Mission Critical Sensors and Sensor Networks (MC-SSN)

Submission Deadline: 30 October 2019

IEEE Access invites manuscript submissions in the area of Mission Critical Sensors and Sensor Networks (MC-SSN).

MC-SSN have been applied to missions such as battlefield, border patrol, search and rescue, critical structure monitoring and surveillance, etc. To support critical missions, sensors and sensor networks will need to be flexible and interactive, and still work despite limited bandwidth, intermittent connectivity and with a large number of devices on the network. Sometimes, humans will be the elements within mission critical sensors and sensor networks that are most vulnerable to deception, and humans will be handicapped when they are concerned that information they are receiving via the network is untrustworthy, even if that concern is misplaced. For example, the military can take all kinds of measures to counterattack cyberattacks on sensor networks, including injecting fake code meant to attract and catch intruders, using disposable connected devices, large-scale physical fingerprinting and ongoing physical and information probing of networks. The military will also need to look at the “psychosocial behaviors” of attackers and see if they can discern patterns of behavior.

In MC-SSN, the advantages of linking multiple electronic support measures and electronic attack assets to achieve improved capabilities across a networked mission-critical force have yet to be quantified. Algorithms are sought for fused, and/or, coherent cross-platform Radio Frequency (RF) sensing. The MC-SSN algorithms should be capable of utilizing RF returns from multiple aspects in time-coordinated sensors and sensor networks. Such adaptation, management and re-organization of information sources, devices, and networks must be accomplished almost entirely autonomously, in order to avoid imposing additional burdens on humans, and without much reliance on support and maintenance services. Moreover, humans, under extreme cognitive and physical stress, will be strongly challenged by the massive complexity of the MC-SSN and the information it will produce and carry. Advances in technologies that capitalize on the benefits of the MC-SSN will have to assist humans in making useful sense of this massive, complex, confusing, and potentially deceptive ocean of information, while taking into account the ever-changing mission.  New approaches and low-complexity algorithms are expected to enable MC-SSN to automatically manage and effect risk and uncertainty in a highly deceptive, mixed cooperative/adversarial, information-centric environment. All of these challenges demand new theories of (and methods for) sensor design, networking, sensing, information management, and decision support analytics. The goal of the Special Section in IEEE Access is to publish the most recent (unclassified) results in MC-SSN.

The topics of interest include, but are not limited to:

  • Overcoming Bandwidth limitation in MC-SSN
  • Intermittent connectivity modeling in MC-SSN
  • Massive devices management in MC-SSN
  • Cybersecurity in MC-SSN
  • Density and deployment of the MC-SSN
  • Heterogeneous modality selection in MC-SSN
  • Information fusion in MC-SSN
  • Capacity of MC-SSN
  • Reliable communications in MC-SSN
  • Target detection in MC-SSN
  • Dynamic resource allocation in MC-SSN
  • Adapt MC-SSN local and distributed processing
  • Waveform design and adaptation in MC-SSN
  • Decision making with uncertainties in MC-SSN
  • Human in the loop for MC-SSN
  • Machine learning for MC-SSN
  • Situation understanding based on MC-SSN
  • Threat assessment based on MC-SSN
  • New and nontraditional sensors in MC-SSN

We also highly recommend the submission of multimedia with each article as it significantly increases the visibility, downloads, and citations of articles.

Associate Editor:  Qilian Liang, University of Texas at Arlington, USA

Guest Editors:

  1. Tariq S. Durrani, University of Strathclyde, UK
  2. Jing Liang, University of Electronic Science and Technology, China
  3. Jinhwan Koh, Gyeongsang National University, Korea
  4. Yonghui Li, University of Sydney, Australia
  5. Xin Wang, Qualcomm Inc, USA


Relevant IEEE Access Special Sections:

  1. Convergence of Sensor Networks, Cloud Computing, and Big Data in Industrial Internet of Things
  2. Networks of Unmanned Aerial Vehicles: Wireless Communications, Applications, Control and Modelling
  3. Underwater Wireless Communications and Networking


IEEE Access Editor-in-Chief: Michael Pecht, Professor and Director, CALCE, University of Maryland

Paper submission: Contact Associate Editor and submit manuscript to:

For inquiries regarding this Special Section, please contact: liang@uta.edu