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Wireless Sensor Networks and Communications
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Wireless Sensor Networks and Communications

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

Deadline for manuscript submissions: closed (31 October 2022) | Viewed by 13158

Special Issue Editors

Dr. Taufiq Asyhari

E-Mail Website
Guest Editor
School of Computing and Digital Technology, Birmingham City University (BCU), Millennium Point, Birmingham B4 7XG, UK
Interests: information theory; wireless communications and sensor networks; Internet of Things; applied machine learning and data analytics; intelligence system
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Marcos Katz

E-Mail Website
Guest Editor
Center for Wireless Communications, University of Oulu (UniOulu), 90500 Oulu, Finland
Interests: wireless and mobile communications; optical wireless communications; cooperative and cognitive communications; medical ICT communications
Dr. Bidushi Barua

E-Mail Website
Guest Editor
School of Computing and Digital Technology, Birmingham City University (BCU), Millennium Point, Birmingham B4 7XG, UK
Interests: Game theory; contract theory; network congestion; energy efficient networks; 5G micro operators; neutral host; machine learning

Special Issue Information

Dear Colleagues,

The recent progress in information and communication technologies (ICT) , including 5G, beyond cellular networks, and Internet of Things (IoT) technologies such as long-range (LoRa), narrowband IoT (NBIoT), etc., has led to a growing interest in utilizing these communication technologies in multi-domain sensing applications, allowing wireless sensors to be connected to each other and to the processing server. While sensing data have been traditionally processed within a powerful remote cloud server, the recent emergence of edge computing with these communication technologies makes it feasible to perform AI processing at the edges. Edge processing is aimed at overcoming the slower and more expensive method of sending the data to the cloud. The benefits of the parallel development of cloud-edge technologies in wireless sensor networks and communications are manifold. The progress in the development of these technologies has opened up several new opportunities in multi-domain applications, such as smart cities, transportation, intelligent manufacturing, and e-Health.

This Special Issue will solicit contributions that cover recent advances in wireless sensor networks and communication powered by cloud and edge technologies, including the fundamentals, technologies, and applications. Appropriate topics include, but are not limited to:

  • AI-based applications in wireless sensor and IoT networks
  • Cloud, edge, and combined cloud-edge computing architectures for wireless sensor and IoT applications
  • 5G and edge computing applications
  • NB-IoT networks for smart applications
  • Security mechanisms in 5G IoT networks
  • Wireless sensor networks for smart cities
  • Wireless sensor networks for transportation
  • Wireless sensor networks for intelligent manufacturing
  • Wireless sensor networks for e-Health

Dr. Taufiq Asyhari
Prof. Dr. Marcos Katz
Dr. Bidushi Barua
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 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 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

  • 5G
  • 6G
  • cloud-computing IoT
  • LoRa
  • NBIoT
  • multi-domain applications
  • edge-computing
  • wireless sensor networks

Published Papers (7 papers)

