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Special Issue "Wireless Systems and Networks in the IoT"

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Internet of Things".

Deadline for manuscript submissions: closed (1 November 2019).

Special Issue Editors

Prof. Dr. Damianos Gavalas
E-Mail Website
Guest Editor
Department of Product and Systems Design Engineering, University of the Aegean, GR-84100 Syros, Greece
Interests: mobile and pervasive computing; wireless sensor networks; information technologies in cultural heritage and tourism; intelligent transportation systems
Special Issues, Collections and Topics in MDPI journals
Dr. Modestos Stavrakis
E-Mail Website
Guest Editor
Department of Product and Systems Design Engineering, University of the Aegean, GR-84100 Syros, Greece
Interests: interaction design; interactive systems; wearable computing; physical computing; Internet of Things
Dr. Periklis Chatzimisios
E-Mail Website
Guest Editor
Computing Systems, Security and Networks Lab, Department of Informatics, Alexander Technological Educational Institute of Thessaloniki (ATEITHE), P.O. Box. 141, 57400 Sindos, Thessaloniki, Greece
Interests: mobile and wireless communications; Internet of Things; 5G; V2X communications; smart cities; standardization; Industry 4.0; big data; cloud computing; telecommunication and network engineering education
Special Issues, Collections and Topics in MDPI journals
Dr. Zhichao Cao
E-Mail Website
Guest Editor
Tsinghua Universeity, Beijing, 100084, China
Interests: internet of things, wireless sensor networks, LPWAN, edge computing, mobile computing
Dr. Xiaolong Zheng
E-Mail Website
Guest Editor
School of Computer Science, Beijing University of Posts and Telecommunications, Beijing, China
Interests: internet of things, wireless networking, mobile & ubiquitous computing

Special Issue Information

Dear Colleagues,

This Special Issue primarily aims at soliciting selected papers presented at the International Workshops colocated with the EWSN 2019 Conference, held on 25 February 2019 in Beijing, China. EWSN is a highly selective, annual forum for presenting research results in the field of networked embedded systems, broadly defined, including, for example, wireless sensor networks, Internet of Things, or cyber-physical systems. The workshops colocated with the EWSN 2019 consist of the following:

  • Workshop on Recent Advances in Wireless Coexistence for Heterogeneous IoT (CoWireless);
  • 2nd International Workshop on Crowd Intelligence for Smart Cities: Technology and Applications (CISC 2019);
  • 1st International Workshop on 6LoWPAN for the Internet of Things (6LoWPAN);
  • Workshop on Security, Reliability, and Resilience in Wireless Sensor Networks (WSRRWSN);
  • 1st Workshop on Low Power Wide Area Networks for Internet of Things (LPNET);
  • 1st International Workshop on Distributed Fog Services Design (DFSD 2019).

The Special Issue also solicits extended versions of selected EWSN 2019 poster session papers.

We invite all contributors to submit an extended version of their EWSN 2019 contribution in this Special Issue of the journal Sensors (ISSN1424-8220; Impact Factor 2.475; https://www.mdpi.com/journal/sensors) published online by MDPI, Switzerland. According to the publishing rules, the full paper should be based on the respective conference version and should be expanded to the size of a research article (add about 50% new material). The length of the extended poster papers should approximately be 6,000–8,000 words.

In addition to the EWSN 2019 Workshops and poster papers, other independent submissions are also welcome. The theme of these contributions may involve any aspect pertaining to the area of wireless systems and networks in the IoT. Topics of interest include but are not limited to the following:

  • Architecture, design, implementation, and measurement of wireless coexistence for heterogeneous IoT systems;
  • Cross-frequency communication in IoT;
  • Cross-technology communication and interference;
  • Big data analytics for IoT wireless networks and systems;
  • 6LoWPAN for Internet of Things;
  • Security, reliability, and resilience in IoT communications;
  • Low power wide area networks for Internet of Things (e.g., LoRa, NB-IoT);
  • Cloud computing and fog computing IoT wireless networks and systems.

