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Special Issue "Green Communications and Networking for IoT"

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

Deadline for manuscript submissions: closed (15 October 2018)

Special Issue Editors

Guest Editor
Prof. Dr. Francesca Cuomo

Department of Information Engineering, Electronics and Telecommunications, SAPIENZA University of Rome, Via Eudossiana 18, 00184 Rome, Italy
Website | E-Mail
Interests: wireless sensor networks; low power wide-area networks; wireless networking; vehicular networks
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
Dr. Konstantin Mikhaylov

Department of Communications Engineering, Centre for Wireless Communications, University of Oulu Erkki Koiso-Kanttilan katu 3, FIN-90014 Oulu, Finland
Website | E-Mail
Interests: low power wide-area networks; energy efficient wireless technologies; embedded systems; IoT applications and use cases

Special Issue Information

Dear Colleagues,

The Internet of Things (IoT) is becoming a pervasive paradigm that will have a significant impact on future generations of applications in many fields, including (but not limited to) automation, computer science, telecommunications, e-health and industrial engineering. The impact of IoT is particularly evident in the increasing research and development activities in the field of industrial models and processes, as well as in the forthcoming next generation technologies in different areas like the wireless low power communications, autonomous system, 5G.

There are several challenges related to the planning, developing and managing of systems for IoT applications, and one of these challenges requires solutions that are able to make IoT a green and an energy-efficient paradigm. As a matter of fact, the exploitation of wireless sensors, autonomous systems (robots, vehicles, UAVs), Machine-to-Machine, industrial and medical IoT and other similar technologies will require on the one side enhanced communications and networking capabilities and on the other side their sustainability and power efficiency, especially for wide-scale deployments of IoT applications.

The research literature is working on the environmental impact and sustainability issues of information and communication technologies. Given that IoT may help in paving the way towards a general green “objective”, the analysis on how the IoT, its architectural models, its protocols and technologies and the resulting applications can be inherently “green” is a mandatory step in this direction. Since different tradeoffs arise when designing IoT networking and communication technologies while taking into account their energy efficiency, we look forward to receiving original reviews and research papers presenting new methodologies, metrics, performance, measurement, test-beds, and results in the field of green IoT communications and networking.

 This call for papers includes the following key thematic areas:

  • innovative green communications technologies and protocols suitably designed for the IoT;
  • architectures, concepts, methods and tools for planning and configuring green IoT communication platforms and networking systems;
  • green IoT applications and results of their practical deployment.
Prof. Dr. Francesca Cuomo
Dr. Luca Chiaraviglio
Dr. Konstantin Mikhaylov
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

  • Low power communications
  • Low-Power Local and Wide-Area Networks (e.g., LoRa, SigFox, 6LowPAN, NB-LTE, LTE-M)
  • Energy-efficiency for wireless and mobile IoT
  • Low energy data processing, analysis and storage for the IoT
  • Sustainability issues in IoT sensors and communication platforms
  • Resource and power management for the green IoT
  • Methods and architectures for local edge and fog computing for IoT
  • Optimization and tradeoff analyses of connectivity/scalability vs. energy
  • Green IoT metrics, performance, measurement, test-beds and results
  • Energy harvesting and wireless power transfer for green IoT
  • Green IoT applications and services.

Published Papers (16 papers)

