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Recent Advances in Next Generation Wireless Sensor and Mesh Networks

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

Deadline for manuscript submissions: closed (31 October 2022) | Viewed by 19859

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Prof. Dr. Leonard Barolli

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Department of Information and Communication Engineering, Faculty of Information Engineering, Fukuoka Institute of Technology (FIT), 3-30-1 Wajiro-Higashi, Higashi-Ku, Fukuoka 811-0295, Japan
Interests: high-speed networks; mobile communication systems; ad hoc networking; sensor networks; P2P systems; quality of service (QoS); traffic control mechanisms (policing, routing, congestion control, connection admission control (CAC)); intelligent algorithms (fuzzy theory, genetic algorithms, neural networks); network protocols; agent-based systems; grid and Internet computing; cybersecurity
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Special Issue Information

Dear Colleagues,

Networks of today are going through a rapid evolution. Different kinds of wireless networks with different characteristics are emerging, and they are being integrated into heterogeneous networks. For these reasons, there are many interconnection problems that may occur at different levels in the hardware and software design of communicating entities and communication networks. These kinds of networks need to manage an increasing usage demand, provide support for a significant number of services, guarantee their QoS, and optimize the utilization of network resources. Therefore, architectures and algorithms in these networks become very complex, and it seems imperative to focus on new models, methods and mechanisms that can enable the network to perform adaptive behaviors. The next generation of wireless and mobile networks will allow mobile users to access heterogeneous wireless and mobile networks. The internetworking of different types of wireless and mobile networks aims to provide seamless services for mobile users among different types of networks. Due to the heterogeneity of different radio access techniques, different types of traffic and applications, the QoS guarantee becomes a critical issue for an integrated wireless and mobile network.

This Special Issue is devoted to the advances in Next Generation Wireless and Mobile Networks and their architectures, protocols, resource management, mobility management and scheduling. Topics of interest include, but are not limited to:

Architecture of Integrated Heterogamous Wireless and Mobile Networks;
Handoff and Mobility Management;
Integration of Heterogeneous Wireless and Mobile Networks;
Resource Management;
Multi-interface Access Protocols;
QoS Provisioning;
Cross-layer Design and Optimization;
Load Balancing and Scheduling;
Routing Protocols;
Security and Privacy;
Opportunistic Networks;
Vehicular Networks;
Sensor and Actor Networks;
Wireless Mesh Networks;
Flying Networks;
Beyond 5G Technology;
IoT Platforms and Applications;
Protocols and Architectures for Next-Generation Networks;
Personal Communication Systems;
Low-power Networks and Systems;
Wearable Networks and Systems;
Ubiquitous/Pervasive Networks and Computing.

Prof. Dr. Leonard Barolli
Guest Editor

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Published Papers (10 papers)

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Research

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24 pages, 2136 KiB

Open AccessArticle

TriNymAuth: Triple Pseudonym Authentication Scheme for VANETs Based on Cuckoo Filter and Paillier Homomorphic Encryption

by Luyuan Zhuang, Nan Guo and Yufan Chen

Sensors 2023, 23(3), 1164; https://doi.org/10.3390/s23031164 - 19 Jan 2023

Cited by 1 | Viewed by 1333

Abstract

In VANETs, owing to the openness of wireless communication, it is necessary to change pseudonyms frequently to realize the unlinkability of vehicle identity. Moreover, identity authentication is needed, which is usually completed by digital certificates or a trusted third party. The storage and the communication overhead are high. This paper proposes a triple pseudonym authentication scheme for VANETs based on the Cuckoo Filter and Paillier homomorphic encryption (called TriNymAuth). TriNymAuth applies Paillier homomorphic encryption, a Cuckoo Filter combining filter-level and bucket-level, and a triple pseudonym (homomorphic pseudonym, local pseudonym, and virtual pseudonym) authentication to the vehicle identity authentication scheme. It reduces the dependence on a trusted third party and ensures the privacy and security of vehicle identity while improving authentication efficiency. Experimental results show that the insert overhead of the Cuckoo Filter is about 10

