Special Issue "Energy-Efficient Computing and Communication "

A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "Smart Grids and Microgrids".

Deadline for manuscript submissions: closed (28 February 2020).

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

Special Issue Editor

Prof. Dr. Sangheon Pack
Website
Guest Editor
School of Electrical Engineering, Korea University, Seoul, South Korea
Interests: 5G; IoT; vehicular networking; energy harvesting; simultaneous wireless information and power transfer (SWIPT); vehicle-to-grid (V2G); network softwarization
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Special Issue Information

Dear Colleagues,

It is well-known that information and communication technologies (ICT) contribute up to 10% of world power consumption. In particular, communications and computing systems are indispensable elements in ICT, and thus how to improve the energy efficiency in communications and computing systems becomes one of the most important issues to realize green ICT. Even though a number of studies have been conducted in the literature, most of them focus on one side—in either communications or computing systems. However, salient features in communications and computing systems should be jointly considered, and novel holistic approaches across communications and computing systems are strongly required to implement energy-efficient systems. In addition, emerging systems such as energy-harvesting IoT devices, cyber-physical systems (CPSs), autonomous vehicles (AVs), and unmanned aerial vehicles (UAVs) require new approaches to satisfy their strict energy consumption requirements in mission-critical situations.

The goal of this Special Issue is to disseminate the recent advances in energy-efficient communications and computing systems. Review and survey papers on these topics are also welcome.

Potential topics include, but are not limited to, the following:

  • energy-efficient communications: from physical layer to application layer;
  • energy-efficient computing systems;
  • energy-efficient network architecture: through SDN/NFV/network slicing;
  • energy-efficient system design;
  • energy-efficient Internet of Things (IoT) and Industrial IoT (IIoT);
  • energy-efficient edge/fog/cloud computing;
  • new approaches for energy-efficient computing and communications (e.g., AI/ML and data-driven approaches);
  • new performance metrics on energy efficiency in emerging systems;
  • energy harvesting and simultaneous wireless information and power transfer (SWIPT);
  • Smart Grid and Vehicle-to-Grid (V2G);
  • standardization and open source activities for energy efficient systems.

Prof. Sangheon Pack
Guest Editor

Manuscript Submission Information

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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. Energies 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

  • energy-efficient communications
  • energy-efficient computing systems
  • energy-efficient networking
  • energy-harvesting techniques
  • Internet of Things (IoT)
  • edge and fog computing

Published Papers (6 papers)

