical Sensors“.

Special Issue Information

Dear Colleagues,

The rapid development in sensor technologies, computing and analytics has enabled the creation of new techniques used to monitor physical infrastructure. However, many of the underlying sensor/data networks in critical infrastructure are unable to self-reconfigure or fulfil the requirements of various applications. Furthermore, the constrained resources in edge/fog nodes limit their ability to process large quantities of data to accurately determine the optimum decision in real time. This makes remote processing unable to minimise the conflict between accuracy and timeliness of decisions. SDN allows the network to programmatically respond to the changes in the communication environment, traffic requirements and operating context.   

In critical infrastructure such as transportation systems, agriculture, smart grids, smart healthcare systems, robotic systems, etc., a loss of information of delays can lead to a loss of human lives or damage to expensive equipment, even if the actions are accurate. The agility and centralised management of data traffic provided by SDN opens new possibilities in the management of critical infrastructure.    

This Special Issue (SI) aims to bring together researchers and practitioners who are interested in the development of these techniques to understand or address the issues related to the application of SDN in critical infrastructure architectures, algorithms, and applications.

The list of possible topics includes, but is not limited to, the following:

  • Novel theories, concepts, and paradigm edge/IoT convergence;
  • Cybersecurity and mitigation in SDN;
  • Application of machine learning in SDN;
  • Surveys and tutorials;
  • Resource allocation and sharing;
  • Congestion management;
  • Quality of service;
  • Novel architectures;
  • Context awareness;
  • Non-deterministic communication;
  • Network automation;
  • Integration of blockchain;
  • SDN-based services in edge computing;
  • SDN for real-time industrial IoT applications;
  • Future directions;
  • Novel collaborative frameworks/algorithms/protocols for intelligent IoT applications;
  • SDN-enabled reliability and low latency for industrial IoT applications;
  • Applications of SDN in critical infrastructure.

Dr. Augustine Ikpehai
Dr. Abayomi Otebolaku
Dr. Kelvin Anoh
Dr. Bernardi Pranggono
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sensors is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • industrial Internet of Things
  • software-defined network
  • edge processing
  • smart infrastructure systems
  • machine learning
  • centralised management
  • artificial intelligence
  • cognitive communication and networking
  • intrusion detection
  • privacy and security

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Sensors - ISSN 1424-8220