μ

s, and the query overhead reaches the ns level. Furthermore, TriNymAuth has significant cost advantages, with an OBU enrollment cost of only 0.884 ms. When the data rate in VANETs

d r \leq

180 kbps, TriNymAuth has the smallest total transmission delay cost and is suitable for shopping malls and other places with dense traffic. Full article

(This article belongs to the Special Issue Recent Advances in Next Generation Wireless Sensor and Mesh Networks)

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14 pages, 5604 KiB

Open AccessArticle

A Delaunay Edges and Simulated Annealing-Based Integrated Approach for Mesh Router Placement Optimization in Wireless Mesh Networks

by Tetsuya Oda

Sensors 2023, 23(3), 1050; https://doi.org/10.3390/s23031050 - 17 Jan 2023

Cited by 4 | Viewed by 1320

Abstract

Wireless Mesh Networks (WMNs) can build a communications infrastructure using only routers (called mesh routers), making it possible to form networks over a wide area at low cost. The mesh routers cover clients (called mesh clients), allowing mesh clients to communicate with different nodes. Since the communication performance of WMNs is affected by the position of mesh routers, the communication performance can be improved by optimizing the mesh router placement. In this paper, we present a Coverage Construction Method (CCM) that optimizes mesh router placement. In addition, we propose an integrated optimization approach that combine Simulated Annealing (SA) and Delaunay Edges (DE) in CCM to improve the performance of mesh router placement optimization. The proposed approach can build and provide a communication infrastructure by WMNs in disaster environments. We consider a real scenario for the placement of mesh clients in an evacuation area of Kurashiki City, Japan. From the simulation results, we found that the proposed approach can optimize the placement of mesh routers in order to cover all mesh clients in the evacuation area. Additionally, the DECCM-based SA approach covers more mesh clients than the CCM-based SA approach on average and can improve network connectivity of WMNs. Full article

(This article belongs to the Special Issue Recent Advances in Next Generation Wireless Sensor and Mesh Networks)

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25 pages, 2276 KiB

Open AccessArticle

Optimization of Vehicular Networks in Smart Cities: From Agile Optimization to Learnheuristics and Simheuristics

by Mohammad Peyman, Tristan Fluechter, Javier Panadero, Carles Serrat, Fatos Xhafa and Angel A. Juan

Sensors 2023, 23(1), 499; https://doi.org/10.3390/s23010499 - 2 Jan 2023

Cited by 5 | Viewed by 3212

Abstract

Vehicular ad hoc networks (VANETs) are a fundamental component of intelligent transportation systems in smart cities. With the support of open and real-time data, these networks of inter-connected vehicles constitute an ‘Internet of vehicles’ with the potential to significantly enhance citizens’ mobility and last-mile delivery in urban, peri-urban, and metropolitan areas. However, the proper coordination and logistics of VANETs raise a number of optimization challenges that need to be solved. After reviewing the state of the art on the concepts of VANET optimization and open data in smart cities, this paper discusses some of the most relevant optimization challenges in this area. Since most of the optimization problems are related to the need for real-time solutions or to the consideration of uncertainty and dynamic environments, the paper also discusses how some VANET challenges can be addressed with the use of agile optimization algorithms and the combination of metaheuristics with simulation and machine learning methods. The paper also offers a numerical analysis that measures the impact of using these optimization techniques in some related problems. Our numerical analysis, based on real data from Open Data Barcelona, demonstrates that the constructive heuristic outperforms the random scenario in the CDP combined with vehicular networks, resulting in maximizing the minimum distance between facilities while meeting capacity requirements with the fewest facilities. Full article

(This article belongs to the Special Issue Recent Advances in Next Generation Wireless Sensor and Mesh Networks)