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Research

Open AccessArticle
Energy-Efficient Topology Control for UAV Networks
Energies 2019, 12(23), 4523; https://doi.org/10.3390/en12234523 - 27 Nov 2019
Cited by 1
Abstract
Following striking developments in Unmanned Aerial Vehicle (UAV) technology, the use of UAVs has been researched in various industrial fields. Furthermore, a number of studies on operating multiple autonomous networking UAVs suggest a potential to use UAVs in large-scale environments. To achieve efficiency [...] Read more.
Following striking developments in Unmanned Aerial Vehicle (UAV) technology, the use of UAVs has been researched in various industrial fields. Furthermore, a number of studies on operating multiple autonomous networking UAVs suggest a potential to use UAVs in large-scale environments. To achieve efficiency of performance in multi-UAV operations, it is essential to consider a variety of factors in UAV network conditions, such as energy efficiency, network overhead, and so on. In this paper, we propose a novel scheme that improves the energy efficiency and network throughputs by controlling the topology of the network. Our proposed network topology control scheme functions between the data link layer (L3) and the network layer (L2). Accordingly, it can be considered to be layer 2.5 in the network hierarchy model. In addition, our methodology includes swarm intelligence, meaning that whole topology control can be generated with less cost and effort, and without a centralized controller. Our experimental results confirm the notable performance of our proposed method compared to previous approaches. Full article
(This article belongs to the Special Issue Energy-Efficient Computing and Communication ) Printed Edition available
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Open AccessArticle
A Novel Coding Metasurface for Wireless Power Transfer Applications
Energies 2019, 12(23), 4488; https://doi.org/10.3390/en12234488 - 25 Nov 2019
Abstract
We propose and implement a novel 1-bit coding metasurface that is capable of focusing and steering beam for enhancing power transfer efficiency of the electromagnetic (EM) wave-based wireless power transfer systems. The proposed metasurface comprises 16 × 16 unit cells which are designed [...] Read more.
We propose and implement a novel 1-bit coding metasurface that is capable of focusing and steering beam for enhancing power transfer efficiency of the electromagnetic (EM) wave-based wireless power transfer systems. The proposed metasurface comprises 16 × 16 unit cells which are designed with a fractal structure and the operating frequency of 5.8 GHz. One PIN diode is incorporated within each unit cell and enables two states with 180 ° phase change of the reflected signal at the unit cell. The two states of the unit cell correspond to the ON and OFF states of the PIN diode or “0” and “1” coding in the metasurface. By appropriately handling the ON/OFF states of the coding metasurface, we can control the reflected EM wave impinged on the metasurface. To verify the working ability of the coding metasurface, a prototype metasurface with a control board has been fabricated and measured. The results showed that the coding metasurface is capable of focusing beam to desired direction. For practical scenarios, we propose an adaptive optimal phase control scheme for focusing the beam to a mobile target. Furthermore, we prove that the proposed adaptive optimal phase control scheme outperforms the random phase control and beam synthesis schemes. Full article
(This article belongs to the Special Issue Energy-Efficient Computing and Communication ) Printed Edition available
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Open AccessArticle
Two-Stage Computation Offloading Scheduling Algorithm for Energy-Harvesting Mobile Edge Computing
Energies 2019, 12(22), 4367; https://doi.org/10.3390/en12224367 - 15 Nov 2019
Abstract
Recently, mobile edge computing (MEC) technology was developed to mitigate the overload problem in networks and cloud systems. An MEC system computes the offloading computation tasks from resource-constrained Internet of Things (IoT) devices. In addition, several convergence technologies with renewable energy resources (RERs) [...] Read more.
Recently, mobile edge computing (MEC) technology was developed to mitigate the overload problem in networks and cloud systems. An MEC system computes the offloading computation tasks from resource-constrained Internet of Things (IoT) devices. In addition, several convergence technologies with renewable energy resources (RERs) such as photovoltaics have been proposed to improve the survivability of IoT systems. This paper proposes an MEC integrated with RER system, which is referred to as energy-harvesting (EH) MEC. Since the energy supply of RERs is unstable due to various reasons, EH MEC needs to consider the state-of-charge (SoC) of the battery to ensure system stability. Therefore, in this paper, we propose an offloading scheduling algorithm considering the battery of EH MEC as well as the service quality of experience (QoE). The proposed scheduling algorithm consists of a two-stage operation, where the first stage consists of admission control of the offloading requests and the second stage consists of computation frequency scheduling of the MEC server. For the first stage, a non-convex optimization problem is designed considering the computation capability, SoC, and request deadline. To solve the non-convex problem, a greedy algorithm is proposed to obtain approximate optimal solutions. In the second stage, based on Lyapunov optimization, a low-complexity algorithm is proposed, which considers both the workload queue and battery stability. In addition, performance evaluations of the proposed algorithm were conducted via simulation. However, this paper has a limitation in terms of verifying in a real-world scenario. Full article
