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Green, Energy-Efficient and Sustainable Networks
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Green, Energy-Efficient and Sustainable Networks

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

Deadline for manuscript submissions: closed (15 August 2019) | Viewed by 80493

Printed Edition Available!
A printed edition of this Special Issue is available here.

Special Issue Editors

Dr. Josip Lorincz

E-Mail Website
Guest Editor
FESB-Split, Department of Electronics and Computing, R. Boskovica 32, 21000 Split, Croatia
Interests: telecommunications; wired/wireless access networks; energy-efficient networking; sensor networks; Internet of Things; cloud computing; system optimization; renewable energies
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Antonio Capone

E-Mail Website
Guest Editor
Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, Piazza Leonardo da Vinci 32, 20133 Milano, Italy
Interests: wireless network; radio resource management; network planning and optimization; software defined networks; energy efficient networking; network slicing; network sharing
Dr. Luca Chiaraviglio

E-Mail Website
Guest Editor
Department of Electronic Engineering, University of Rome Tor Vergata, Viale del Politecnico, 00133 Rome, Italy
Interests: 5G networks; Internet for rural and low-income areas; sustainable cloud data centers; optimization techniques
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Jinsong Wu

E-Mail Website
Guest Editor
1. School of Artificial Intelligence, Guilin University of Electronic Technology, Guilin, China.
2. Department of Electrical Engineering, Universidad de Chile, Santiago, Chile.
Interests: edge computing; green computing; Artificial Intelligence
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The topic of “energy-efficient networking and computing” is attracting growing attention for economic, energetic, and environmental reasons. According to a number of studies, Information and Communication Technologies (ICT) alone are responsible for up to 10% of world power consumption, due to the ever-increasing diffusion of electronic devices. Communication networks, including the Internet and wireless networks, represent a non-negligible part of the energy consumption of ICT. In addition, the carbon footprint of ICT devices due to energy consumption and the activities related to their entire lifecycle contributes to global warming. Hence, such rapid increase of power consumed by ICT, as well as the energy bills of service providers indicate necessity for improving energy-efficiency of ICT sector.

This Special Issue aims to serve as a platform for researchers and visionaries from academia, research labs, and industry from all over the world in presenting novelties related to energy-efficiency improvement of networking and computing systems. Sharing ideas, views, results, and experiences in the field of green wired and wireless networking is what this special issue on green, energy-efficient and sustainable Internet is intended to be about. Anything from theoretical and experimental achievements to innovative design and management approaches, prototyping efforts, and case studies is in the focus of this Special Issue, which aims to open new research ways toward more energy efficient networking and computing.

Topics of interest include, but are not limited to, the following:

  • Power consumption models of networking infrastructure
  • Power measurements and data from empirical studies of communication networks
  • Techniques for reducing power consumption in data centers
  • Hardware and architectural support for reducing power consumption
  • Energy efficient network management
  • Energy-efficient Internet of Things (IoT) and Internet of Everything (IoE)
  • Green network design and energy-efficient smart grids
  • Applications of green networking technologies and principles
  • Cross-layer optimizations for reducing energy consumption
  • Optimization of energy consumption in optical networks
  • Energy-efficient protocols and protocol extensions
  • Energy-efficient transmission technologies
  • Energy-efficient peer-to-peer networking and overlays
  • Energy-efficient cloud computing and network function virtualization
  • Green wireless access networks
  • Energy-efficient fog computing
  • Green satellite communications
  • Green wired access networks
  • Green future Internet and software-defined networking
  • Big data meet green challenges
  • Energy cost models for network operators
  • Energy-efficient sensor networks
  • Renewable energy sources for communication networks
  • Antenna design and transmission technologies for reducing energy consumption
  • Green communication technologies for smart cities
  • Energy-efficient vehicle communications
  • Energy-efficient automation and industrial communications
  • Energy-efficient critical communications
  • Energy-efficient solutions for 5G and beyond
  • Green mobile applications
  • Green cognitive networks
  • Low power wireless networks
  • Energy harvesting solutions and prototypes
  • Energy-efficient UAV-based networks
  • Field Trials of Sustainable Networking and Computing
  • Energy-efficient public health solutions based on 5G networks

Authors of selected accepted and presented papers at the 9th Symposium on Green Networking and Computing (SGNC 2018) and the 6th Edition of the International Renewable and Sustainable Energy Conference (IEEE IRSEC'18) are invited to submit extended versions of the papers for this Special Issue.

