Special issue | Dependable Wireless Communications: Applications and Practices

Vol. 76, n° 5-6, May-June 2021
Content available on Springerlink

Guest editors

Muhammad Alam, School of Engineering, London South Bank University, London, UK and Instituto de Telecomunicações, Universidade de Aveiro, Aveiro, Portugal
Nadjib Ait Saadi, UVSQ Paris-Saclay University, Paris, France
Mian Ahmad Jan, Abdul Wali Khan University Mardan, Mardan, Pakistan
Xiaohua Xu, Department of Computer Science, Kennesaw State University, Kennesaw, GA, USA


Dependable wireless communications: applications and practices

Muhammad Alam · Nadjib Ait Saadi · Mian Ahmad Jan · Xiaohua Xu

The robust deep learning–based schemes for intrusion detection in Internet of Things environments

Xingbing Fu1,2 · Nan Zhou1 · Libin Jiao2 · Haifeng Li3 · Jianwu Zhang4

(1) School of Cyberspace, Hangzhou Dianzi University, Hangzhou, People’s Republic of China
(2) Science and Technology on Communication Networks Laboratory, Shijiazhuang,
People’s Republic of China
(3) School of Software, Dalian University of Technology, Dalian, People’s Republic of China
(4) School of Communication Engineering, Hangzhou Dianzi University, Hangzhou,
People’s Republic of China

Abstract With the advent of the Internet of Things (IoT), network attacks have become more diverse and intelligent. In order to ensure the security of the network, Intrusion Detection system (IDS) has become very important. However, when met with the adversarial examples, IDS has itself become no longer secure, and the attackers can increase the success rate of attacks by misleading IDS. Therefore, it is necessary to improve the robustness of the IDS. In this paper, we employ Fast Gradient Sign Method (FGSM) to generate adversarial examples to test the robustness of three intrusion detection models based on convolutional neural network (CNN), long short-term memory (LSTM), and gated recurrent unit (GRU). We employ three training methods: the first is to train the models with normal examples, the second is to train the models directly with adversarial examples, and the last is to pretrain the models with normal examples, and then employ adversarial examples to train the models. We evaluate the performance of the three models under different training methods, and find that under normal training method, CNN is the most robust model to adversarial examples. After adversarial training, the robustness of GRU and LSTM to adversarial examples has greatly been improved.

Keywords Adversarial examples · Adversary training · CNN · FGSM · LSTM · GRU

Design of a portable and multifunctional dependable wireless communication platform for smart health care

Muhammad Bilal Khan1 · Chunxi Dong1 · Mohammed Ali Mohammed Al-Hababi1 · Xiaodong Yang1

(1) School of Electronic Engineering, Xidian University, Xi’an, Shaanxi, China

Abstract The future of dependable wireless communication will encompass a much eclectic range of applications. Not only are traditional telecommunication facilities such as text messaging, audio and video calling, video download and upload, web browsing, and social networking being improved but also a wide range of sensors and devices in the “Internet of things,” such as “smart cities” and smart hospital applications are being adopted. Researchers are trying hard to ensure timely detection of various diseases anytime and anywhere. In this research, a portable and multifunctional software-defined radio (SDR) platform is designed to detect different activities of human life, in particular for the monitoring of health. The wireless channel state information (WCSI) in the presence of the human body is investigated to capture movements using different frequency bands and is the key idea of this work. Orthogonal frequency division multiplexing (OFDM) with 64 subcarriers and the magnitude and phase responses in the frequency domain are used to capture the WCSI of the activity. The design is validated through simulation and real-time experiments. However, it is widely accepted that simulation results fail to capture real-life situations. Extensive and repeated real-time experiments are carried out on the hardware platform to ensure that the activity is detected accurately. The results achieved by detecting hand motion activity ensure that the system is capable of detecting human body motions and vital signs.

Keywords OFDM . SDR . USRP .WCSI

A single-player Monte Carlo tree search method combined with node importance for virtual network embedding

Guangcong Zheng1 · Cong Wang1 · Weijie Shao1 · Ying Yuan1 · Zejie Tian1 · Sancheng Peng2 · Ali Kashif Bashir3,4 · Shahid Mumtaz5

(1) School of Computer and Communication Engineering, Northeastern University at Qinhuangdao, Qinhuangdao, Hebei, China
(2) Laboratory of Language Engineering and Computing, Guangdong University of Foreign Studies, Guangzhou, China
(3) Department of Computing and Mathematics, Manchester Metropolitan University, Manchester, UK
(4) School of Electrical Engineering and Computer Science, National University of Science and Technology, Islamabad, (NUST), Pakistan
(5) Instituto de Telecomunicações, Campus Universitário de Santiago, Aveiro, Portugal