Dr. Damianos Gavalas
Dr. Modestos Stavrakis
Dr. Periklis Chatzimisios
Dr. Zhichao Cao
Dr. Xiaolong Zheng
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 papers will be 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. 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 2200 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

  • Wireless coexistence
  • Cross-technology communication keywords
  • 6LoWPAN
  • LoRa
  • NB-IoT

Published Papers (8 papers)

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Editorial

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Editorial
Wireless Systems and Networks in the IoT
Sensors 2020, 20(8), 2279; https://doi.org/10.3390/s20082279 - 17 Apr 2020
Viewed by 886
Abstract
This Special Issue is focused on breakthrough developments in the field of Wireless Systems and Networks in the IoT. The selected contributions report current scientific progress in a wide range of topics covering clock error compensation in sensor networks, backscatter communication networks, Radio-Frequency [...] Read more.
This Special Issue is focused on breakthrough developments in the field of Wireless Systems and Networks in the IoT. The selected contributions report current scientific progress in a wide range of topics covering clock error compensation in sensor networks, backscatter communication networks, Radio-Frequency Identification (RFID)-based inventory management, resource allocation in Long-Term Evolution (LTE)/LTE-A, (Long Range Wide-Area Network (LoRaWAN) modeling and key generation for the IoT. Full article
(This article belongs to the Special Issue Wireless Systems and Networks in the IoT)