Dr. Josip Lorincz
Prof. Dr. Antonio Capone
Dr. Luca Chiaraviglio
Prof. Dr. Jinsong Wu
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

  • Green wireless networks
  • Green wired networking
  • Energy-efficient data centres
  • Green cloud computing
  • Energy-efficient sensor networks
  • Green IoT
  • Energy-efficient industrial communications
  • Sustainable Networking and Computing
  • Green Cellular Planning

Published Papers (18 papers)

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Editorial

Jump to: Research, Review

29 pages, 2069 KiB  
Editorial
Greener, Energy-Efficient and Sustainable Networks: State-Of-The-Art and New Trends
by Josip Lorincz, Antonio Capone and Jinsong Wu
Sensors 2019, 19(22), 4864; https://doi.org/10.3390/s19224864 - 08 Nov 2019
Cited by 59 | Viewed by 10128
Abstract
Although information and communications technologies (ICTs) have the potential of enabling powerful social, economic and environmental benefits, ICT systems give a non-negligible contribution to world electricity consumption and carbon dioxide (CO2) footprint. This contribution will sustain since the increased demand for [...] Read more.
Although information and communications technologies (ICTs) have the potential of enabling powerful social, economic and environmental benefits, ICT systems give a non-negligible contribution to world electricity consumption and carbon dioxide (CO2) footprint. This contribution will sustain since the increased demand for user′s connectivity and an explosion of traffic volumes necessitate continuous expansion of current ICTs services and deployment of new infrastructures and technologies which must ensure the expected user experiences and performance. In this paper, analyses of costs for the global annual energy consumption of telecommunication networks, estimation of ICT sector CO2 footprint contribution and predictions of energy consumption of all connected user-related devices and equipment in the period 2011–2030 are presented. Since presented estimations of network energy consumption trends for main communication sectors by 2030 shows that highest contribution to global energy consumption will come from wireless access networks and data centres (DCs), the rest of the paper analyses technologies and concepts which can contribute to the energy-efficiency improvements of these two sectors. More specifically, different paradigms for wireless access networks such as millimetre-wave communications, Long-Term Evolution in unlicensed spectrum, ultra-dense heterogeneous networks, device-to-device communications and massive multiple-input multiple-output communications have been analysed as possible technologies for improvement of wireless networks energy efficiency. Additionally, approaches related to the DC resource management, DCs power management, green DC monitoring and thermal management in DCs have been discussed as promising approaches to improvement of DC power usage efficiency. For each of analysed technologies, future research challenges and open issues have been summarised and discussed. Lastly, an overview of the accepted papers in the Special Issue dedicated to the green, energy-efficient and sustainable networks is presented. Full article
(This article belongs to the Special Issue Green, Energy-Efficient and Sustainable Networks)
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Research

Jump to: Editorial, Review

12 pages, 590 KiB  
Article
Closed-Form Expression for the Symbol Error Probability in Full-Duplex Spatial Modulation Relay System and Its Application in Optimal Power Allocation
by Le Van Nguyen, Ba Cao Nguyen, Xuan Nam Tran and Le The Dung
Sensors 2019, 19(24), 5390; https://doi.org/10.3390/s19245390 - 06 Dec 2019
Cited by 17 | Viewed by 2973
Abstract
Full-duplex (FD) communication and spatial modulation (SM) are two promising techniques to achieve high spectral efficiency. Recent works in the literature have investigated the possibility of combining the FD mode with SM in the relay system to benefit their advantages. In this paper, [...] Read more.
Full-duplex (FD) communication and spatial modulation (SM) are two promising techniques to achieve high spectral efficiency. Recent works in the literature have investigated the possibility of combining the FD mode with SM in the relay system to benefit their advantages. In this paper, we analyze the performance of the FD-SM decode-and-forward (DF) relay system and derive the closed-form expression for the symbol error probability (SEP). To tackle the residual self-interference (RSI) due to the FD mode at the relay, we propose a simple yet effective power allocation algorithm to compensate for the RSI impact and improve the system SEP performance. Both numerical and simulation results confirm the accuracy of the derived SEP expression and the efficacy of the proposed optimal power allocation. Full article
(This article belongs to the Special Issue Green, Energy-Efficient and Sustainable Networks)
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Graphical abstract