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Research

27 pages, 3586 KiB  
Article
Enhancing Localization Efficiency and Accuracy in Wireless Sensor Networks
by Muhammad Fawad, Muhammad Zahid Khan, Khalil Ullah, Hisham Alasmary, Danish Shehzad and Bilal Khan
Sensors 2023, 23(5), 2796; https://0-doi-org.brum.beds.ac.uk/10.3390/s23052796 - 03 Mar 2023
Cited by 7 | Viewed by 2093
Abstract
Accuracy is the vital indicator in location estimation used in many scenarios, such as warehousing, tracking, monitoring, security surveillance, etc., in a wireless sensor network (WSN). The conventional range-free DV-Hop algorithm uses hop distance to estimate sensor node positions but has limitations in [...] Read more.
Accuracy is the vital indicator in location estimation used in many scenarios, such as warehousing, tracking, monitoring, security surveillance, etc., in a wireless sensor network (WSN). The conventional range-free DV-Hop algorithm uses hop distance to estimate sensor node positions but has limitations in terms of accuracy. To address the issues of low accuracy and high energy consumption of DV-Hop-based localization in static WSNs, this paper proposes an enhanced DV-Hop algorithm for efficient and accurate localization with reduced energy consumption. The proposed method consists of three steps: first, the single-hop distance is corrected using the RSSI value for a specific radius; second, the average hop distance between unknown nodes and anchors is modified based on the difference between actual and estimated distances; and finally, the least-squares approach is used to estimate the location of each unknown node. The proposed algorithm, named Hop-correction and energy-efficient DV-Hop (HCEDV-Hop), is executed and evaluated in MATLAB to compare its performance with benchmark schemes. The results show that HCEDV-Hop improves localization accuracy by an average of 81.36%, 77.99%, 39.72%, and 9.96% compared to basic DV-Hop, WCL, improved DV-maxHop, and improved DV-Hop, respectively. In terms of message communication, the proposed algorithm reduces energy usage by 28% compared to DV-Hop and 17% compared to WCL. Full article
(This article belongs to the Special Issue Wireless Sensor Networks and Communications)
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21 pages, 1537 KiB  
Article
Data Dissemination in VANETs Using Particle Swarm Optimization
by Dhwani Desai, Hosam El-Ocla and Surbhi Purohit
Sensors 2023, 23(4), 2124; https://0-doi-org.brum.beds.ac.uk/10.3390/s23042124 - 13 Feb 2023
Cited by 6 | Viewed by 1873
Abstract
A vehicular Ad-Hoc Network (VANET) is a type of Mobile Ad-Hoc Networks (MANETs) that uses wireless routers inside each vehicle to act as a node. The need for effective solutions to urban traffic congestion issues has increased recently due to the growing number [...] Read more.
A vehicular Ad-Hoc Network (VANET) is a type of Mobile Ad-Hoc Networks (MANETs) that uses wireless routers inside each vehicle to act as a node. The need for effective solutions to urban traffic congestion issues has increased recently due to the growing number of automobile connections in the car communications system. To ensure a high level of service and avoid unsafe situations brought on by congestion or a broadcast storm, data dissemination in a VANET network requires an effective approach. Effective multi-objective optimization methods are required to tackle this because of the implied competing nature of multi-metric approaches. A meta-heuristic technique with a high level of solution interactions can handle efficient optimization. To accomplish this, a meta-heuristic search algorithm particle optimization was chosen. In this paper, we have created a network consisting of vehicles as nodes. The aim is to send emergency messages immediately to the stationary nodes. The normal messages will be sent to the FIFO queue. To send these messages to a destination node, multiple routes were found using Time delay-based Multipath Routing (TMR) method, and to find the optimal and secure path Particle Swarm Optimization (PSO) is used. Our method is compared with different optimization methods such as Ant Colony Optimization (ACO), Firefly Optimization (FFO), and Enhanced Flying Ant Colony Optimization (EFACO). Significant improvements in terms of throughput and packet loss ratio, reduced end-to-end delay, rounding overhead ratio, and the energy consumption are revealed by the experimental results. Full article
(This article belongs to the Special Issue Wireless Sensor Networks and Communications)
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14 pages, 4056 KiB  
Article
An Energy Efficient Load Balancing Tree-Based Data Aggregation Scheme for Grid-Based Wireless Sensor Networks
by Neng-Chung Wang, Chao-Yang Lee, Young-Long Chen, Ching-Mu Chen and Zi-Zhen Chen
Sensors 2022, 22(23), 9303; https://0-doi-org.brum.beds.ac.uk/10.3390/s22239303 - 29 Nov 2022
Cited by 7 | Viewed by 1358
Abstract