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Research

Open AccessArticle The Design of an Energy Harvesting Wireless Sensor Node for Tracking Pink Iguanas
Sensors 2019, 19(5), 985; https://doi.org/10.3390/s19050985
Received: 28 December 2018 / Revised: 1 February 2019 / Accepted: 21 February 2019 / Published: 26 February 2019
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Abstract
The design of wireless sensor nodes for animal tracking is a multidisciplinary activity that presents several research challenges both from a technical and a biological point of view. A monitoring device has to be designed accounting for all system requirements including the specific [...] Read more.
The design of wireless sensor nodes for animal tracking is a multidisciplinary activity that presents several research challenges both from a technical and a biological point of view. A monitoring device has to be designed accounting for all system requirements including the specific characteristics of animals and environment. In this work we present some aspects of the design of a wireless sensor node to track and monitor the pink iguana of the Galápagos: a recently discovered species living in remote locations at the Galápagos Islands. The few individuals of this species live in a relatively small area that lacks of any available communication infrastructure. We present and discuss the energy harvesting architecture and the related energy management logic. We also discuss the impact of packaging on the sensor performance and the consequences of the limited available energy on the GPS tracking. Full article
(This article belongs to the Special Issue Green Communications and Networking for IoT)
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Open AccessArticle An Intelligent Low-Power Displaying System with Integrated Emergency Alerting Capability
Sensors 2019, 19(3), 666; https://doi.org/10.3390/s19030666
Received: 14 December 2018 / Revised: 27 January 2019 / Accepted: 2 February 2019 / Published: 6 February 2019
Cited by 1 | PDF Full-text (4410 KB) | HTML Full-text | XML Full-text
Abstract
Integrated communication infrastructure has become a must-have facility for modern public buildings and offices. To cover this need, several commercial products exist on the market, but most of them require advanced technical skill to operate, while others require manual and time-consuming operations. This [...] Read more.
Integrated communication infrastructure has become a must-have facility for modern public buildings and offices. To cover this need, several commercial products exist on the market, but most of them require advanced technical skill to operate, while others require manual and time-consuming operations. This work proposes an intelligent displaying and alerting system (called SICIAD), implemented over an integrated communication infrastructure with support for wireless ePaper and iBeacon technologies to enhance displaying static and dynamic information, as well as to ease the indoor orientation of guests. A centralized display management console is implemented, as well as procedures for automatically displaying different types of notifications. An Android mobile application is developed which enables indoor user location and guidance. The system targets educational and research institutions but could also cope with public institutions such as museums and hospitals. Remote authentication is supported in research facilities through eduroam technology, access being provided by the user’s distant institution of affiliation. Secure multiple-level access to the system is provided to users, from guests to system administrators, based on locally defined policies. Functional validation and performance evaluation aspects are presented for the proposed system. Full article
(This article belongs to the Special Issue Green Communications and Networking for IoT)
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Open AccessArticle Wireless Energy Transfer Powered Wireless Sensor Node for Green IoT: Design, Implementation and Evaluation
Sensors 2019, 19(1), 90; https://doi.org/10.3390/s19010090
Received: 15 October 2018 / Revised: 12 December 2018 / Accepted: 21 December 2018 / Published: 28 December 2018
Cited by 2 | PDF Full-text (100036 KB) | HTML Full-text | XML Full-text
Abstract
The number of IoT (Internet of Things) devices is predicted to increase dramatically in the years to come and their manufacturing and maintenance, including both commercial and ecological aspects associated with these, are gaining substantial attention. One of the effective ways of addressing [...] Read more.