15 pages, 1296 KiB  
Article
An SDN Focused Approach for Energy Aware Traffic Engineering in Data Centers
by Paris Charalampou and Efstathios D. Sykas
Sensors 2019, 19(18), 3980; https://doi.org/10.3390/s19183980 - 14 Sep 2019
Cited by 6 | Viewed by 3335
Abstract
There is a lot of effort to limit the impact of CO2 emissions from the information communication technologies (ICT) industry by reducing the energy consumption on all aspects of networking technologies. In a service provider network, data centers (DCs) are the major [...] Read more.
There is a lot of effort to limit the impact of CO2 emissions from the information communication technologies (ICT) industry by reducing the energy consumption on all aspects of networking technologies. In a service provider network, data centers (DCs) are the major power consumer and considerable gains are expected by regulating the operation network devices. In this context, we developed a mixed integer programming (MIP) algorithm to optimize the power consumption of network devices via energy aware traffic engineering. We verified our approach by simulating DC network topologies and demonstrated that clear benefits can be achieved for various network sizes and traffic volumes. Our algorithm can be easily implemented as an application in the software-defined networking (SDN) paradigm, making quite feasible its deployment in a production environment. Full article
(This article belongs to the Special Issue Green, Energy-Efficient and Sustainable Networks)
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26 pages, 3566 KiB  
Article
Towards Sustainable Energy-Efficient Communities Based on a Scheduling Algorithm
by Carlos Cruz, Esther Palomar, Ignacio Bravo and Alfredo Gardel
Sensors 2019, 19(18), 3973; https://doi.org/10.3390/s19183973 - 14 Sep 2019
Cited by 10 | Viewed by 3176
Abstract
The Internet of Things (IoT) and Demand Response (DR) combined have transformed the way Information and Communication Technologies (ICT) contribute to saving energy and reducing costs, while also giving consumers more control over their energy footprint. Unlike current price and incentive based DR [...] Read more.
The Internet of Things (IoT) and Demand Response (DR) combined have transformed the way Information and Communication Technologies (ICT) contribute to saving energy and reducing costs, while also giving consumers more control over their energy footprint. Unlike current price and incentive based DR strategies, we propose a DR model that promotes consumers reaching coordinated behaviour towards more sustainable (and green) communities. A cooperative DR system is designed not only to bolster energy efficiency management at both home and district levels, but also to integrate the renewable energy resource information into the community’s energy management. Initially conceived in a centralised way, a data collector called the “aggregator” will handle the operation scheduling requirements given the consumers’ time preferences and the available electricity supply from renewables. Evaluation on the algorithm implementation shows feasible computational cost (CC) in different scenarios of households, communities and consumer behaviour. Number of appliances and timeframe flexibility have the greatest impact on the reallocation cost. A discussion on the communication, security and hardware platforms is included prior to future pilot deployment. Full article
(This article belongs to the Special Issue Green, Energy-Efficient and Sustainable Networks)
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15 pages, 2134 KiB  
Article
Radio Frequency Fingerprint-Based Intelligent Mobile Edge Computing for Internet of Things Authentication
by Songlin Chen, Hong Wen, Jinsong Wu, Aidong Xu, Yixin Jiang, Huanhuan Song and Yi Chen
Sensors 2019, 19(16), 3610; https://doi.org/10.3390/s19163610 - 19 Aug 2019
Cited by 29 | Viewed by 5134
Abstract
In this paper, a light-weight radio frequency fingerprinting identification (RFFID) scheme that combines with a two-layer model is proposed to realize authentications for a large number of resource-constrained terminals under the mobile edge computing (MEC) scenario without relying on encryption-based methods. In the [...] Read more.
In this paper, a light-weight radio frequency fingerprinting identification (RFFID) scheme that combines with a two-layer model is proposed to realize authentications for a large number of resource-constrained terminals under the mobile edge computing (MEC) scenario without relying on encryption-based methods. In the first layer, signal collection, extraction of RF fingerprint features, dynamic feature database storage, and access authentication decision are carried out by the MEC devices. In the second layer, learning features, generating decision models, and implementing machine learning algorithms for recognition are performed by the remote cloud. By this means, the authentication rate can be improved by taking advantage of the machine-learning training methods and computing resource support of the cloud. Extensive simulations are performed under the IoT application scenario. The results show that the novel method can achieve higher recognition rate than that of traditional RFFID method by using wavelet feature effectively, which demonstrates the efficiency of our proposed method. Full article
(This article belongs to the Special Issue Green, Energy-Efficient and Sustainable Networks)
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25 pages, 1346 KiB  
Article
A Machine Learning Approach to Achieving Energy Efficiency in Relay-Assisted LTE-A Downlink System
by Hammad Hassan, Irfan Ahmed, Rizwan Ahmad, Hedi Khammari, Ghulam Bhatti, Waqas Ahmed and Muhammad Mahtab Alam
Sensors 2019, 19(16), 3461; https://doi.org/10.3390/s19163461 - 08 Aug 2019
Cited by 7 | Viewed by 3049
Abstract
In recent years, Energy Efficiency (EE) has become a critical design metric for cellular systems. In order to achieve EE, a fine balance between throughput and fairness must also be ensured. To this end, in this paper we have presented various resource block [...] Read more.