Abstract As a critical technology in network virtualization, virtual network embedding (VNE) focuses on how to allocate physical resources to virtual network requests efficiently. Because the VNE problem is NP-hard, most of the existing approaches are heuristic-based algorithms that tend to converge to a local optimal solution and have a low performance. In this paper, we propose an algorithm that combines the basic Monte Carlo tree search (MCTS) method with node importance to apply domain-specific knowledge. For a virtual network request, we first model the embedding process as a finite Markov decision process (MDP), where each virtual node is embedded in one state in the order of node importance that we design. The shortest-path algorithm is then applied to embed links in the terminal state and return the cost as a part of the reward. Due to the reward delay mechanism of the MDP, the result of link mapping can affect the action selected in the previous node mapping stage, coordinating the two embedding stages. With node importance, domain-specific knowledge can be used in the Expansion and Simulation stages of MCTS to speed up the search and estimate the simulation value more accurately. The experimental results show that, compared with the existing classic algorithms, our proposed algorithm can improve the performance of VNE in terms of the average physical node utilization ratio, acceptance ratio, and long-term revenue to cost ratio.

Keywords Network virtualization · Virtual network embedding · Reinforcement learning · Markov decision process · Monte Carlo tree search · Node ranking

The identity authentication of Wi-Fi system based on network security

Hao Tao1

(1) Information Construction Center, Jiangsu Vocational College of Information Technology, Wuxi, Jiangsu, China

Abstract With the wide distribution of hot spots, in order to facilitate users to access the network at anytime and anywhere, the current network technology has developed a convenient and fast hot spot sharing system and has been popularized in daily life. However, the convenience of the information society also hides network security dangers. The purpose of this paper is to study and analyze the security problems existing in current Wi-Fi sharing applications by designing two different network authentication programs. In this paper, ieeee802.1x protocol is used for wireless access, eap-tls and RADIUS bidirectional authentication mechanism to achieve the authentication of access users, and one-time password authentication technology is used in Fat AP networking mode. Aiming at the defects of S/KEY protocol, such as server impersonation and system crash, an authentication scheme combining DES and RSA algorithm is proposed and implemented. The authentication scheme in network mode retains the advantage of simple operation of static cryptography system. By adding uncertainties, the security of the authentication system can be improved. The encrypted information is used to encrypt the transmitted information to ensure the confidentiality of the information during transmission. After successful authentication, session key negotiation is completed to ensure the security of subsequent communication. This scheme has a success rate of more than 95% after the experiment, is simple in design, high in security, low in cost, and does not need the participation of the third party, which is very suitable for solving the problems of user authentication and communication confidentiality in the shared system.

Keywords Shared system . Identity authentication . One-time password protocol . Network security

An energy-efficient data aggregation approach for cluster-based wireless sensor networks

Syed Rooh Ullah Jan1 · Rahim Khan1 · Mian Ahmad Jan1

(1) Department of Computer Science, Abdul Wali Khan University, Mardan, KPK, Pakistan

Abstract In wireless sensor networks (WSNs), data redundancy is a challenging issue that not only introduces network congestion but also consumes considerable sensor node resources. Data redundancy occurs due to the spatial and temporal correlations among the data gathered by the neighboring nodes. Data aggregation is a prominent technique that performs in-network filtering of the redundant data and accelerates knowledge extraction by eliminating the correlated data. However, most data aggregation techniques have low accuracy because they do not consider the presence of erroneous data from faulty nodes, which represents an open research challenge. To address this challenge, we have proposed a novel, lightweight, and energy-efficient function-based data aggregation approach for a cluster-based hierarchical WSN. Our proposed approach works at two levels: the node level and the cluster head level. At the node level, the data aggregation is performed using the exponential moving average (EMA), and a threshold-based mechanism is adopted to detect any outliers to improve the accuracy of data aggregation. At the cluster head level, we have employed a modified version of the Euclidean distance function to provide highly refined aggregated data to the base station. Our experimental results show that our approach reduces the communication cost, transmission cost, and energy consumption at the nodes and cluster heads and delivers highly refined, fused data to the base station.

