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Special Issue "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: 15 June 2019

Special Issue Editors

Guest Editor
Dr. Josip Lorincz

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

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

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

Department of Electrical Engineering, Universidad de Chile, Av Tupper 2007, Santiago, 8370451, Chile
Website | E-Mail
Interests: green communications and computing; environmental sustainability; big data and data analytics; smart cities

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 papers will be 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 1800 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 (7 papers)

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Research

Open AccessArticle
Social-Aware Peer Discovery for Energy Harvesting-Based Device-to-Device Communications
Sensors 2019, 19(10), 2304; https://doi.org/10.3390/s19102304 (registering DOI)
Received: 7 March 2019 / Revised: 27 April 2019 / Accepted: 16 May 2019 / Published: 18 May 2019
PDF Full-text (644 KB)
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)
Open AccessArticle
Joint Optimization of Interference Coordination Parameters and Base-Station Density for Energy-Efficient Heterogeneous Networks
Sensors 2019, 19(9), 2154; https://doi.org/10.3390/s19092154
Received: 16 March 2019 / Revised: 5 May 2019 / Accepted: 6 May 2019 / Published: 9 May 2019
PDF Full-text (700 KB) | HTML Full-text | XML Full-text
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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Open AccessArticle
Clustering Based Physical-Layer Authentication in Edge Computing Systems with Asymmetric Resources
Sensors 2019, 19(8), 1926; https://doi.org/10.3390/s19081926
Received: 15 March 2019 / Revised: 19 April 2019 / Accepted: 20 April 2019 / Published: 24 April 2019
PDF Full-text (3993 KB) | HTML Full-text | XML Full-text
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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Open AccessArticle
Adversarial Samples on Android Malware Detection Systems for IoT Systems
Sensors 2019, 19(4), 974; https://doi.org/10.3390/s19040974
Received: 22 December 2018 / Revised: 11 February 2019 / Accepted: 20 February 2019 / Published: 25 February 2019
PDF Full-text (731 KB) | HTML Full-text | XML Full-text
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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Open AccessArticle
Measurement Structures of Image Compressive Sensing for Green Internet of Things (IoT)
Sensors 2019, 19(1), 102; https://doi.org/10.3390/s19010102
Received: 7 November 2018 / Revised: 15 December 2018 / Accepted: 24 December 2018 / Published: 29 December 2018
PDF Full-text (7717 KB) | HTML Full-text | XML Full-text
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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Open AccessFeature PaperArticle
Matching SDN and Legacy Networking Hardware for Energy Efficiency and Bounded Delay
Sensors 2018, 18(11), 3915; https://doi.org/10.3390/s18113915
Received: 3 October 2018 / Revised: 29 October 2018 / Accepted: 8 November 2018 / Published: 13 November 2018
PDF Full-text (830 KB) | HTML Full-text | XML Full-text
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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Open AccessArticle
Impact of Node Speed on Energy-Constrained Opportunistic Internet-of-Things with Wireless Power Transfer
Sensors 2018, 18(7), 2398; https://doi.org/10.3390/s18072398
Received: 15 June 2018 / Revised: 6 July 2018 / Accepted: 16 July 2018 / Published: 23 July 2018
Cited by 2 | PDF Full-text (896 KB) | HTML Full-text | XML Full-text
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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