In recent years, Energy Efficiency (EE) has become a critical design metric for cellular systems. In order to achieve EE, a fine balance between throughput and fairness must also be ensured. To this end, in this paper we have presented various resource block (RB) allocation schemes in relay-assisted Long Term Evolution-Advanced (LTE-A) networks. Driven by equal power and Bisection-based Power Allocation (BOPA) algorithm, the Maximum Throughput (MT) and an alternating MT and proportional fairness (PF)-based SAMM (abbreviated with Authors’ names) RB allocation scheme is presented for a single relay. In the case of multiple relays, the dependency of RB and power allocation on relay deployment and users’ association is first addressed through a k-mean clustering approach. Secondly, to reduce the computational cost of RB and power allocation, a two-step neural network (NN) process (SAMM NN) is presented that uses SAMM-based unsupervised learning for RB allocation and BOPA-based supervised learning for power allocation. The results for all the schemes are compared in terms of EE and user throughput. For a single relay, SAMM BOPA offers the best EE, whereas SAMM equal power provides the best fairness. In the case of multiple relays, the results indicate SAMM NN achieves better EE compared to SAMM equal power and BOPA, and it also achieves better throughput fairness compared to MT equal power and MT BOPA. Full article
(This article belongs to the Special Issue Green, Energy-Efficient and Sustainable Networks)
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18 pages, 534 KiB  
Article
On the Performance of Energy Harvesting Non-Orthogonal Multiple Access Relaying System with Imperfect Channel State Information over Rayleigh Fading Channels
by Tran Manh Hoang, Nguyen Le Van, Ba Cao Nguyen and Le The Dung
Sensors 2019, 19(15), 3327; https://doi.org/10.3390/s19153327 - 29 Jul 2019
Cited by 21 | Viewed by 3163
Abstract
In this paper, we propose a non-orthogonal multiple access (NOMA) relaying system, where a source node communicates simultaneously with multiple users via the assistance of the best amplify-and-forward (AF) relay. The best relay is selected among N relays which are capable of harvesting [...] Read more.
In this paper, we propose a non-orthogonal multiple access (NOMA) relaying system, where a source node communicates simultaneously with multiple users via the assistance of the best amplify-and-forward (AF) relay. The best relay is selected among N relays which are capable of harvesting the energy from radio frequency (RF) signals. We analyze the performance of the proposed NOMA relaying system in the conditions of imperfect channel state information (CSI) and Rayleigh fading by deriving the exact expressions of the outage probability (OP) and the approximate expression of the ergodic capacities of each user and the whole system. We also determine the optimal energy harvesting duration which minimizes the OP. Numerical results show that, for the same parameter settings, the performance of the proposed NOMA relaying system, especially the ergodic capacity of the whole system, outperforms that of the orthogonal-multiple-access (OMA) relaying system. Monte-Carlo simulations are used to validate the correctness of the analytical results. Full article
(This article belongs to the Special Issue Green, Energy-Efficient and Sustainable Networks)
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22 pages, 4072 KiB  
Article
Energy, Carbon and Renewable Energy: Candidate Metrics for Green-Aware Routing?
by Md. Mohaimenul Hossain, Jean-Philippe Georges, Eric Rondeau and Thierry Divoux
Sensors 2019, 19(13), 2901; https://doi.org/10.3390/s19132901 - 30 Jun 2019
Cited by 4 | Viewed by 3106
Abstract
There are all sort of indications that Internet usage will go only upwards, resulting in an increase in energy consumption and CO2 emissions. At the same time, a significant amount of this carbon footprint corresponds to the information and communication technologies (ICT) [...] Read more.
There are all sort of indications that Internet usage will go only upwards, resulting in an increase in energy consumption and CO2 emissions. At the same time, a significant amount of this carbon footprint corresponds to the information and communication technologies (ICT) sector, with around one third being due to networking. In this paper we have approached the problem of green networking from the point of view of sustainability. Here, alongside energy-aware routing, we have also introduced pollution-aware routing with environmental metrics like carbon emission factor and non-renewable energy usage percentage. We have proposed an algorithm based on these three candidate-metrics. Our algorithm provides optimum data and control planes for three different metrics which regulate the usage of different routers and adapt the bandwidth of the links while giving the traffic demand requirements utmost priority. We have made a comparison between these three metrics in order to show their impact on greening routing. The results show that for a particular scenario, our pollution-aware routing algorithm can reduce 36% and 20% of CO2 emissions compared to shortest path first and energy-based solutions, respectively. Full article
(This article belongs to the Special Issue Green, Energy-Efficient and Sustainable Networks)
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24 pages, 6391 KiB  
Article
Optimizing Charging Efficiency and Maintaining Sensor Network Perpetually in Mobile Directional Charging
by Xianghua Xu, Lu Chen and Zongmao Cheng
Sensors 2019, 19(12), 2657; https://doi.org/10.3390/s19122657 - 12 Jun 2019
Cited by 6 | Viewed by 3400
Abstract
Wireless Power Transfer (WPT) is a promising technology to replenish energy of sensors in Rechargeable Wireless Sensor Networks (RWSN). In this paper, we investigate the mobile directional charging optimization problem in RWSN. Our problem is how to plan the moving path and charging [...] Read more.