Keywords Wireless sensor network · Data aggregation · Energy efficiency · Accuracy · Outlier detection

SOSW: scalable and optimal nearsighted location selection for fog node deployment and routing in SDN-based wireless networks for IoT systems

Muhammad Ibrar1 · Lei Wang1,2,3 · Gabriel-Miro Muntean4 · Nadir Shah5 · Aamir Akbar6 · Khalid Ibrahim Qureshi1

(1) School of Software, Dalian University of Technology, Dalian, China
(2) Key Lab of Ubiquitous Network and Service Software of Liaoning Province, Shenzhen, China
(3) Peng Cheng Laboratory, Shenzhen, China
(4) School of Electronic Engineering, Dublin City University, Dublin, Ireland
(5) Department of Computer Science, COMSATS University Islamabad, Wah Campus, Islamabad, Pakistan
(6) Department of Computer Science, Abdul Wali Khan University Mardan (AWKUM), Mardan, Pakistan

Abstract In a fog computing (FC) architecture, cloud services migrate towards the network edge and operate via edge devices such as access points (AP), routers, and switches. These devices become part of a virtualization infrastructure and are referred to as “fog nodes.” Recently, software-defined networking (SDN) has been used in FC to improve its control and manageability. The current SDN-based FC literature has overlooked two issues: (a) fog nodes’ deployment at optimal locations and (b) SDN best path computation for data flows based on constraints (i.e., end-to-end delay and link utilization). To solve these optimization problems, this paper suggests a novel approach, called scalable and optimal near-sighted location selection for fog node deployment and routing in SDN-based wireless networks for IoT systems (SOSW). First, the SOSW model uses singular-value decomposition (SVD) and QR factorization with column pivoting linear algebra methods on the traffic matrix of the network to compute the optimal locations for fog nodes, and second, it introduces a new heuristic-based traffic engineering algorithm, called the constraint-based shortest path algorithm (CSPA), which uses ant colony optimization (ACO) to optimize the path computation process for task offloading. The results show that our proposed approach significantly reduces average latency and energy consumption in comparison with existing approaches.

Keywords Wireless network · IoT · Fog computing · SDN · Optimization

An enhanced energy optimization routing protocol for WSNs

Xiaojun Ren1 · Jiaqing Li2 · Yongtang Wu1 · Yuanfang Chen3 · Hongwei Sun1 ·
Zhichen Shi4

(1) Blockchain Laboratory of Agricultural Vegetables, Weifang University of Science and Technology, Weifang, Shandong, China
(2) School of Mechanical, Electrical, Information Engineering, Shandong University, Weihai, Shandong, China
(3) School of Cyberspace, Hangzhou Dianzi University, Hangzhou, Zhejiang, China
(4) Network Infomation Center, Weifang University, Weifang, Shandong, China

Abstract Wireless sensor networks (WSNs) have received increasing attention due to their broad application prospects. However, the nature of sensor nodes, i.e., limited battery life and inefficient protocols, greatly reduces the sensor networks’ lifetime. Therefore, determining how to extend their lifetime has become an important issue for WSNs. This paper focuses on the technique of extending the networks’ lifetime by reducing and balancing energy consumption and proposes an enhanced energy optimization routing protocol (EEORP) for WSNs. EEORP proposes a grid-based cluster head (CH) election algorithm and introduces the energy weight and declaration number order weight factors to reduce the energy consumption in the rotation of CHs. EEORP adopts the dynamic clustering algorithm to reduce the energy consumption in intra-cluster data collection. The hop-count gradient field and grid distance are also introduced in EEORP to minimize the energy consumption in inter-cluster forwarding of the data. Our proposed protocol (EEORP) shows better performance than the existing protocols (LEACH, IEE-LEACH and EAMR) in terms of the networks’ lifetime and data throughput in WSNs, as has been demonstrated experimentally.

Keywords Wireless sensor networks · Clustering · Cluster head · Gradient methods · Energy efficiency · Network lifetime

Outage probability of MIMO cognitive radio networks with energy harvesting and adaptive transmit power

Nadhir Ben Halima1 · Hatem Boujemâa2

(1) Higher College of Technology, Sharjah Women College, Sharjah, United Arab Emirates
(2) COSIM Laboratory, SUPCOM, Ariana, Tunisia

Abstract This paper derives the outage probability of cognitive radio networks (CRNs) with energy harvesting (EH). The primary nodes have a single antenna, whereas the secondary nodes have multiple antennas. A secondary source S harvests energy from radiofrequency (RF) signal received from primary transmitter PT using nr, S antennas. S also adapts its power so that the interference at primary receiver PR is less than threshold I. The main contribution of the paper is to derive the throughput of multiple input multiple output (MIMO) CRN with RF energy harvesting and adaptive transmit power. We also optimize the secondary throughput by choosing the optimal harvesting duration.

