Special Issue "Intelligent and Cooperation Communication and Networking Technologies for IoT"

A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Networks".

Deadline for manuscript submissions: 30 November 2019

Special Issue Editors

Guest Editor
Prof. Dr. Ke Xiong

School of Computer and Information Technology, Beijing Jiaotong University, Beijing 100044, China
Website 1 | Website 2 | E-Mail
Interests: IoT, wireless cooperative networks, wireless powered networks, AI-based network optimization and network information theory
Guest Editor
Dr. Waleed Ejaz

Assistant Professor in the Department of Applied Science and Engineering at Thompson Rivers University (TRU), 805 TRU Way, Kamloops, BC V2C 0C8, Canada
Website 1 | Website 2 | E-Mail
Interests: cognitive radios, M2M communication, and next generation wireless networks

Special Issue Information

IoT has great potential to be employed in various fields including industrial controlling; automatic driving; environmental monitoring; and medical protection, which plays a key role in supporting future smart cities. However, designing efficient IoT systems involves may challenges. For example, more and more sensors will be deployed in IoT systems for sensing and information collection, which will generate a huge amount of data. Such data is required to be transferred over IoT and processed as soon as possible for systems to make decisions. However, due to their limited energy and computing capabilities, it is difficult for sensors to fulfill reliable communications and computing. Besides, for large-scale IoT systems, optimally allocating the limited network sources such as time, frequency, power, and routing paths in order to improve system performances is not an easy task. Fortunately, the recent development of communication and networking technologies including energy harvesting, wireless power transfer, fog computing, cooperative communications, user cooperation, convex optimization, and artificial intelligence may provide efficient ways to help solve these problems. Motivated by these observations, this Special Issue aims to capture state-of-the-art advances in intelligent and cooperation communication and networking technologies for IoT and foster new avenues for research in this area. The topics of interest include, but are not limited to, the following:

  1. Energy harvesting-powered IoT;
  2. Fog computing and cloud computing for IoT;
  3. Cooperative communication and routing methods for IoT;
  4. Green IoT system design;
  5. Artificial intelligence-assisted IoT systems;
  6. Resource management in IoT systems;
  7. Self-organization technologies for IoT;
  8. Cognitive techniques for IoT;
  9. New Emerging Applications for IoT.

Dr. Waleed Ejaz
Prof. Dr. Ke Xiong
Guest Editors

Manuscript Submission Information

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Keywords

  • IoT
  • Energy harvesting
  • Fog computing
  • Intelligence
  • Green IoT
  • Resource Management

Published Papers (8 papers)