Wireless Power Transfer (WPT) is a promising technology to replenish energy of sensors in Rechargeable Wireless Sensor Networks (RWSN). In this paper, we investigate the mobile directional charging optimization problem in RWSN. Our problem is how to plan the moving path and charging direction of the Directional Charging Vehicle (DCV) in the 2D plane to replenish energy for RWSN. The objective is to optimize energy charging efficiency of the DCV while maintaining the sensor network working continuously. To the best of our knowledge, this is the first work to study the mobile directional charging problem in RWSN. We prove that the problem is NP-hard. Firstly, the coverage utility of the DCV’s directional charging is proposed. Then we design an approximation algorithm to determine the docking spots and their charging orientations while minimizing the number of the DCV’s docking spots and maximizing the charging coverage utility. Finally, we propose a moving path planning algorithm for the DCV’s mobile charging to optimize the DCV’s energy charging efficiency while ensuring the networks working continuously. We theoretically analyze the DCV’s charging service capability, and perform the comprehensive simulation experiments. The experiment results show the energy efficiency of the DCV is higher than the omnidirectional charging model in the sparse networks. Full article
(This article belongs to the Special Issue Green, Energy-Efficient and Sustainable Networks)
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17 pages, 3030 KiB  
Article
Deep-Learning-Based Physical Layer Authentication for Industrial Wireless Sensor Networks
by Run-Fa Liao, Hong Wen, Jinsong Wu, Fei Pan, Aidong Xu, Yixin Jiang, Feiyi Xie and Minggui Cao
Sensors 2019, 19(11), 2440; https://doi.org/10.3390/s19112440 - 28 May 2019
Cited by 68 | Viewed by 6477
Abstract
In this paper, a deep learning (DL)-based physical (PHY) layer authentication framework is proposed to enhance the security of industrial wireless sensor networks (IWSNs). Three algorithms, the deep neural network (DNN)-based sensor nodes’ authentication method, the convolutional neural network (CNN)-based sensor nodes’ authentication [...] Read more.
In this paper, a deep learning (DL)-based physical (PHY) layer authentication framework is proposed to enhance the security of industrial wireless sensor networks (IWSNs). Three algorithms, the deep neural network (DNN)-based sensor nodes’ authentication method, the convolutional neural network (CNN)-based sensor nodes’ authentication method, and the convolution preprocessing neural network (CPNN)-based sensor nodes’ authentication method, have been adopted to implement the PHY-layer authentication in IWSNs. Among them, the improved CPNN-based algorithm requires few computing resources and has extremely low latency, which enable a lightweight multi-node PHY-layer authentication. The adaptive moment estimation (Adam) accelerated gradient algorithm and minibatch skill are used to accelerate the training of the neural networks. Simulations are performed to evaluate the performance of each algorithm and a brief analysis of the application scenarios for each algorithm is discussed. Moreover, the experiments have been performed with universal software radio peripherals (USRPs) to evaluate the authentication performance of the proposed algorithms. Due to the trainings being performed on the edge sides, the proposed method can implement a lightweight authentication for the sensor nodes under the edge computing (EC) system in IWSNs. Full article
(This article belongs to the Special Issue Green, Energy-Efficient and Sustainable Networks)
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21 pages, 4208 KiB  
Article
Social-Aware Peer Discovery for Energy Harvesting-Based Device-To-Device Communications
by Zelalem Legese Hailemariam, Yuan-Cheng Lai, Yen-Hung Chen, Yu-Hsueh Wu and Arthur Chang
Sensors 2019, 19(10), 2304; https://doi.org/10.3390/s19102304 - 18 May 2019
Cited by 5 | Viewed by 2769
Abstract
In Device-to-Device (D2D) communications, the first step is to find all of the neighboring peers in the network by performing a peer discovery process. Most previous studies use the social behaviors of the users to adjust the sending rates of the peer discovery [...] Read more.
In Device-to-Device (D2D) communications, the first step is to find all of the neighboring peers in the network by performing a peer discovery process. Most previous studies use the social behaviors of the users to adjust the sending rates of the peer discovery messages (i.e., beacons) under the constraint of consumed power for increasing the Peer Discovery Ratio (PDR). However, these studies do not consider the potential for energy harvesting, which allows for the User Equipments (UEs) to procure additional power within charging areas. Accordingly, this paper proposes an Energy-Ratio Rate Decision (ERRD) algorithm that comprises three steps, namely Social Ratio Allocation (SRA), Energy Ratio Allocation (ERA), and Beacon Rate Decision (BRD). The SRA step determines the allocated power quantum for each UE from the total budget power based on the social behavior of the UE. The ERA step then adjusts this allocated power quantum in accordance with the power that is harvested by the UE. Finally, the BRD step computes the beacon rate for the UE based on the adjusted power quantum. The simulation results show that ERRD outperforms the previously-reported Social-Based Grouping (SBG) algorithm by 190% on the PDR for a budget power of one watt and 8% for a budget power of 20 watts. Full article
(This article belongs to the Special Issue Green, Energy-Efficient and Sustainable Networks)
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24 pages, 700 KiB  
Article
Joint Optimization of Interference Coordination Parameters and Base-Station Density for Energy-Efficient Heterogeneous Networks
by Yanzan Sun, Han Xu, Shunqing Zhang, Yating Wu, Tao Wang, Yong Fang and Shugong Xu
Sensors 2019, 19(9), 2154; https://doi.org/10.3390/s19092154 - 09 May 2019
Cited by 4 | Viewed by 3075
Abstract
Heterogeneous networks (HetNets), consisting of macro-cells and overlaying pico-cells, have been recognized as a promising paradigm to support the exponential growth of data traffic demands and high network energy efficiency (EE). However, for two-tier heterogeneous architecture deployment of HetNets, the inter-tier interference will [...] Read more.