Keywords CRN · MIMO · Outage probability · Throughput maximization

Performance evaluation of an active signaling based time-slot scheduling scheme for connected vehicles

Fouzi Boukhalfa1 · Mohamed Hadded1 · Paul Muhlethaler2 · Oyunchimeg Shagdar1

(1) Institute VEDECOM, 23 bis allée des Marronniers, Versailles, France
(2) EVA Team, Inria Paris, 2 Rue Simone Iff, Paris, France

Abstract Latency is a very important metric to be taken into account in the design of the Connected and Automated Driving (CAD) technology. Today, connected vehicles have a dedicated technology named vehicle-to-everything (V2X). Many current research efforts and standardization activities aim to make the next generation of V2X technology able to offer new usages and services, with the main focus being on supporting road safety applications: hazard, obstacle and collision avoidance, etc. To satisfy the real-time constraints of safety applications, Time Division Multiple Access (TDMA) is a widely-used technique to control and share the channel. TDMA-based Medium Access Control (MAC) protocols have resolved many issues in VANETs and shown good performances in the literature by ensuring a bounded access delay to send an emergency message. However, latency can be further improved by eradicating some imperfections in the functionality of these protocols, such as the access collision problem which can occur when two or more vehicles in the same two-hop neighborhood set try to access the same slot at the same time. That is why we recently proposed an Active Signaling-based TDMA MAC protocol, called AS-DTMAC, which operates above the existing DTMAC protocol. In this paper, we analytically study the performance of AS-DMTAC when we have a homogeneous arrival on each time slot with an error in the signaling process.

Keywords Connected vehicles · VANETs · MAC · TDMA · Active signaling · Low latency · Next-generation V2X · Analytical modeling

Physical layer security for NOMA: limitations, issues, and recommendations

Reem Melki1 · Hassan N. Noura1 · Ali Chehab1

(1) Department of Electrical and Computer Engineering, American University of Beirut, Beirut, Lebanon

Abstract More and more attention is being directed towards the Non-Orthogonal Multiple Access (NOMA) technology due to its many advantages such as high data rate, enhanced spectral and energy efficiency, massive connectivity, and low latency. On the other hand, secure data transmission remains a critical challenge in wireless communication systems since wireless channels are, in general, exposed. To increase the robustness of NOMA systems and overcome the issues related to wireless transmission, several Physical Layer Security (PLS) schemes have been recently presented. Unlike conventional security algorithms, this type of solutions exploits the dynamicity of the physical layer to secure data using a single iteration and minimum operations. In this paper, we survey the various NOMA-based PLS schemes in the literature, which target all kinds of security properties. From this study, we have noticed that the majority of the research work in this area is mainly focused on data confidentiality and privacy and not on other security properties such as device and source authentication, key generation, and message integrity. Therefore, we discuss the PLS data confidentiality schemes for NOMA and their limitations, challenges, and countermeasures, and we propose different methods to address the remaining security properties.

Keywords NOMA · Physical layer security · MIMO-NOMA · Security properties · Data confidentiality

Energy-efficient cross-layer resource allocation scheme for OFDMA systems

Ayman Khalil1 · Jean-François Hélard1

(1) Institute of Electronics and Telecommunications of Rennes (IETR), European University of Brittany (UEB), INSA, Rennes, France

Abstract Recently, the interest of the telecommunication operators and Internet service providers (ISPs) in energy efficiency (EE) for wireless networks has remarkably increased. The boost in energy prices, the continuous increase of the user numbers, the pervasion of wideband access, and the diffusion of offered services have motivated this interest. The challenge is to minimize the transmitted energy without compromising the quality of service (QoS) and the network performance. In this paper, a new efficient Orthogonal Frequency Division Multiple Access (OFDMA) resource allocation for Long Term Evolution (LTE)-advanced systems based on cross-layer optimization between Physical (PHY) and Medium Access Control (MAC) layers is proposed. A new solution based on Rate Adaptive (RA) principle is presented to achieve better EE resource allocation. The purpose behind the new model is to increase the capacity of the system as much as possible while trying to decrease the total transmit power. Hence, the EE which is equal to the capacity to total transmit power ratio is increased. As reducing the transmit power for the transmission of a given capacity reduces the power consumption, the greenhouse gas (GHG) emission will be then reduced. On the other hand, the service differentiation is highly considered to provide high QoS support. The users are differentiated according to different service classes and different data rates. The proposed cross-layer-based solution has then to allocate the system resources in an optimal way while satisfying the users having high QoS requirements.

Keywords Green communication . Quality of service (QoS) . LTE; OFDMA