The number of IoT (Internet of Things) devices is predicted to increase dramatically in the years to come and their manufacturing and maintenance, including both commercial and ecological aspects associated with these, are gaining substantial attention. One of the effective ways of addressing both these issues at a time is the energy-neutral systems, which operate with the energy harvested from their environment. To address the major problem of this system, namely the low reliability, in the current paper, we develop and study the utility of a system powered solely with the wireless power transfer (WPT) over a radio frequency (RF) channel. In the article, we propose a methodology for developing and implementing a real-life IoT application based on RF WPT. We employ the proposed methodology to develop a WPT-powered solution to sense the temperature and the angular velocity in the rotating industrial environment. First, we discuss the key trade-offs arising when selecting and developing the new components for a WPT system. Then, we present and detail our solutions and describe the results of their evaluations. Finally, we instrument and evaluate the complete system, proving that it is capable of meeting all the design goals and requirements. The results reported in this paper can be of interest to the practitioners, for whom they provide a step-by-step methodology of WPT application development with a practical example. In addition, these results may be valuable for analysts, as they demonstrate many practical interrelations and effects specific to the real-life WPT applications. Full article
(This article belongs to the Special Issue Green Communications and Networking for IoT)
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Open AccessFeature PaperArticle Designing Transmission Strategies for Enhancing Communications in Medical IoT Using Markov Decision Process
Sensors 2018, 18(12), 4450; https://doi.org/10.3390/s18124450
Received: 30 September 2018 / Revised: 15 November 2018 / Accepted: 29 November 2018 / Published: 15 December 2018
Cited by 1 | PDF Full-text (721 KB) | HTML Full-text | XML Full-text
Abstract
The introduction of medical Internet of Things (IoT) for biomedical applications has brought about the era of proactive healthcare. Such advanced medical supervision lies on the foundation of a network of energy-constrained wearable or implantable sensors (or things). These miniaturized battery-powered biosensor nodes [...] Read more.
The introduction of medical Internet of Things (IoT) for biomedical applications has brought about the era of proactive healthcare. Such advanced medical supervision lies on the foundation of a network of energy-constrained wearable or implantable sensors (or things). These miniaturized battery-powered biosensor nodes are placed in, on, or around the human body to measure vital signals to be reported to the sink. This network configuration deployed on a human body is known as the Wireless Body Area Network (WBAN). Strategies are required to restrict energy expenditure of the nodes without degrading performance of WBAN to make medical IoT a green (energy-efficient) and effective paradigm. Direct communication from a node to sink in WBAN may often lead to rapid energy depletion of nodes as well as growing thermal effects on the human body. Hence, multi-hop communication from sources to sink in WBAN is often preferred instead of direct communication with high transmission power. Existing research focuses on designing multi-hop protocols addressing the issues in WBAN routing. However, the ideal conditions for multi-hop routing in preference to single-hop direct delivery is rarely investigated. Accordingly, in this paper an optimal transmission policy for WBAN is developed using Markov Decision Process (MDP) subject to various input conditions such as battery level, event occurrence, packet transmission rate and link quality. Thereafter, a multi-hop routing protocol is designed where routing decisions are made following a pre-computed strategy. The algorithm is simulated, and performance is compared with existing multi-hop protocol for WBAN to demonstrate the viability of the proposed scheme. Full article
(This article belongs to the Special Issue Green Communications and Networking for IoT)
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Open AccessArticle Evaluation of Strategies for the Development of Efficient Code for Raspberry Pi Devices
Sensors 2018, 18(11), 4066; https://doi.org/10.3390/s18114066
Received: 13 October 2018 / Revised: 16 November 2018 / Accepted: 17 November 2018 / Published: 21 November 2018
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Abstract
The Internet of Things (IoT) is faced with challenges that require green solutions and energy-efficient paradigms. Architectures (such as ARM) have evolved significantly in recent years, with improvements to processor efficiency, essential for always-on devices, as a focal point. However, as far as [...] Read more.
The Internet of Things (IoT) is faced with challenges that require green solutions and energy-efficient paradigms. Architectures (such as ARM) have evolved significantly in recent years, with improvements to processor efficiency, essential for always-on devices, as a focal point. However, as far as software is concerned, few approaches analyse the advantages of writing efficient code when programming IoT devices. Therefore, this proposal aims to improve source code optimization to achieve better execution times. In addition, the importance of various techniques for writing efficient code for Raspberry Pi devices is analysed, with the objective of increasing execution speed. A complete set of tests have been developed exclusively for analysing and measuring the improvements achieved when applying each of these techniques. This will raise awareness of the significant impact the recommended techniques can have. Full article