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18 pages, 1250 KiB

Open AccessArticle

Trustability for Resilient Internet of Things Services on 5G Multiple Access Edge Cloud Computing

by Suleyman Uslu, Davinder Kaur, Mimoza Durresi and Arjan Durresi

Sensors 2022, 22(24), 9905; https://doi.org/10.3390/s22249905 - 16 Dec 2022

Cited by 7 | Viewed by 1580

Abstract

Billions of Internet of Things (IoT) devices and sensors are expected to be supported by fifth-generation (5G) wireless cellular networks. This highly connected structure is predicted to attract different and unseen types of attacks on devices, sensors, and networks that require advanced mitigation strategies and the active monitoring of the system components. Therefore, a paradigm shift is needed, from traditional prevention and detection approaches toward resilience. This study proposes a trust-based defense framework to ensure resilient IoT services on 5G multi-access edge computing (MEC) systems. This defense framework is based on the trustability metric, which is an extension of the concept of reliability and measures how much a system can be trusted to keep a given level of performance under a specific successful attack vector. Furthermore, trustability is used as a trade-off with system cost to measure the net utility of the system. Systems using multiple sensors with different levels of redundancy were tested, and the framework was shown to measure the trustability of the entire system. Furthermore, different types of attacks were simulated on an edge cloud with multiple nodes, and the trustability was compared to the capabilities of dynamic node addition for the redundancy and removal of untrusted nodes. Finally, the defense framework measured the net utility of the service, comparing the two types of edge clouds with and without the node deactivation capability. Overall, the proposed defense framework based on trustability ensures a satisfactory level of resilience for IoT on 5G MEC systems, which serves as a trade-off with an accepted cost of redundant resources under various attacks. Full article

(This article belongs to the Special Issue Recent Advances in Next Generation Wireless Sensor and Mesh Networks)

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14 pages, 4079 KiB

Open AccessArticle

Fairness-Based Multi-AP Coordination Using Federated Learning in Wi-Fi 7

by Gimoon Woo, Hyungbin Kim, Seunghyun Park, Cheolwoo You and Hyunhee Park

Sensors 2022, 22(24), 9776; https://doi.org/10.3390/s22249776 - 13 Dec 2022

Cited by 1 | Viewed by 1777

Abstract

Federated learning is a type of distributed machine learning in which models learn by using large-scale decentralized data between servers and devices. In a short-range wireless communication environment, it can be difficult to apply federated learning because the number of devices in one access point (AP) is small, which can be small enough to perform federated learning. Therefore, it means that the minimum number of devices required to perform federated learning cannot be matched by the devices included in one AP environment. To do this, we propose to obtain a uniform global model regardless of data distribution by considering the multi-AP coordination characteristics of IEEE 802.11be in a decentralized federated learning environment. The proposed method can solve the imbalance in data transmission due to the non-independent and identically distributed (non-IID) environment in a decentralized federated learning environment. In addition, we can also ensure the fairness of multi-APs and determine the update criteria for newly elected primary-APs by considering the learning training time of multi-APs and energy consumption of grouped devices performing federated learning. Thus, our proposed method can determine the primary-AP according to the number of devices participating in the federated learning in each AP during the initial federated learning to consider the communication efficiency. After the initial federated learning, fairness can be guaranteed by determining the primary-AP through the training time of each AP. As a result of performing decentralized federated learning using the MNIST and FMNIST dataset, the proposed method showed up to a 97.6% prediction accuracy. In other words, it can be seen that, even in a non-IID multi-AP environment, the update of the global model for federated learning is performed fairly. Full article

(This article belongs to the Special Issue Recent Advances in Next Generation Wireless Sensor and Mesh Networks)

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27 pages, 7305 KiB

Open AccessArticle

A Software-Defined Directional Q-Learning Grid-Based Routing Platform and Its Two-Hop Trajectory-Based Routing Algorithm for Vehicular Ad Hoc Networks