Heterogeneous networks (HetNets), consisting of macro-cells and overlaying pico-cells, have been recognized as a promising paradigm to support the exponential growth of data traffic demands and high network energy efficiency (EE). However, for two-tier heterogeneous architecture deployment of HetNets, the inter-tier interference will be challenging. Time domain further-enhanced inter-cell interference coordination (FeICIC) proposed in 3GPP Release-11 becomes necessary to mitigate the inter-tier interference by applying low power almost blank subframe (ABS) scheme. Therefore, for HetNets deployment in reality, the pico-cell range expansion (CRE) bias, the power of ABS and the density of pico base stations (PBSs) are three important factors for the network EE improvement. Aiming to improve the network EE, the above three factors are jointly considered in this paper. In particular, we first derive the closed-form expression of the network EE as a function of pico CRE bias, power reduction factor of low power ABS and PBS density based on stochastic geometry model. Then, the approximate relationship between pico CRE bias and power reduction factor is deduced, followed by a linear search algorithm to get the near-optimal pico CRE bias and power reduction factor together at a given PBS density. Next, a linear search algorithm is further proposed to optimize PBS density based on fixed pico CRE bias and power reduction factor. Due to the fact that the above pico CRE bias and power reduction factor optimization and PBS density optimization are optimized separately, a heuristic algorithm is further proposed to optimize pico CRE bias, power reduction factor and PBS density jointly to achieve global network EE maximization. Numerical simulation results show that our proposed heuristic algorithm can significantly enhance the network EE while incurring low computational complexity. Full article
(This article belongs to the Special Issue Green, Energy-Efficient and Sustainable Networks)
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20 pages, 3993 KiB  
Article
Clustering Based Physical-Layer Authentication in Edge Computing Systems with Asymmetric Resources
by Yi Chen, Hong Wen, Jinsong Wu, Huanhuan Song, Aidong Xu, Yixin Jiang, Tengyue Zhang and Zhen Wang
Sensors 2019, 19(8), 1926; https://doi.org/10.3390/s19081926 - 24 Apr 2019
Cited by 22 | Viewed by 3504
Abstract
In this paper, we propose a clustering based physical-layer authentication scheme (CPAS) to overcome the drawback of traditional cipher-based authentication schemes that suffer from heavy costs and are limited by energy-constrained intelligent devices. CPAS is a novel cross-layer secure authentication approach for edge [...] Read more.
In this paper, we propose a clustering based physical-layer authentication scheme (CPAS) to overcome the drawback of traditional cipher-based authentication schemes that suffer from heavy costs and are limited by energy-constrained intelligent devices. CPAS is a novel cross-layer secure authentication approach for edge computing system with asymmetric resources. The CPAS scheme combines clustering and lightweight symmetric cipher with physical-layer channel state information to provide two-way authentication between terminals and edge devices. By taking advantage of temporal and spatial uniqueness in physical layer channel responses, the non-cryptographic physical layer authentication techniques can achieve fast authentication. The lightweight symmetric cipher initiates user authentication at the start of a session to establish the trust connection. Based on theoretical analysis, the CPAS scheme is secure and simple, but there is no trusted party, while it can also resist small integer attacks, replay attacks, and spoofing attacks. Besides, experimental results show that the proposed scheme can boost the total success rate of access authentication and decrease the data frame loss rate, without notable increase in authentication latencies. Full article
(This article belongs to the Special Issue Green, Energy-Efficient and Sustainable Networks)
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15 pages, 731 KiB  
Article
Adversarial Samples on Android Malware Detection Systems for IoT Systems
by Xiaolei Liu, Xiaojiang Du, Xiaosong Zhang, Qingxin Zhu, Hao Wang and Mohsen Guizani
Sensors 2019, 19(4), 974; https://doi.org/10.3390/s19040974 - 25 Feb 2019
Cited by 50 | Viewed by 6578
Abstract
Many IoT (Internet of Things) systems run Android systems or Android-like systems. With the continuous development of machine learning algorithms, the learning-based Android malware detection system for IoT devices has gradually increased. However, these learning-based detection models are often vulnerable to adversarial samples. [...] Read more.
Many IoT (Internet of Things) systems run Android systems or Android-like systems. With the continuous development of machine learning algorithms, the learning-based Android malware detection system for IoT devices has gradually increased. However, these learning-based detection models are often vulnerable to adversarial samples. An automated testing framework is needed to help these learning-based malware detection systems for IoT devices perform security analysis. The current methods of generating adversarial samples mostly require training parameters of models and most of the methods are aimed at image data. To solve this problem, we propose a testing framework for learning-based Android malware detection systems (TLAMD) for IoT Devices. The key challenge is how to construct a suitable fitness function to generate an effective adversarial sample without affecting the features of the application. By introducing genetic algorithms and some technical improvements, our test framework can generate adversarial samples for the IoT Android application with a success rate of nearly 100% and can perform black-box testing on the system. Full article
(This article belongs to the Special Issue Green, Energy-Efficient and Sustainable Networks)
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16 pages, 7717 KiB  
Article
Measurement Structures of Image Compressive Sensing for Green Internet of Things (IoT)
by Ran Li, Xiaomeng Duan and Yanling Li
Sensors 2019, 19(1), 102; https://doi.org/10.3390/s19010102 - 29 Dec 2018
Cited by 3 | Viewed by 3307
Abstract
Image compressive sensing (CS) is a potential imaging scheme for green internet of things (IoT). To further make CS-based sensor adaptable to low bandwidth and low power, this paper focuses on finding a good measurement structure, i.e., the organization and storage format of [...] Read more.