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Research

Open AccessArticle
Dynamic Network Topology Control of Branch-Trimming Robot for Transmission Lines
Electronics 2019, 8(5), 549; https://doi.org/10.3390/electronics8050549
Received: 13 March 2019 / Revised: 2 May 2019 / Accepted: 9 May 2019 / Published: 15 May 2019
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Abstract
With the development of engineering technology, the distributed design-based Branch-Trimming Robot (BTR) has been used to ensure the power supply security of transmission lines. However, it remains difficult to combine distributed BTRs with a wireless sensor network to build an efficient multi-robot system. [...] Read more.
With the development of engineering technology, the distributed design-based Branch-Trimming Robot (BTR) has been used to ensure the power supply security of transmission lines. However, it remains difficult to combine distributed BTRs with a wireless sensor network to build an efficient multi-robot system. To achieve this combination, a dynamic network topology control method was proposed, combining the motion characteristics of robots with the structure of a distributed wireless sensor network. In addition, a topology-updating mechanism based on node signal strength was adopted as well. To achieve efficient data transmission for distributed multi-robot systems, the present study focused on the design of a distributed network model and a dynamic network topology control strategy. Several simulation and test scenarios were implemented, and the changes of network performance under different parameters were studied. Furthermore, the real scene-based dynamic topology control method considers the relationship between network performance and antenna layout. Full article
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Open AccessArticle
AN-Aided Secure Beamforming in Power-Splitting-Enabled SWIPT MIMO Heterogeneous Wireless Sensor Networks
Electronics 2019, 8(4), 459; https://doi.org/10.3390/electronics8040459
Received: 4 March 2019 / Revised: 8 April 2019 / Accepted: 17 April 2019 / Published: 25 April 2019
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Abstract
In this paper, we investigate the physical layer security in a two-tier heterogeneous wireless sensor network (HWSN) depending on simultaneous wireless information and power transfer (SWIPT) approach for multiuser multiple-input multiple-output wiretap channels with artificial noise (AN) transmission, where a more general system [...] Read more.
In this paper, we investigate the physical layer security in a two-tier heterogeneous wireless sensor network (HWSN) depending on simultaneous wireless information and power transfer (SWIPT) approach for multiuser multiple-input multiple-output wiretap channels with artificial noise (AN) transmission, where a more general system framework of HWSN only includes a macrocell and a femtocell. For the sake of implementing security enhancement and green communications, the joint optimization problem of the secure beamforming vector at the macrocell and femtocell, the AN vector, and the power splitting ratio is modeled to maximize the minimal secrecy capacity of the wiretapped macrocell sensor nodes (M-SNs) while considering the fairness among multiple M-SNs. To reduce the performance loss of the rank relaxation from the SDR technique while solving the non-convex max–min program, we apply successive convex approximation (SCA) technique, first-order Taylor series expansion and sequential parametric convex approximation (SPCA) approach to transform the max–min program to a second order cone programming (SOCP) problem to iterate to a near-optimal solution. In addition, we propose a novel SCA-SPCA-based iterative algorithm while its convergence property is proved. The simulation shows that our SCA-SPCA-based method outperforms the conventional methods. Full article
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Open AccessArticle
Resource Management Based on OCF for Device Self-Registration and Status Detection in IoT Networks
Electronics 2019, 8(3), 311; https://doi.org/10.3390/electronics8030311
Received: 31 December 2018 / Revised: 26 February 2019 / Accepted: 6 March 2019 / Published: 11 March 2019
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Abstract
Recently, there are heterogeneous devices that connect to the Internet to provide ubiquitous and intelligent services based on sensors and actuators in the network of the Internet of Things (IoT). The resources of IoT represent the physical entities on the Internet to expose [...] Read more.
Recently, there are heterogeneous devices that connect to the Internet to provide ubiquitous and intelligent services based on sensors and actuators in the network of the Internet of Things (IoT). The resources of IoT represent the physical entities on the Internet to expose functions through services. Resource management is necessary to enable a massive amount of IoT-connected devices to be discoverable and accessible in the network of IoT. In this paper, we propose an IoT resource management to provide schemes of device self-registration and status detection for devices based on the Open Connectivity Foundation (OCF) standard. This device self-registration scheme is based on an agent that is proposed for registering devices itself which deployed in the OCF network. The devices host the OCF resources to provide IoT services such as sensing