by Chen-Pin Yang, Chin-En Yen and Ing-Chau Chang

Sensors 2022, 22(21), 8222; https://doi.org/10.3390/s22218222 - 27 Oct 2022

Cited by 4 | Viewed by 1827

Abstract

Dealing with the packet-routing problem is challenging in the V2X (Vehicle-to-Everything) network environment, where it suffers from the high mobility of vehicles and varied vehicle density at different times. Many related studies have been proposed to apply artificial intelligence models, such as Q-learning, which is a well-known reinforcement learning model, to analyze the historical trajectory data of vehicles and to further design an efficient packet-routing algorithm for V2X. In order to reduce the number of Q-tables generated by Q-learning, grid-based routing algorithms such as the QGrid have been proposed accordingly to divide the entire network environment into equal grids. This paper focuses on improving the defects of these grid-based routing algorithms, which only consider the vehicle density of each grid in Q-learning. Hence, we propose a Software-Defined Directional QGrid (SD-QGrid) routing platform in this paper. By deploying an SDN Control Node (CN) to perform centralized control for V2X, the SD-QGrid considers the directionality from the source to the destination, real-time positions and historical trajectory records between the adjacent grids of all vehicles. The SD-QGrid further proposes the flows of the offline Q-learning training process and the online routing decision process. The two-hop trajectory-based routing (THTR) algorithm, which depends on the source–destination directionality and the movement direction of the vehicle for the next two grids, is proposed as a vehicle node to forward its packets to the best next-hop neighbor node in real time. Finally, we use the real vehicle trajectory data of Taipei City to conduct extensive simulation experiments with respect to four transmission parameters. The simulation results prove that the SD-QGrid achieved an over 10% improvement in the average packet delivery ratio and an over 25% reduction in the average end-to-end delay at the cost of less than 2% in average overhead, compared with two well-known Q-learning grid-based routing algorithms. Full article

(This article belongs to the Special Issue Recent Advances in Next Generation Wireless Sensor and Mesh Networks)

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12 pages, 630 KiB

Open AccessArticle

A Hybrid Intelligent Simulation System for Building IoT Networks: Performance Comparison of Different Router Replacement Methods for WMNs Considering Stadium Distribution of IoT Devices

by Admir Barolli, Shinji Sakamoto, Kevin Bylykbashi and Leonard Barolli

Sensors 2022, 22(20), 7727; https://doi.org/10.3390/s22207727 - 12 Oct 2022

Cited by 1 | Viewed by 1175

Abstract

As the Internet of Things (IoT) devices and applications proliferate, it becomes increasingly important to design robust networks that can continue to meet user demands at a high level. Wireless local area networks (WLANs) can be a good choice as IoT infrastructure when high throughput is required. On the other hand, wireless mesh networks (WMNs), which are WLANs with mesh topology following the IEEE802.11s standard, have many advantages compared to conventional WLANs. Nevertheless, there are some problems that need solutions. One of them is the node placement problem. In this work, we propose and implement a hybrid intelligent system that solves this problem by determining the position of mesh nodes by maximizing the mesh connectivity and the coverage of IoT devices. The system is based on particle swarm optimization (PSO), simulated annealing (SA), and distributed genetic algorithm (DGA). We compare the performance of three router replacement methods: constriction method (CM), random inertia weight method (RIWM), and rational decrement of Vmax method (RDVM). The simulation results show that RIWM achieves better performance compared to CM and RDVM because it achieves the highest connectivity while covering more clients than the other two methods. Full article

(This article belongs to the Special Issue Recent Advances in Next Generation Wireless Sensor and Mesh Networks)

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25 pages, 2674 KiB

Open AccessArticle

Reconfigurable Intelligent Surface-Aided Cooperative NOMA with p-CSI Fading Channel toward 6G-Based IoT System