(This article belongs to the Special Issue Energy-Efficient Computing and Communication ) Printed Edition available
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Open AccessArticle
Energy Efficient Cooperative Computation Algorithm in Energy Harvesting Internet of Things
Energies 2019, 12(21), 4050; https://doi.org/10.3390/en12214050 - 24 Oct 2019
Cited by 2
Abstract
The limited battery capacity of Internet of Things (IoT) devices is a major deployment barrier for IoT-based computing systems. In this paper, we propose an energy efficient cooperative computation algorithm (EE-CCA). In an EE-CCA, a pair of IoT devices decide whether to offload [...] Read more.
The limited battery capacity of Internet of Things (IoT) devices is a major deployment barrier for IoT-based computing systems. In this paper, we propose an energy efficient cooperative computation algorithm (EE-CCA). In an EE-CCA, a pair of IoT devices decide whether to offload some parts of the task to the opponent by considering their energy levels and the task deadline. To minimize the energy outage probability while completing most of tasks before their deadlines, we formulate a constraint Markov decision process (CMDP) problem and the optimal offloading strategy is obtained by linear programming (LP). Meanwhile, an optimization problem of finding pairs of IoT devices (i.e., IoT device pairing problem) is formulated under the optimal offloading strategy. Evaluation results demonstrate that the EE-CCA can reduce the energy outage probability up to 78 % compared with the random offloading scheme while completing tasks before their deadlines with high probability. Full article
(This article belongs to the Special Issue Energy-Efficient Computing and Communication ) Printed Edition available
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Open AccessArticle
Energy-Neutral Operation Based on Simultaneous Wireless Information and Power Transfer for Wireless Powered Sensor Networks
Energies 2019, 12(20), 3823; https://doi.org/10.3390/en12203823 - 10 Oct 2019
Cited by 1
Abstract
For energy-neutral operation (ENO) of wireless sensor networks (WSNs), we apply a wireless powered communication network (WPCN) to a WSN with a hierarchical structure. In this hierarchical wireless powered sensor network (WPSN), sensor nodes with high harvesting energies and good link budgets have [...] Read more.
For energy-neutral operation (ENO) of wireless sensor networks (WSNs), we apply a wireless powered communication network (WPCN) to a WSN with a hierarchical structure. In this hierarchical wireless powered sensor network (WPSN), sensor nodes with high harvesting energies and good link budgets have energy remaining after sending their data to the cluster head (CH), whereas the CH suffers from energy scarcity. Thus, we apply the simultaneous wireless information and power transfer (SWIPT) technique to the considered WPSN so that the sensor nodes can transfer their remaining energy to the CH while transmitting data in a cooperative manner. To maximize the achievable rate of sensing data while guaranteeing ENO, we propose a novel ENO framework, which provides a frame structure for SWIPT operation, rate improvement subject to ENO, SWIPT ratio optimization, as well as clustering and CH selection algorithm. The results of extensive simulations demonstrate that the proposed ENO based on SWIPT significantly improves the achievable rate and reduces the energy dissipated in the network while guaranteeing ENO, in comparison with the conventional schemes without SWIPT. Full article
(This article belongs to the Special Issue Energy-Efficient Computing and Communication ) Printed Edition available
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Open AccessArticle
Power Control Method for Energy Efficient Buffer-Aided Relay Systems
Energies 2019, 12(17), 3234; https://doi.org/10.3390/en12173234 - 22 Aug 2019
Abstract
In this paper, a power control method is proposed for a buffer-aided relay node (RN) to enhance the energy efficiency of the RN system. By virtue of a buffer, the RN can reserve the data at the buffer when the the channel gain [...] Read more.
In this paper, a power control method is proposed for a buffer-aided relay node (RN) to enhance the energy efficiency of the RN system. By virtue of a buffer, the RN can reserve the data at the buffer when the the channel gain between an RN and a destination node (DN) is weaker than that between SN and RN. The RN then opportunistically forward the reserved data in the buffer according to channel condition between the RN and the DN. By exploiting the buffer, RN reduces transmit power when it reduces the transmit data rate and reserve the data in the buffer. Therefore, without any total throughput reduction, the power consumption of RN can be reduced, resulting in the energy efficiency (EE) improvement of the RN system. Furthermore, for the power control, we devise a simple power control method based on a two-dimensional surface fitting model of an optimal transmit power of RN. The proposed RN power control method is readily and locally implementable at the RN, and it can significantly improve EE of the RN compared to the fixed power control method and the spectral efficiency based method as verified by the rigorous numerical results. Full article
(This article belongs to the Special Issue Energy-Efficient Computing and Communication ) Printed Edition available
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