and controlling through the sensors and actuators. For a group of devices, an agent-based self-registration is proposed to register the resources. Through the proposed self-registration, the information of IoT devices is published using profile and saved in the management platform that enables the clients to discover the resources and access the services. For accessing the IoT resources in the OCF network, an interworking proxy is proposed to support the communications between web clients and devices over Hypertext Transfer Protocol (HTTP) and Constrained Application Protocol (CoAP) based on OCF. Furthermore, through the interoperability of the resources using the registered information, a real-time monitoring scheme is proposed based on periodic request and response for the status detection of deployed devices. Full article
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Open AccessArticle
Resource Allocation in Wireless-Powered Mobile Edge Computing Systems for Internet of Things Applications
Electronics 2019, 8(2), 206; https://doi.org/10.3390/electronics8020206
Received: 30 December 2018 / Revised: 25 January 2019 / Accepted: 11 February 2019 / Published: 12 February 2019
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Abstract
Wireless devices in Internet of Things (IoT) applications, such as wireless sensors and Radio Frequency Identifications (RFIDs), are faced with challenges of heavy computation tasks and limited energy, which can be solved by the importation of mobile edge computing (MEC) and wireless power [...] Read more.
Wireless devices in Internet of Things (IoT) applications, such as wireless sensors and Radio Frequency Identifications (RFIDs), are faced with challenges of heavy computation tasks and limited energy, which can be solved by the importation of mobile edge computing (MEC) and wireless power transfer (WPT) techniques. As MEC can effectively enhance computation capability, and the wireless power transfer can ensure a sustainable supply of energy, it has drawn significant research interest in IoT applications. In this paper, we will study the resource allocation problem in the wireless-powered MEC system for IoT applications with one access point (AP) and many other wireless devices, and propose a Stackelberg dynamic game model to obtain the optimal allocated resource for the nodes in the IoT environment. The AP is a wireless power source that can charge wireless devices based on wireless power transfer techniques. The AP is also integrated with a MEC server that can carry out computation tasks that offload from wireless devices. The wireless devices can use the harvested energy to execute and offload computation tasks to the AP. Based on the proposed game model, the AP and wireless devices can control their optimal transmit power for energy transfer, and computation tasks offloading to the AP, respectively. The numerical simulation results show the correctness and effectiveness of the proposed model. Full article
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Open AccessArticle
Trajectory Protection Schemes Based on a Gravity Mobility Model in IoT
Electronics 2019, 8(2), 148; https://doi.org/10.3390/electronics8020148
Received: 10 December 2018 / Revised: 24 January 2019 / Accepted: 28 January 2019 / Published: 31 January 2019
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Abstract
With the proliferation of the Internet-of-Things (IoT), the users’ trajectory data containing privacy information in the IoT systems are easily exposed to the adversaries in continuous location-based services (LBSs) and trajectory publication. Existing trajectory protection schemes generate dummy trajectories without considering the user [...] Read more.
With the proliferation of the Internet-of-Things (IoT), the users’ trajectory data containing privacy information in the IoT systems are easily exposed to the adversaries in continuous location-based services (LBSs) and trajectory publication. Existing trajectory protection schemes generate dummy trajectories without considering the user mobility pattern accurately. This would cause that the adversaries can easily exclude the dummy trajectories according to the obtained geographic feature information. In this paper, the continuous location entropy and the trajectory entropy are defined based on the gravity mobility model to measure the level of trajectory protection. Then, two trajectory protection schemes are proposed based on the defined entropy metrics to protect the trajectory data in continuous LBSs and trajectory publication, respectively. Experimental results demonstrate that the proposed schemes have a higher level than the enhanced dummy-location selection (enhance-DLS) scheme and the random scheme. Full article
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Open AccessArticle
Active Eavesdropping Detection Based on Large-Dimensional Random Matrix Theory for Massive MIMO-Enabled IoT
Electronics 2019, 8(2), 146; https://doi.org/10.3390/electronics8020146
Received: 31 December 2018 / Revised: 25 January 2019 / Accepted: 28 January 2019 / Published: 31 January 2019
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Abstract
The increasing Internet-of-Things (IoT) applications will take a significant share of the services of the fifth generation mobile network (5G). However, IoT devices are vulnerable to security threats due to the limitation of their simple hardware and communication protocol. Massive multiple-input multiple-output (massive [...] Read more.