(This article belongs to the Special Issue Green Communications and Networking for IoT)
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Open AccessArticle Adaptive Data Synchronization Algorithm for IoT-Oriented Low-Power Wide-Area Networks
Sensors 2018, 18(11), 4053; https://doi.org/10.3390/s18114053
Received: 5 October 2018 / Revised: 14 November 2018 / Accepted: 17 November 2018 / Published: 20 November 2018
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Abstract
The Internet of Things (IoT) is by now very close to be realized, leading the world towards a new technological era where people’s lives and habits will be definitively revolutionized. Furthermore, the incoming 5G technology promises significant enhancements concerning the Quality of Service [...] Read more.
The Internet of Things (IoT) is by now very close to be realized, leading the world towards a new technological era where people’s lives and habits will be definitively revolutionized. Furthermore, the incoming 5G technology promises significant enhancements concerning the Quality of Service (QoS) in mobile communications. Having billions of devices simultaneously connected has opened new challenges about network management and data exchange rules that need to be tailored to the characteristics of the considered scenario. A large part of the IoT market is pointing to Low-Power Wide-Area Networks (LPWANs) representing the infrastructure for several applications having energy saving as a mandatory goal besides other aspects of QoS. In this context, we propose a low-power IoT-oriented file synchronization protocol that, by dynamically optimizing the amount of data to be transferred, limits the device level of interaction within the network, therefore extending the battery life. This protocol can be adopted with different Layer 2 technologies and provides energy savings at the IoT device level that can be exploited by different applications. Full article
(This article belongs to the Special Issue Green Communications and Networking for IoT)
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Open AccessArticle A Practical Evaluation on RSA and ECC-Based Cipher Suites for IoT High-Security Energy-Efficient Fog and Mist Computing Devices
Sensors 2018, 18(11), 3868; https://doi.org/10.3390/s18113868
Received: 15 October 2018 / Revised: 5 November 2018 / Accepted: 6 November 2018 / Published: 10 November 2018
Cited by 4 | PDF Full-text (3237 KB) | HTML Full-text | XML Full-text
Abstract
The latest Internet of Things (IoT) edge-centric architectures allow for unburdening higher layers from part of their computational and data processing requirements. In the specific case of fog computing systems, they reduce greatly the requirements of cloud-centric systems by processing in fog gateways [...] Read more.
The latest Internet of Things (IoT) edge-centric architectures allow for unburdening higher layers from part of their computational and data processing requirements. In the specific case of fog computing systems, they reduce greatly the requirements of cloud-centric systems by processing in fog gateways part of the data generated by end devices, thus providing services that were previously offered by a remote cloud. Thanks to recent advances in System-on-Chip (SoC) energy efficiency, it is currently possible to create IoT end devices with enough computational power to process the data generated by their sensors and actuators while providing complex services, which in recent years derived into the development of the mist computing paradigm. To allow mist computing nodes to provide the previously mentioned benefits and guarantee the same level of security as in other architectures, end-to-end standard security mechanisms need to be implemented. In this paper, a high-security energy-efficient fog and mist computing architecture and a testbed are presented and evaluated. The testbed makes use of Transport Layer Security (TLS) 1.2 Elliptic Curve Cryptography (ECC) and Rivest-Shamir-Adleman (RSA) cipher suites (that comply with the yet to come TLS 1.3 standard requirements), which are evaluated and compared in terms of energy consumption and data throughput for a fog gateway and two mist end devices. The obtained results allow a conclusion that ECC outperforms RSA in both energy consumption and data throughput for all the tested security levels. Moreover, the importance of selecting a proper ECC curve is demonstrated, showing that, for the tested devices, some curves present worse energy consumption and data throughput than other curves that provide a higher security level. As a result, this article not only presents a novel mist computing testbed, but also provides guidelines for future researchers to find out efficient and secure implementations for advanced IoT devices. Full article
(This article belongs to the Special Issue Green Communications and Networking for IoT)
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Open AccessArticle A Joint Low-Power Cell Search and Frequency Tracking Scheme in NB-IoT Systems for Green Internet of Things
