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Electronics
Special Issues
Safety, Efficiency, and Reliability of Connected Smart Sensor Systems
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Safety, Efficiency, and Reliability of Connected Smart Sensor Systems

A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Computer Science & Engineering".

Deadline for manuscript submissions: closed (28 February 2022) | Viewed by 5002

Special Issue Editor

Dr. Myounggyu Won

E-Mail Website1 Website2
Guest Editor
Department of Computer Science, University of Memphis, Memphis, TN 38152, USA
Interests: Internet of Things; mobile computing; vehicular networks; intelligent transportation systems

Special Issue Information

Dear Colleagues,

Communities around the world are evolving in a rapid pace through interconnection of smart sensor systems advancing numerous areas of our society, including health care, transportation, electric power management, agriculture, emergency response, and education. While this evolution offers great promises for significantly improved safety, efficiency, and reliability for society, the complex nature of the connected smart sensor systems involving convergence of sensing, actuation, intelligent computation, and communication poses significant challenges, such as effective incorporation of heterogeneous system components, autonomous detection of failures and anomalies, stable operation under the presence of disturbances, energy efficiency, access control for protection of sensitive information, efficient communication protocols for interconnecting a huge number of sensors, and analysis and mining of big sensor data.

The aim of this Special Issue is to gather the latest contributions from academia and industry focused on addressing these key challenges for improving the safety, security, efficiency, and reliability of connected smart sensor systems. Review papers on emerging technologies and applications of novel connected smart sensor systems are welcome. The topics of interest include but are not limited to the following:

  • Network protocols for connected smart sensor systems;
  • Security, robustness, and reliability of connected smart sensor systems;
  • Energy efficiency for connected smart sensor systems;
  • Foundations and theory for connected smart sensor systems;
  • Edge and fog computing for connected smart sensor systems;
  • Embedded system architecture for connected smart sensor systems;
  • Deployment experiences;
  • Test-bed development experiences;
  • Machine learning analytics for connected smart sensor systems;
  • Big data management for connected smart sensor systems;
  • Data mining for connected smart sensor systems;
  • Human-in-the-loop aspects of connected smart sensor systems;
  • Applications of connected smart sensor systems.

Asst. Prof. Dr. Myounggyu Won
Guest Editor

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 100 words) can be sent to the Editorial Office for announcement on this website.

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. Electronics 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 2400 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

  • smart sensor systems
  • Internet of Things
  • cyber physical systems
  • machine learning

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Published Papers (2 papers)

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Research

16 pages, 943 KiB  
Article
ACE-M: Automated Control Flow Integrity Enforcement Based on MPUs at the Function Level
by Sungbin Lee and Jeonghun Cho
Electronics 2022, 11(6), 912; https://doi.org/10.3390/electronics11060912 - 15 Mar 2022
Cited by 1 | Viewed by 2034
Abstract
Control-flow integrity(CFI) ensures that the execution flow of a program follows the control-flow graph(CFG) determined at compile time. CFI is a security technique designed to prevent runtime attacks such as return-oriented programming (ROP). With the development of the Internet of Things (IoT), the [...] Read more.
Control-flow integrity(CFI) ensures that the execution flow of a program follows the control-flow graph(CFG) determined at compile time. CFI is a security technique designed to prevent runtime attacks such as return-oriented programming (ROP). With the development of the Internet of Things (IoT), the number of embedded devices has increased, and security and protection techniques in embedded systems have become important. Since the hardware-based CFI technique requires separate hardware support, it is difficult to apply to an embedded device that is already arranged. In this paper, we propose a function-level CFI technique named ACE-M, which uses the memory protection unit (MPU) included in most embedded devices. MPU may provide attributes such as read-write-execute to the memory area. ACE-M has three steps: (1) initiate—inserts an MPU-related function into a specific position; (2) profiling—provides information for MPU configuration. After the initation step, several pieces of information can be determined; (3) set—modify the already-inserted function’s arguments. We propose a design that supports the MPU. In our model, the MPU becomes a control flow monitor that detects control flow errors(CFEs), and the inserted codes cause the MPU to act as a control flow checker. If the program deviates from the original control flow, the MPU raises an exception since its corresponding area will not be included in the executable area. This approach not only verifies the target address but also guarantees the running position. Our technique can detect any modification of the program counter (PC) to an arbitrary address. Full article
(This article belongs to the Special Issue Safety, Efficiency, and Reliability of Connected Smart Sensor Systems)
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20 pages, 3123 KiB  
Article
Binary-Addition Tree Algorithm-Based Resilience Assessment for Binary-State Network Problems
by Yi-Zhu Su and Wei-Chang Yeh
Electronics 2020, 9(8), 1207; https://doi.org/10.3390/electronics9081207 - 27 Jul 2020
Cited by 18 | Viewed by 2296
Abstract
Applications in real life are composed of different kinds of network systems; these networks may be interfered by uncontrollable or unpredictable disruptive events involving natural disasters, human errors, evil-intentioned attacks, or other disturbances. Any of these disruptive events will cause networks to malfunction [...] Read more.
Applications in real life are composed of different kinds of network systems; these networks may be interfered by uncontrollable or unpredictable disruptive events involving natural disasters, human errors, evil-intentioned attacks, or other disturbances. Any of these disruptive events will cause networks to malfunction and possibly result in large economic losses. As a result, it is important to assess network resilience which is a measure to describe how a network system recovers its performance and functionality to a satisfactory level from a disruptive event. Inspired by the measures of reliability evaluation used in binary-state networks, this paper proposes a binary-addition tree algorithm-based resilience assessment for binary-state networks and applies it on a wildfire network with wireless sensors. Considering the stochastic nature of disruptive events, the proposed binary-addition tree algorithm-based resilience assessment comprehensively enumerates all the possible disruptive events and all the corresponding recovery strategies, and then calculate the network resilience. Furthermore, recovery cost limit is concerned in this paper for decision makers who choose the recovery strategies with their recovery cost limit and resilience requirement. Full article
(This article belongs to the Special Issue Safety, Efficiency, and Reliability of Connected Smart Sensor Systems)
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