Research

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Article
Compensation Method for Sensor Network Clock Error Based on Cyclic Symmetry Algorithm
Sensors 2020, 20(6), 1738; https://doi.org/10.3390/s20061738 - 20 Mar 2020
Cited by 2 | Viewed by 767
Abstract
Since the existing methods cannot evaluate the time delay of different layers of sensor networks, there are some problems such as the low precision of clock error compensation, high time delay, and low efficiency of communication in sensor networks. To solve this problem, [...] Read more.
Since the existing methods cannot evaluate the time delay of different layers of sensor networks, there are some problems such as the low precision of clock error compensation, high time delay, and low efficiency of communication in sensor networks. To solve this problem, a method of clock error compensation in sensor networks based on a cyclic symmetry algorithm is proposed. Based on the basic theory of cyclic symmetry, the cyclic symmetry matrix of the sensor network is constructed; in the communication process, all nodes are extended to get the cumulative delay rate of the sensor network in the specified time domain. Using the cumulative delay rate of the cyclic network and the sensor network, the autoregressive integral sliding mode control model is established to compensate for the cumulative error of clock synchronization. The simulation results show that the compensation accuracy of this method is more than 98%, which can effectively reduce the delay of sensor network. It improves the communication efficiency of the sensor network, meets the communication requirements of the sensor network, and has a very broad application prospect. Full article
(This article belongs to the Special Issue Wireless Systems and Networks in the IoT)
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Article
Channel Prediction Based on BP Neural Network for Backscatter Communication Networks
Sensors 2020, 20(1), 300; https://doi.org/10.3390/s20010300 - 05 Jan 2020
Cited by 3 | Viewed by 1283
Abstract
Backscatter communication networks are receiving a lot of attention thanks to the application of ultra-low power sensors. Because of the large amount of sensor data, increasing network throughput becomes a key issue, so rate adaption based on channel quality is a novel direction. [...] Read more.
Backscatter communication networks are receiving a lot of attention thanks to the application of ultra-low power sensors. Because of the large amount of sensor data, increasing network throughput becomes a key issue, so rate adaption based on channel quality is a novel direction. Most existing methods share common drawbacks; that is, spatial and frequency diversity cannot be considered at the same time or channel probe is expensive. In this paper, we propose a channel prediction scheme for backscatter networks. The scheme consists of two parts: the monitoring module, which uses the data of the acceleration sensor to monitor the movement of the node itself, and uses the link burstiness metric β to monitor the burstiness caused by the environmental change, thereby determining that new data of channel quality are needed. The prediction module predicts the channel quality at the next moment using a prediction algorithm based on BP (back propagation) neural network. We implemented the scheme on readers. The experimental results show that the accuracy of channel prediction is high and the network goodput is improved. Full article
(This article belongs to the Special Issue Wireless Systems and Networks in the IoT)
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Article
Intelligent Management of Chemical Warehouses with RFID Systems
Sensors 2020, 20(1), 123; https://doi.org/10.3390/s20010123 - 24 Dec 2019
Cited by 2 | Viewed by 1068
Abstract
At present, most chemical warehouses rely on human management, which is a time-consuming and laborious process. Therefore, it is very meaningful to use radio frequency identification (RFID) systems for the intelligent management of chemicals. Detecting the remaining amount of chemicals is an important [...] Read more.
At present, most chemical warehouses rely on human management, which is a time-consuming and laborious process. Therefore, it is very meaningful to use radio frequency identification (RFID) systems for the intelligent management of chemicals. Detecting the remaining amount of chemicals is an important process in the management of a chemical warehouse. It helps managers find the chemicals that are going to run out and replenish them in time. However, in a traditional chemical warehouse, managers usually inspect each chemical on the shelf in turn manually, which is a waste of time and labor. Although some solutions using RFID technology have been proposed, they are expensive and difficult to deploy in a real environment. In order to solve this problem, we propose an intelligent system called the RF-Detector in this paper, which combines robotics and RFID technology. An RFID reader and an antenna are installed on the robot, which achieves automatic scanning of the chemicals. The RF-Detector can achieve two functions: One function is to detect the remaining amount of chemicals using the changes in received signal strength indication (RSSI) and read rate, and the other is to locate chemicals using the phase curve, so that managers can quickly find the chemicals with an insufficient amount remaining. In this paper we implement the RF-Detector and evaluate its performance. The experimental results show that the RF-Detector achieves about 93% detection accuracy and 92% positioning accuracy for chemicals. Full article
(This article belongs to the Special Issue Wireless Systems and Networks in the IoT)
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Article
Fast and Reliable Burst Data Transmission for Backscatter Communications
Sensors 2019, 19(24), 5418; https://doi.org/10.3390/s19245418 - 09 Dec 2019
Cited by 2 | Viewed by 884
Abstract
Computational radio frequency identification (CRFID) sensors are able to transfer potentially large amounts of data to the reader in the radio frequency range. However, the existing EPC C1G2 protocol is inefficient when there are abundant critical and emergency data to be transmitted and [...] Read more.