Sensors 2018, 18(10), 3274; https://doi.org/10.3390/s18103274
Received: 4 August 2018 / Revised: 26 September 2018 / Accepted: 27 September 2018 / Published: 29 September 2018
Cited by 1 | PDF Full-text (1779 KB) | HTML Full-text | XML Full-text
Abstract
As a dedicated communication protocol for Internet-of-Things, narrowband internet of things (NB-IoT) needs to establish the communication link rapidly and reduce retransmissions as much as possible to achieve low power consumption and stable performance. To achieve these targets, the low-power scheme of the [...] Read more.
As a dedicated communication protocol for Internet-of-Things, narrowband internet of things (NB-IoT) needs to establish the communication link rapidly and reduce retransmissions as much as possible to achieve low power consumption and stable performance. To achieve these targets, the low-power scheme of the initial cell search and frequency tracking is investigated in this paper. The cell search process can be subdivided into narrowband primary synchronization signal (NPSS) detection and narrowband secondary synchronization signal (NSSS) detection. We present an NPSS detection method whose timing metric is composed of symbol-wise autocorrelation and a dedicated normalization factor. After the detection of NPSS, the symbol timing and fractional frequency offset estimation is implemented in a resource-efficient way. NSSS detection is conducted in the frequency domain with a calculation-reduced algorithm based on the features of NSSS sequences. To compensate the accumulated frequency offset during uplink transmission, a pilot-aided rapid frequency tracking algorithm is proposed. The simulation results of the proposed cell search scheme are outstanding in both normal coverage and extended coverage NB-IoT scenarios, and the accumulated frequency offset can be estimated with high efficiency. Full article
(This article belongs to the Special Issue Green Communications and Networking for IoT)
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Open AccessArticle Resource Allocation in Wireless Powered IoT System: A Mean Field Stackelberg Game-Based Approach
Sensors 2018, 18(10), 3173; https://doi.org/10.3390/s18103173
Received: 11 August 2018 / Revised: 16 September 2018 / Accepted: 18 September 2018 / Published: 20 September 2018
Cited by 1 | PDF Full-text (2637 KB) | HTML Full-text | XML Full-text
Abstract
The IoT system has become a significant component of next generation networks, and drawn a lot of research interest in academia and industry. As the sensor nodes in the IoT system are always battery-limited devices, the power control problem is a serious problem [...] Read more.
The IoT system has become a significant component of next generation networks, and drawn a lot of research interest in academia and industry. As the sensor nodes in the IoT system are always battery-limited devices, the power control problem is a serious problem in the IoT system which needs to be solved. In this paper, we research the resource allocation in the wireless powered IoT system, which includes one hybrid access point (HAP) and many wireless sensor nodes, to obtain the optimal power level for information transmission and energy transfer simultaneously. The relationship between the HAP and the sensor nodes are formulated as the Stackelberg game, and the dynamic variations of the energy for both the HAP and IoT devices are formulated through the dynamic game with mean field control. Then the power control in the wireless powered IoT system is formulated as a mean field Stackelberg game model. We aim to minimize the transmission cost for each sensor node based on optimally power resource allocation. Meanwhile, we attempt to minimize the energy transfer cost based on power control. As a result, the optimal solutions based on the mean field control of the sensor nodes and the HAP are achieved through dynamic programming theory and the law of large numbers, and ε -Nash equilibriums can be obtained. The energy variations for both the sensor nodes and HAP after the control of resource allocation based on the proposed approach are verified based on the simulation results. Full article
(This article belongs to the Special Issue Green Communications and Networking for IoT)
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Open AccessArticle An Energy Conserving and Transmission Radius Adaptive Scheme to Optimize Performance of Energy Harvesting Sensor Networks
Sensors 2018, 18(9), 2885; https://doi.org/10.3390/s18092885
Received: 2 August 2018 / Revised: 23 August 2018 / Accepted: 27 August 2018 / Published: 31 August 2018
Cited by 16 | PDF Full-text (18351 KB) | HTML Full-text | XML Full-text
Abstract
In energy harvesting wireless sensor networks (EHWSNs), the energy tension of the network can be relieved by obtaining the energy from the surrounding environment, but the cost on hardware cannot be ignored. Therefore, how to minimize the cost of energy harvesting hardware to [...] Read more.