by Hsing-Chung Chen, Agung Mulyo Widodo, Jerry Chun-Wei Lin and Chien-Erh Weng

Sensors 2022, 22(19), 7664; https://doi.org/10.3390/s22197664 - 9 Oct 2022

Cited by 4 | Viewed by 1639

Abstract

Addressing the challenges of internet-based 5G technology, namely increasing density through micro-cell systems, frequency spectrum, and reducing resource costs, is needed to meet the use of IoT-based 6G technology with the goal of high-speed, high-capacity, and low-latency communication. In this research, we considered the coverage performance and ergodic capacity of the Reconfigurable Intelligent Surface (RIS)-aided cooperative nonorthogonal multiple-access network (NOMA) of an IoT system. This enables the upgrading of 5G- toward 6G-technology-based IoT systems. We developed a closest-form formula of near and far user coverage probabilities as a function of perfect channel statistical information (p-CSI) using only a single-input single-output (SISO) system with a finite number of RIS elements under the Nakagami-m fading channel. We also define ergodic capacity as a simple upper limit by simplifying the use of symbolic functions and it could be used for a sustained period. The simulation findings suggest that RIS-assisted NOMA has a reduced risk of outage than standard NOMA. All of the derived closed-form formulas agree with Monte Carlo simulations, indicating that the distant user’s coverage probability outperforms the nearby user. The bigger the number of RIS parts, however, the greater the chance of coverage. They also disclose the scaling law of the number of phase shifts at the RIS-aided NOMA based on the asymptotic analysis and the upper bound on channel capacity. In both arbitrary and optimum phase shifts, the distant user’s ergodic capacity outperforms the near user. Full article

(This article belongs to the Special Issue Recent Advances in Next Generation Wireless Sensor and Mesh Networks)

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29 pages, 1033 KiB

Open AccessArticle

PINE: Post-Quantum Based Incentive Technique for Non-Cooperating Nodes in Internet of Everything

by Ashwin Balaji, Sanjay Kumar Dhurandher and Isaac Woungang

Sensors 2022, 22(18), 6928; https://doi.org/10.3390/s22186928 - 13 Sep 2022

Cited by 2 | Viewed by 2059

Abstract

The Internet of Everything (IoE) is a smart system that interconnects smart entities by incorporating low-cost or low-energy gadgets that are useful for communication with people, processes, data, and devices/things. In such an instantaneously connected environment, network-enabled heterogeneous devices may exhibit non-cooperative behaviour which may lead to the degradation of the network. To address this performance degradation, the proposed Post-quantum based Incentive technique for Non-cooperating nodes in internet of Everything (PINE) protocol provides an end-to-end reliable solution by incorporating location-aware post-quantum encryption in these networks while addressing the non-cooperative behaviour of the nodes by employing an effective strategy in a bi-directional multi-hop relay environment. This proposed protocol further aims to evaluate the consequences of non-cooperative nodes by considering various metrics, namely, number of nodes, message size, execution time, memory consumption, average residual energy, percentage of selfish nodes, and blackhole nodes detection, aiming to achieve significant accuracy in an IoE environment. Full article

(This article belongs to the Special Issue Recent Advances in Next Generation Wireless Sensor and Mesh Networks)

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Review

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30 pages, 1731 KiB

Open AccessReview

Resource Management for Massive Internet of Things in IEEE 802.11ah WLAN: Potentials, Current Solutions, and Open Challenges

by Arshad Farhad and Jae-Young Pyun

Sensors 2022, 22(23), 9509; https://doi.org/10.3390/s22239509 - 5 Dec 2022

Cited by 7 | Viewed by 3058

Abstract

IEEE 802.11ah, known as Wi-Fi HaLow, is envisioned for long-range and low-power communication. It is sub-1 GHz technology designed for massive Internet of Things (IoT) and machine-to-machine devices. It aims to overcome the IoT challenges, such as providing connectivity to massive power-constrained devices distributed over a large geographical area. To accomplish this objective, IEEE 802.11ah introduces several unique physical and medium access control layer (MAC) features. In recent years, the MAC features of IEEE 802.11ah, including restricted access window, authentication (e.g., centralized and distributed) and association, relay and sectorization, target wake-up time, and traffic indication map, have been intensively investigated from various aspects to improve resource allocation and enhance the network performance in terms of device association time, throughput, delay, and energy consumption. This survey paper presents an in-depth assessment and analysis of these MAC features along with current solutions, their potentials, and key challenges, exposing how to use these novel features to meet the rigorous IoT standards. Full article

(This article belongs to the Special Issue Recent Advances in Next Generation Wireless Sensor and Mesh Networks)

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