A wireless sensor network (WSN) consists of a very large number of sensors which are deployed in the specific area of interest. A sensor is an electronic device equipped with a small processor and has a small-capacity memory. The WSN has the functions [...] Read more.
A wireless sensor network (WSN) consists of a very large number of sensors which are deployed in the specific area of interest. A sensor is an electronic device equipped with a small processor and has a small-capacity memory. The WSN has the functions of low cost, easy deployment, and random reconfiguration. In this paper, an energy-efficient load balancing tree-based data aggregation scheme (LB-TBDAS) for grid-based WSNs is proposed. In this scheme, the sensing area is partitioned into many cells of a grid and then the sensor node with the maximum residual energy is elected to be the cell head in each cell. Then, the tree-like path is established by using the minimum spanning tree algorithm. In the tree construction, it must meet the three constraints, which are the minimum energy consumption spanning tree, the network depth, and the maximum number of child nodes. In the data transmission process, the cell head is responsible for collecting the sensing data in each cell, and the collected data are transmitted along the tree-like path to the base station (BS). Simulation results show that the total energy consumption of LB-TBDAS is significantly less than that of GB-PEDAP and PEDAP. Compared to GB-PEDAP and PEDAP, the proposed LB-TBDAS extends the network lifetime by more than 100%. The proposed LB-TBDAS can avoid excessive energy consumption of sensor nodes during multi-hop data transmission and can also avoid the hotspot problem of WSNs. Full article
(This article belongs to the Special Issue Wireless Sensor Networks and Communications)
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18 pages, 3017 KiB  
Article
On Transient Queue-Size Distribution in a Model of WSN Node with Threshold-Type Power-Saving Algorithm
by Wojciech M. Kempa and Dariusz Kurzyk
Sensors 2022, 22(23), 9285; https://0-doi-org.brum.beds.ac.uk/10.3390/s22239285 - 29 Nov 2022
Cited by 1 | Viewed by 948
Abstract
This article proposes a queueing model of the operation of a wireless sensor network node, in which a threshold strategy for starting the node after a period of no transmission is used. In this model, transmission of packets is resumed when the number [...] Read more.
This article proposes a queueing model of the operation of a wireless sensor network node, in which a threshold strategy for starting the node after a period of no transmission is used. In this model, transmission of packets is resumed when the number of packets in the accumulation buffer reaches a predefined level. In the literature, most of the results for models with limited access to the service station are obtained in equilibrium. In this paper, a formula for the Laplace transform of the transient queue-size distribution is obtained and written using the key input parameters of the system. The analytical apparatus uses the concept of the embedded Markov chain, the formula for total probability, renewal theory and some supporting algebraic results. Numerical examples are attached as well. Full article
(This article belongs to the Special Issue Wireless Sensor Networks and Communications)
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17 pages, 22671 KiB  
Article
Problem Characteristics and Dynamic Search Balance-Based Artificial Bee Colony for the Optimization of Two-Tiered WSN Lifetime with Relay Nodes Deployment
by Wenjie Yu, Xiangmei Li, Zhi Zeng and Miao Luo
Sensors 2022, 22(22), 8916; https://0-doi-org.brum.beds.ac.uk/10.3390/s22228916 - 18 Nov 2022
Cited by 3 | Viewed by 1060
Abstract
Lifetime optimization is one of the key issues among the many challenges of wireless sensor networks. The introduction of a small number of high-performance relay nodes can effectively improve the quality of the network services. However, how to deploy these nodes reasonably to [...] Read more.
Lifetime optimization is one of the key issues among the many challenges of wireless sensor networks. The introduction of a small number of high-performance relay nodes can effectively improve the quality of the network services. However, how to deploy these nodes reasonably to fully enhance the network lifetime becomes a very difficult problem. In this study, a modified and enhanced Artificial Bee Colony is proposed to maximize the lifetime of a two-tiered wireless sensor network by optimal deployment of relay nodes. First, the dimension of the problem is introduced into the candidate search equation and the local search is adjusted according to the fitness of the problem and number of iterations, which helps to balance the exploration and exploitation ability of the algorithm. Second, in order to prevent the algorithm from falling into local convergence, a dynamic search balance strategy is proposed instead of the scout bee phase in the original Artificial Bee Colony. Then, a feasible solution formation method is proposed to ensure that the relay nodes can form the upper-layer backbone of the network. Finally, we employ this algorithm on a test dataset obtained from the literature. The simulation results show that the proposed algorithm for two-tiered wireless sensor network lifetime optimization can obtain higher and stable average network lifetime and more reasonable relay node deployment compared to other classical and state-of-the-art algorithms, verifying the competitive performance of the proposed algorithm. Full article