In energy harvesting wireless sensor networks (EHWSNs), the energy tension of the network can be relieved by obtaining the energy from the surrounding environment, but the cost on hardware cannot be ignored. Therefore, how to minimize the cost of energy harvesting hardware to reduce the network deployment cost, and further optimize the network performance, is still a challenging issue in EHWSNs. In this paper, an energy conserving and transmission radius adaptive (ECTRA) scheme is proposed to reduce the cost and optimize the performance of solar-based EHWSNs. There are two main innovations of the ECTRA scheme. Firstly, an energy conserving approach is proposed to conserve energy and avoid outage for the nodes in hotspots, which are the bottleneck of the whole network. The novelty of this scheme is adaptively rotating the transmission radius. In this way, the nodes with maximum energy consumption are rotated, balancing energy consumption between nodes and reducing the maximum energy consumption in the network. Therefore, the battery storage capacity of nodes and the cost on hardware. Secondly, the ECTRA scheme selects a larger transmission radius for rotation when the node can absorb enough energy from the surroundings. The advantages of using this method are: (a) reducing the energy consumption of nodes in near-sink areas, thereby reducing the maximum energy consumption and allowing the node of the hotspot area to conserve energy, in order to prevent the node from outage. Hence, the network deployment costs can be further reduced; (b) reducing the network delay. When a larger transmission radius is used to transmit data in the network, fewer hops are needed by data packet to the sink. After the theoretical analyses, the results show the following advantages compared with traditional method. Firstly, the ECTRA scheme can effectively reduce deployment costs by 29.58% without effecting the network performance as shown in experiment analysis; Secondly, the ECTRA scheme can effectively reduce network data transmission delay by 44–71%; Thirdly, the ECTRA scheme shows a better balance in energy consumption and the maximum energy consumption is reduced by 27.89%; And lastly, the energy utilization rate is effectively improved by 30.09–55.48%. Full article
(This article belongs to the Special Issue Green Communications and Networking for IoT)
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Open AccessArticle Green Compressive Sampling Reconstruction in IoT Networks
Sensors 2018, 18(8), 2735; https://doi.org/10.3390/s18082735
Received: 8 July 2018 / Revised: 6 August 2018 / Accepted: 17 August 2018 / Published: 20 August 2018
Cited by 1 | PDF Full-text (883 KB) | HTML Full-text | XML Full-text
Abstract
In this paper, we address the problem of green Compressed Sensing (CS) reconstruction within Internet of Things (IoT) networks, both in terms of computing architecture and reconstruction algorithms. The approach is novel since, unlike most of the literature dealing with energy efficient gathering [...] Read more.
In this paper, we address the problem of green Compressed Sensing (CS) reconstruction within Internet of Things (IoT) networks, both in terms of computing architecture and reconstruction algorithms. The approach is novel since, unlike most of the literature dealing with energy efficient gathering of the CS measurements, we focus on the energy efficiency of the signal reconstruction stage given the CS measurements. As a first novel contribution, we present an analysis of the energy consumption within the IoT network under two computing architectures. In the first one, reconstruction takes place within the IoT network and the reconstructed data are encoded and transmitted out of the IoT network; in the second one, all the CS measurements are forwarded to off-network devices for reconstruction and storage, i.e., reconstruction is off-loaded. Our analysis shows that the two architectures significantly differ in terms of consumed energy, and it outlines a theoretically motivated criterion to select a green CS reconstruction computing architecture. Specifically, we present a suitable decision function to determine which architecture outperforms the other in terms of energy efficiency. The presented decision function depends on a few IoT network features, such as the network size, the sink connectivity, and other systems’ parameters. As a second novel contribution, we show how to overcome classical performance comparison of different CS reconstruction algorithms usually carried out w.r.t. the achieved accuracy. Specifically, we consider the consumed energy and analyze the energy vs. accuracy trade-off. The herein presented approach, jointly considering signal processing and IoT network issues, is a relevant contribution for designing green compressive sampling architectures in IoT networks. Full article
(This article belongs to the Special Issue Green Communications and Networking for IoT)
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Open AccessArticle Energy-Aware Control of Data Compression and Sensing Rate for Wireless Rechargeable Sensor Networks
Sensors 2018, 18(8), 2609; https://doi.org/10.3390/s18082609
Received: 9 July 2018 / Revised: 7 August 2018 / Accepted: 8 August 2018 / Published: 9 August 2018
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Abstract