Image compressive sensing (CS) is a potential imaging scheme for green internet of things (IoT). To further make CS-based sensor adaptable to low bandwidth and low power, this paper focuses on finding a good measurement structure, i.e., the organization and storage format of CS measurements. Three potential measurement structures are proposed in this paper, respectively raster structure (RA), patch structure, and layer structure (LA). RA stores CS measurements of each column in an image, and PA packets CS measurements of overlapping patches forming an image. LA enables the measuring of small blocks and recovery of large blocks. All of the three structures avoid high computation complexity and huge memory in the process of measuring and recovery, and efficiently suppress the annoying blocking artifacts which often occur in traditional block structures. Experimental results show that RA, PA, and LA can efficiently reduce blocking artifacts, and produce comforting visual qualities. LA, especially, presents both good time-distortion and rate-distortion performance. By this paper, it is proved that LA is a suitable measurement structure for green IoT. Full article
(This article belongs to the Special Issue Green, Energy-Efficient and Sustainable Networks)
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23 pages, 830 KiB  
Article
Matching SDN and Legacy Networking Hardware for Energy Efficiency and Bounded Delay
by Pablo  Fondo-Ferreiro, Miguel Rodríguez-Pérez, Manuel  Fernández-Veiga and Sergio  Herrería-Alonso
Sensors 2018, 18(11), 3915; https://doi.org/10.3390/s18113915 - 13 Nov 2018
Cited by 3 | Viewed by 4424
Abstract
Both economic and environmental costs are driving much research in the area of the energy efficiency of networking equipment. This research has produced a great amount of proposals. However, the majority of them remain unimplemented due to the lack of flexibility of current [...] Read more.
Both economic and environmental costs are driving much research in the area of the energy efficiency of networking equipment. This research has produced a great amount of proposals. However, the majority of them remain unimplemented due to the lack of flexibility of current hardware devices and a certain lack of enthusiasm from commercial vendors. At the same time, Software-Defined Networking (SDN) has allowed customers to control switching decisions with a flexibility and precision previously unheard of. This paper explores the potential convergence between the two aforementioned trends and presents a promising power saving algorithm that can be implemented using standard SDN capabilities of current switches, reducing operation costs on both data centers and wired access networks. In particular, we focus on minimizing the energy consumption in bundles of energy-efficient Ethernet links leveraging SDN. For this, we build on an existing theoretical algorithm and adapt it for implementing with an SDN solution. We study several approaches and compare the resulting algorithms not only according to their energy efficiency, but also taking into account additional QoS metrics. The results show that the resulting algorithm is able to closely match the theoretical results, even when taking into account the requirements of delay-sensitive traffic. Full article
(This article belongs to the Special Issue Green, Energy-Efficient and Sustainable Networks)
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22 pages, 896 KiB  
Article
Impact of Node Speed on Energy-Constrained Opportunistic Internet-of-Things with Wireless Power Transfer
by Seung-Woo Ko and Seong-Lyun Kim
Sensors 2018, 18(7), 2398; https://doi.org/10.3390/s18072398 - 23 Jul 2018
Cited by 9 | Viewed by 3962
Abstract
Wireless power transfer (WPT) is a promising technology to realize the vision of Internet-of-Things (IoT) by powering energy-hungry IoT nodes by electromagnetic waves, overcoming the difficulty in battery recharging for massive numbers of nodes. Specifically, wireless charging stations (WCS) are deployed to transfer [...] Read more.
Wireless power transfer (WPT) is a promising technology to realize the vision of Internet-of-Things (IoT) by powering energy-hungry IoT nodes by electromagnetic waves, overcoming the difficulty in battery recharging for massive numbers of nodes. Specifically, wireless charging stations (WCS) are deployed to transfer energy wirelessly to IoT nodes in the charging coverage. However, the coverage is restricted due to the limited hardware capability and safety issue, making mobile nodes have different battery charging patterns depending on their moving speeds. For example, slow moving nodes outside the coverage resort to waiting for energy charging from WCSs for a long time while those inside the coverage consistently recharge their batteries. On the other hand, fast moving nodes are able to receive energy within a relatively short waiting time. This paper investigates the above impact of node speed on energy provision and the resultant throughput of energy-constrained opportunistic IoT networks when data exchange between nodes are constrained by their intermittent connections as well as the levels of remaining energy. To this end, we design a two-dimensional Markov chain of which the state dimensions represent remaining energy and distance to the nearest WCS normalized by node speed, respectively. Solving this enables providing the following three insights. First, faster node speed makes the inter-meeting time between a node and a WCS shorter, leading to more frequent energy supply and higher throughput. Second, the above effect of node speed becomes marginal as the battery capacity increases. Finally, as nodes are more densely deployed, the throughput becomes scaling with the density ratio between mobiles and WCSs but independent of node speed, meaning that the throughput improvement from node speed disappears in dense networks. The results provide useful guidelines for IoT network provisioning and planning to achieve the maximum throughput performance given mobile environments. Full article
(This article belongs to the Special Issue Green, Energy-Efficient and Sustainable Networks)
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Review