The increasing Internet-of-Things (IoT) applications will take a significant share of the services of the fifth generation mobile network (5G). However, IoT devices are vulnerable to security threats due to the limitation of their simple hardware and communication protocol. Massive multiple-input multiple-output (massive MIMO) is recognized as a promising technique to support massive connections of IoT devices, but it faces potential physical layer breaches. An active eavesdropper can compromises the communication security of massive MIMO systems by purposely contaminating the uplink pilots. According to the random matrix theory (RMT), the eigenvalue distribution of a large dimensional matrix composed of data samples converges to the limit spectrum distribution that can be characterized by matrix dimensions. With the assistance of RMT, we propose an active eavesdropping detection method in this paper. The theoretical limit spectrum distribution is exploited to determine the distribution range of the eigenvalues of a legitimate user signal. In addition the noise components are removed using the Marčenko–Pastur law of RMT. Hypothesis testing is then carried out to determine whether the spread range of eigenvalues is “normal” or not. Simulation results show that, compared with the classical Minimum Description Length (MDL)-based detection algorithm, the proposed method significantly improves active eavesdropping detection performance. Full article
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Open AccessArticle
Adaptive Method for Packet Loss Types in IoT: An Naive Bayes Distinguisher
Electronics 2019, 8(2), 134; https://doi.org/10.3390/electronics8020134
Received: 31 December 2018 / Revised: 21 January 2019 / Accepted: 23 January 2019 / Published: 28 January 2019
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Abstract
With the rapid development of IoT (Internet of Things), massive data is delivered through trillions of interconnected smart devices. The heterogeneous networks trigger frequently the congestion and influence indirectly the application of IoT. The traditional TCP will highly possible to be reformed supporting [...] Read more.
With the rapid development of IoT (Internet of Things), massive data is delivered through trillions of interconnected smart devices. The heterogeneous networks trigger frequently the congestion and influence indirectly the application of IoT. The traditional TCP will highly possible to be reformed supporting the IoT. In this paper, we find the different characteristics of packet loss in hybrid wireless and wired channels, and develop a novel congestion control called NB-TCP (Naive Bayesian) in IoT. NB-TCP constructs a Naive Bayesian distinguisher model, which can capture the packet loss state and effectively classify the packet loss types from the wireless or the wired. More importantly, it cannot cause too much load on the network, but has fast classification speed, high accuracy and stability. Simulation results using NS2 show that NB-TCP achieves up to 0.95 classification accuracy and achieves good throughput, fairness and friendliness in the hybrid network. Full article
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Open AccessArticle
Structure of All-Digital Frequency Synthesiser for IoT and IoV Applications
Electronics 2019, 8(1), 29; https://doi.org/10.3390/electronics8010029
Received: 26 November 2018 / Revised: 14 December 2018 / Accepted: 19 December 2018 / Published: 27 December 2018
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Abstract
In recent years number of Internet of Things (IoT) services and devices is growing and Internet of Vehicles (IoV) technologies are emerging. Multiband transceiver with high performance frequency synthesisers should be used to support a multitude of existing and developing wireless standards. In [...] Read more.
In recent years number of Internet of Things (IoT) services and devices is growing and Internet of Vehicles (IoV) technologies are emerging. Multiband transceiver with high performance frequency synthesisers should be used to support a multitude of existing and developing wireless standards. In this paper noise sources of an all-digital frequency synthesiser are discussed through s-domain model of frequency synthesisers, and the impact of noise induced by main blocks of synthesisers to the overall phase noise of frequency synthesisers is analysed. Requirements for time to digital converter (TDC), digitally controlled oscillator (DCO) and digital filter suitable for all-digital frequency synthesiser for IoT and IoV applications are defined. The structure of frequency synthesisers, which allows us to meet defined requirements, is presented. Its main parts are 2D Vernier TDC based on gated ring oscillators, which can achieve resolution close to 1 ps; multi core LC-tank DCO, whose tuning range is 4.3–5.4 GHz when two cores are used and phase noise is −116.4 dBc/Hz at 1 MHz offset from 5.44 GHz carrier; digital filter made of proportional and integral gain stages and additional infinite impulse response filter stages. Such a structure allows us to achieve a synthesiser’s in-band phase noise lower than −100 dBc/Hz, out-of-band phase noise equal to −134.0 dBc/Hz and allows us to set a synthesiser to type-I or type-II and change its order from first to sixth. Full article
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