Wireless rechargeable sensor nodes can collect additional data, which leads to an increase in the precision of data analysis, when enough harvested energy is acquired. However, because such nodes increase the amount of sensory data, some nodes (especially near the sink) may blackout [...] Read more.
Wireless rechargeable sensor nodes can collect additional data, which leads to an increase in the precision of data analysis, when enough harvested energy is acquired. However, because such nodes increase the amount of sensory data, some nodes (especially near the sink) may blackout because more transmitted data can make relaying nodes expend more energy. In this paper, we propose an energy-aware control scheme of data compression and sensing rate to maximize the amount of data collected at the sink, while minimizing the blackout time. In this scheme, each dominant node determines the data quota that all its descendant nodes can transmit during the next period, which operates with an efficient energy allocation scheme. Then, the node receiving the quota selects an appropriate data compression algorithm and sensing rate according to both its quota and allocated energy during the next period, so as not to exhaust the energy of nodes near the sink. Experimental results verify that the proposed scheme collects more data than other schemes, while suppressing the blackout of nodes. We also found that it adapts better to changes in node density and harvesting environments. Full article
(This article belongs to the Special Issue Green Communications and Networking for IoT)
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Open AccessArticle Energy-Aware Control of Error Correction Rate for Solar-Powered Wireless Sensor Networks
Sensors 2018, 18(8), 2599; https://doi.org/10.3390/s18082599
Received: 24 June 2018 / Revised: 2 August 2018 / Accepted: 5 August 2018 / Published: 8 August 2018
Cited by 1 | PDF Full-text (1290 KB) | HTML Full-text | XML Full-text
Abstract
In a wireless sensor network (WSN) environment with frequent errors, forward error correction (FEC) is usually employed at the link layer to achieve reliable transmission. In the FEC scheme, the error correction rate varies depending on the length of parity used for the [...] Read more.
In a wireless sensor network (WSN) environment with frequent errors, forward error correction (FEC) is usually employed at the link layer to achieve reliable transmission. In the FEC scheme, the error correction rate varies depending on the length of parity used for the recovery of broken data. The longer the parity length, the higher the possible error correction rate. However, this also means that the energy consumption increases. Meanwhile, in a solar-powered WSN, the energy of each node can be periodically collected, but the amount of collected energy varies drastically depending on the harvesting environment, including factors such as the weather, season and time of day. Therefore, each node must control energy consumption according to the energy harvesting rate. The scheme proposed in this study executes this control by adaptively adjusting the parity length of FEC according to the given energy budget of a node for the next period. This means that the error recovery rate can be increased as much as possible without adversely affecting the blackout time. Simulation results show that the proposed scheme improves the amount of data collected from the entire network for each environment compared with previous schemes. Full article
(This article belongs to the Special Issue Green Communications and Networking for IoT)
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Open AccessArticle On Maximizing the Throughput of Packet Transmission under Energy Constraints
Sensors 2018, 18(7), 2018; https://doi.org/10.3390/s18072018
Received: 3 May 2018 / Revised: 16 June 2018 / Accepted: 18 June 2018 / Published: 23 June 2018
PDF Full-text (1821 KB) | HTML Full-text | XML Full-text
Abstract
More and more Internet of Things (IoT) wireless devices have been providing ubiquitous services over the recent years. Since most of these devices are powered by batteries, a fundamental trade-off to be addressed is the depleted energy and the achieved data throughput in [...] Read more.
More and more Internet of Things (IoT) wireless devices have been providing ubiquitous services over the recent years. Since most of these devices are powered by batteries, a fundamental trade-off to be addressed is the depleted energy and the achieved data throughput in wireless data transmission. By exploiting the rate-adaptive capacities of wireless devices, most existing works on energy-efficient data transmission try to design rate-adaptive transmission policies to maximize the amount of transmitted data bits under the energy constraints of devices. Such solutions, however, cannot apply to scenarios where data packets have respective deadlines and only integrally transmitted data packets contribute. Thus, this paper introduces a notion of weighted throughput, which measures how much total value of data packets are successfully and integrally transmitted before their own deadlines. By designing efficient rate-adaptive transmission policies, this paper aims to make the best use of the energy and maximize the weighted throughput. What is more challenging but with practical significance, we consider the fading effect of wireless channels in both offline and online scenarios. In the offline scenario, we develop an optimal algorithm that computes the optimal solution in pseudo-polynomial time, which is the best possible solution as the problem undertaken is NP-hard. In the online scenario, we propose an efficient heuristic algorithm based on optimal properties derived for the optimal offline solution. Simulation results validate the efficiency of the proposed algorithm. Full article