Jump to: Editorial, Research

23 pages, 827 KiB  
Review
A Survey on Recent Trends and Open Issues in Energy Efficiency of 5G
by Muhammad Usama and Melike Erol-Kantarci
Sensors 2019, 19(14), 3126; https://doi.org/10.3390/s19143126 - 15 Jul 2019
Cited by 56 | Viewed by 7222
Abstract
The rapidly increasing interest from various verticals for the upcoming 5th generation (5G) networks expect the network to support higher data rates and have an improved quality of service. This demand has been met so far by employing sophisticated transmission techniques including massive [...] Read more.
The rapidly increasing interest from various verticals for the upcoming 5th generation (5G) networks expect the network to support higher data rates and have an improved quality of service. This demand has been met so far by employing sophisticated transmission techniques including massive Multiple Input Multiple Output (MIMO), millimeter wave (mmWave) bands as well as bringing the computational power closer to the users via advanced baseband processing units at the base stations. Future evolution of the networks has also been assumed to open many new business horizons for the operators and the need of not only a resource efficient but also an energy efficient ecosystem has greatly been felt. The deployment of small cells has been envisioned as a promising answer for handling the massive heterogeneous traffic, but the adverse economic and environmental impacts cannot be neglected. Given that 10% of the world’s energy consumption is due to the Information and Communications Technology (ICT) industry, energy-efficiency has thus become one of the key performance indicators (KPI). Various avenues of optimization, game theory and machine learning have been investigated for enhancing power allocation for downlink and uplink channels, as well as other energy consumption/saving approaches. This paper surveys the recent works that address energy efficiency of the radio access as well as the core of wireless networks, and outlines related challenges and open issues. Full article
(This article belongs to the Special Issue Green, Energy-Efficient and Sustainable Networks)
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