(This article belongs to the Special Issue Wireless Sensor Networks and Communications)
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22 pages, 2099 KiB  
Article
The RapidIO Routing Strategy Based on the Double-Antibody Group Multi-Objective Artificial Immunity Algorithm
by Yanming Fu, Youquan Jia, Baohua Huang, Xing Zhou and Xiaoqiong Qin
Sensors 2022, 22(3), 914; https://0-doi-org.brum.beds.ac.uk/10.3390/s22030914 - 25 Jan 2022
Viewed by 2149
Abstract
The RapidIO standard is a packet-switching interconnection technology similar to the Internet Protocol (IP) conceptually. It realizes the high-speed transmission of RapidIO packets at the transport layer, but this greatly increases the probability of network blocking. Therefore, it is of great significance to [...] Read more.
The RapidIO standard is a packet-switching interconnection technology similar to the Internet Protocol (IP) conceptually. It realizes the high-speed transmission of RapidIO packets at the transport layer, but this greatly increases the probability of network blocking. Therefore, it is of great significance to optimize the RapidIO routing strategy. For this problem, this paper proposes a Double-Antibody Group Multi-Objective Artificial Immune Algorithm (DAG-MOAIA), which improves the local search and global search ability of the population by adaptive crossover and adaptive mutation of the double-antibody groups, and uses co-competition of multi-antibody groups to increase the diversity of population. Through DAG-MOAIA, an optimal transmission path from the source node to multiple destination nodes can be selected to solve the Quality Of Service (QoS) problem during data transmission and ensure the QoS of the RapidIO network. Simulation results show that DAG-MOAIA could obtain high-quality solutions to select better routing transmission paths, and exhibit better comprehensive performance in all simulated test networks, which plays a certain role in solving the problem of the RapidIO routing strategy. Full article
(This article belongs to the Special Issue Wireless Sensor Networks and Communications)
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13 pages, 2882 KiB  
Communication
An Efficient Turbo Decoding and Frequency Domain Turbo Equalization for LTE Based Narrowband Internet of Things (NB-IoT) Systems
by Mohammed Jajere Adamu, Li Qiang, Rabiu Sale Zakariyya, Charles Okanda Nyatega, Halima Bello Kawuwa and Ayesha Younis
Sensors 2021, 21(16), 5351; https://0-doi-org.brum.beds.ac.uk/10.3390/s21165351 - 08 Aug 2021
Cited by 7 | Viewed by 2312
Abstract
This paper addresses the main crucial aspects of physical (PHY) layer channel coding in uplink NB-IoT systems. In uplink NB-IoT systems, various channel coding algorithms are deployed due to the nature of the adopted Long-Term Evolution (LTE) channel coding which presents a great [...] Read more.
This paper addresses the main crucial aspects of physical (PHY) layer channel coding in uplink NB-IoT systems. In uplink NB-IoT systems, various channel coding algorithms are deployed due to the nature of the adopted Long-Term Evolution (LTE) channel coding which presents a great challenge at the expense of high decoding complexity, power consumption, error floor phenomena, while experiencing performance degradation for short block lengths. For this reason, such a design considerably increases the overall system complexity, which is difficult to implement. Therefore, the existing LTE turbo codes are not recommended in NB-IoT systems and, hence, new channel coding algorithms need to be employed for LPWA specifications. First, LTE-based turbo decoding and frequency-domain turbo equalization algorithms are proposed, modifying the simplified maximum a posteriori probability (MAP) decoder and minimum mean square error (MMSE) Turbo equalization algorithms were appended to different Narrowband Physical Uplink Shared Channel (NPUSCH) subcarriers for interference cancellation. These proposed methods aim to minimize the complexity of realizing the traditional MAP turbo decoder and MMSE estimators in the newly NB-IoT PHY layer features. We compare the system performance in terms of block error rate (BLER) and computational complexity. Full article
(This article belongs to the Special Issue Wireless Sensor Networks and Communications)
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