(This article belongs to the Special Issue Green Communications and Networking for IoT)
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Open AccessArticle FPGA-Based High-Performance Embedded Systems for Adaptive Edge Computing in Cyber-Physical Systems: The ARTICo3 Framework
Sensors 2018, 18(6), 1877; https://doi.org/10.3390/s18061877
Received: 6 April 2018 / Revised: 5 June 2018 / Accepted: 5 June 2018 / Published: 8 June 2018
Cited by 3 | PDF Full-text (5520 KB) | HTML Full-text | XML Full-text
Abstract
Cyber-Physical Systems are experiencing a paradigm shift in which processing has been relocated to the distributed sensing layer and is no longer performed in a centralized manner. This approach, usually referred to as Edge Computing, demands the use of hardware platforms that are [...] Read more.
Cyber-Physical Systems are experiencing a paradigm shift in which processing has been relocated to the distributed sensing layer and is no longer performed in a centralized manner. This approach, usually referred to as Edge Computing, demands the use of hardware platforms that are able to manage the steadily increasing requirements in computing performance, while keeping energy efficiency and the adaptability imposed by the interaction with the physical world. In this context, SRAM-based FPGAs and their inherent run-time reconfigurability, when coupled with smart power management strategies, are a suitable solution. However, they usually fail in user accessibility and ease of development. In this paper, an integrated framework to develop FPGA-based high-performance embedded systems for Edge Computing in Cyber-Physical Systems is presented. This framework provides a hardware-based processing architecture, an automated toolchain, and a runtime to transparently generate and manage reconfigurable systems from high-level system descriptions without additional user intervention. Moreover, it provides users with support for dynamically adapting the available computing resources to switch the working point of the architecture in a solution space defined by computing performance, energy consumption and fault tolerance. Results show that it is indeed possible to explore this solution space at run time and prove that the proposed framework is a competitive alternative to software-based edge computing platforms, being able to provide not only faster solutions, but also higher energy efficiency for computing-intensive algorithms with significant levels of data-level parallelism. Full article
(This article belongs to the Special Issue Green Communications and Networking for IoT)
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Open AccessArticle An Energy-Efficient Compressive Image Coding for Green Internet of Things (IoT)
Sensors 2018, 18(4), 1231; https://doi.org/10.3390/s18041231
Received: 20 March 2018 / Revised: 14 April 2018 / Accepted: 14 April 2018 / Published: 17 April 2018
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Abstract
Aimed at a low-energy consumption of Green Internet of Things (IoT), this paper presents an energy-efficient compressive image coding scheme, which provides compressive encoder and real-time decoder according to Compressive Sensing (CS) theory. The compressive encoder adaptively measures each image block based on [...] Read more.
Aimed at a low-energy consumption of Green Internet of Things (IoT), this paper presents an energy-efficient compressive image coding scheme, which provides compressive encoder and real-time decoder according to Compressive Sensing (CS) theory. The compressive encoder adaptively measures each image block based on the block-based gradient field, which models the distribution of block sparse degree, and the real-time decoder linearly reconstructs each image block through a projection matrix, which is learned by Minimum Mean Square Error (MMSE) criterion. Both the encoder and decoder have a low computational complexity, so that they only consume a small amount of energy. Experimental results show that the proposed scheme not only has a low encoding and decoding complexity when compared with traditional methods, but it also provides good objective and subjective reconstruction qualities. In particular, it presents better time-distortion performance than JPEG. Therefore, the proposed compressive image coding is a potential energy-efficient scheme for Green IoT. Full article
(This article belongs to the Special Issue Green Communications and Networking for IoT)
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