Computational radio frequency identification (CRFID) sensors are able to transfer potentially large amounts of data to the reader in the radio frequency range. However, the existing EPC C1G2 protocol is inefficient when there are abundant critical and emergency data to be transmitted and cannot adapt to changing energy-harvesting and channel conditions. In this paper, we propose a fast and reliable method for burst data transmission by fragmenting large data packets into blocks and we introduce a burst transmission mechanism to optimize the EPC C1G2 communication procedure for burst transmission when there are critical and emergency data to be transmitted. In addition, we utilize erasure codes to reduce Acknowledgement (ACK) delay and to improve system reliability. Our results show that our proposed scheme significantly outperforms the current fixed frame length approach and the dynamic frame length and charging time adaptation scheme (DFCA) and that the goodput is close to the theoretically optimal value under different energy-harvesting and channel conditions. Full article
(This article belongs to the Special Issue Wireless Systems and Networks in the IoT)
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Article
Energy Efficient Resource Allocation for M2M Devices in LTE/LTE-A
Sensors 2019, 19(24), 5337; https://doi.org/10.3390/s19245337 - 04 Dec 2019
Cited by 4 | Viewed by 1093
Abstract
Machine-to-machine (M2M) communication consists of the communication between intelligent devices without human intervention. Long term evolution (LTE) and Long-term evolution-advanced (LTE-A) cellular networks technologies are excellent candidates to support M2M communication as they offer high data rates, low latencies, high capacities and more [...] Read more.
Machine-to-machine (M2M) communication consists of the communication between intelligent devices without human intervention. Long term evolution (LTE) and Long-term evolution-advanced (LTE-A) cellular networks technologies are excellent candidates to support M2M communication as they offer high data rates, low latencies, high capacities and more flexibility. However, M2M communication over LTE/LTE-A networks faces some challenges. One of these challenges is the management of resource radios especially on the uplink. LTE schedulers should be able to meet the needs of M2M devices, such as power management and the support of large number of devices, in addition to handling both human-to-human (H2H) and M2M communications. Motivated by the fundamental requirement of extending the battery lives of M2M devices and managing an LTE network system, including both M2M devices and H2H users, in this paper, two channel-aware scheduling algorithms on the uplink are proposed. Both of them consider the coexistence of H2H and M2M communications and aim to reduce energy consumption in M2M devices. The first algorithm, called FDPS-carrier-by-carrier modified (CBC-M), takes into account channel quality and power consumption while allocating radio resources. Our second algorithm, recursive maximum expansion modified (RME-M), offers a balance between delay requirement and energy consumption. Depending on the system requirements, RME-M considers both channel quality and system deadlines in an adjustable manner according to M2M devices needs. Simulation results show that the proposed schedulers outperform the round-robin scheduler in terms of energy efficiency and have better cell spectral efficiency. Full article
(This article belongs to the Special Issue Wireless Systems and Networks in the IoT)
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Article
LoRaWAN Modeling and MCS Allocation to Satisfy Heterogeneous QoS Requirements
Sensors 2019, 19(19), 4204; https://doi.org/10.3390/s19194204 - 27 Sep 2019
Cited by 13 | Viewed by 1386
Abstract
LoRaWAN infrastructure has become widely deployed to provide wireless communications for various sensor applications. These applications generate different traffic volumes and require different quality of service (QoS). The paper presents an accurate mathematical model of low-power data transmission in a LoRaWAN sensor network, [...] Read more.
LoRaWAN infrastructure has become widely deployed to provide wireless communications for various sensor applications. These applications generate different traffic volumes and require different quality of service (QoS). The paper presents an accurate mathematical model of low-power data transmission in a LoRaWAN sensor network, which allows accurate validation of key QoS indices, such as network capacity and packet loss ratio. Since LoRaWAN networks operate in the unlicensed spectrum, the model takes into account transmission attempt failures caused by random noise in the channel. Given QoS requirements, we can use the model to study how the performance of a LoRaWAN network depends on the traffic load and other scenario parameters. Since in LoRaWAN networks the transmissions at different modulation and coding schemes (MCSs) typically do not collide, we use the model to assign MCSs to the devices to satisfy their QoS requirements. Full article
(This article belongs to the Special Issue Wireless Systems and Networks in the IoT)
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Article
An Efficient Key Generation for the Internet of Things Based Synchronized Quantization
Sensors 2019, 19(12), 2674; https://doi.org/10.3390/s19122674 - 13 Jun 2019
Cited by 8 | Viewed by 1283
Abstract
One solution to ensure secrecy in the Internet of Things (IoT) is cryptography. However, classical cryptographic systems require high computational complexity that is not appropriate for IoT devices with restricted computing resources, energy, and memory. Physical layer security that utilizes channel characteristics is [...] Read more.
One solution to ensure secrecy in the Internet of Things (IoT) is cryptography. However, classical cryptographic systems require high computational complexity that is not appropriate for IoT devices with restricted computing resources, energy, and memory. Physical layer security that utilizes channel characteristics is an often used solution because it is simpler and more efficient than classical cryptographic systems. In this paper, we propose a signal strength exchange (SSE) system as an efficient key generation system and a synchronized quantization (SQ) method as a part of the SSE system that synchronizes data blocks in the quantization phase. The SQ method eliminates the signal pre-processing phase by performing a multi-bit conversion directly from the channel characteristics of the measurement results. Synchronization is carried out between the two authorized nodes to ensure sameness of the produced keys so it can eliminate the error-correcting phase. The test results at the IoT devices equipped with IEEE 802.11 radio show that SSE system is more efficient in terms of computing time and communication overhead than existing systems. Full article
(This article belongs to the Special Issue Wireless Systems and Networks in the IoT)
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