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Special Issue "Green IT and IT for Smart Energy Savings"

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A special issue of Energies (ISSN 1996-1073).

Deadline for manuscript submissions: closed (31 May 2014)

Special Issue Editor

Guest Editor
Prof. Dr. Erol Gelenbe (Website)

Intelligent Systems and Networks, Imperial College London, London SW7 2AZ, UK
Interests: energy optimization; energy packet networks; networked systems; physical and biological networks; probability models; natural computation

Special Issue Information

Dear Colleagues,

Information technology (IT), including data centers, communication networks, and office or individual computer and mobile devices, are known to be responsible for roughly 2% of CO2 emissions world-wide, or roughly as much as the impact of air travel. Also, by some reports information technology consumes as much as 5% of all the electricity consumption in the world, and this ratio is increasing, despite major successes in reducing the energy consumption of data processing and communication devices per amount of processing or communication that is carried out across the world. The ever increasing need to communicate through technology, and to conduct our affairs based on information laboriously gleaned from huge data sets, are the major culprits in our world today.

At the same time, IT also has the potential to offer huge energy savings in all human activities such as business, daily work, education and travel, and even energy generation and distribution, through greater efficiency and optimization in the manner in which we conduct our lives and run our homes, offices, factories and vehicles.

Thus this special issue will address both these very important aspects that tie IT and Energy, from a principled engineering and scientific perspective, by publishing carefully refereed papers that establish new methods and show how IT can deliver the best quality of service and quality of experience with the minimum required energy expenditures; how cost functions that combine the quality of the value delivered by ICT (Information and communications technology) and its energy expenditure can be minimized; and how IT can effectively reduce energy consumption in other fields. Papers with validated empirical content and sound theoretical studies are welcome and are encouraged for submission.

Prof. Dr. Erol Gelenbe
Guest Editor

Submission

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. Papers will be published continuously (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as 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 refereed through a 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 monthly 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 1400 CHF (Swiss Francs).

Keywords

  • green IT
  • smart systems for energy savings
  • energy consumption by ICT
  • metrics combining quality of service and energy consumption
  • hardware and software energy measurements
  • quality of service and energy trade-offs
  • controlling energy flows with IT
  • foundations of the smart grid
  • energy savings through IT

Published Papers (6 papers)

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Research

Open AccessArticle Synchronising Energy Harvesting and Data Packets in a Wireless Sensor
Energies 2015, 8(1), 356-369; doi:10.3390/en8010356
Received: 20 November 2014 / Accepted: 26 December 2014 / Published: 5 January 2015
Cited by 6 | PDF Full-text (177 KB) | HTML Full-text | XML Full-text
Abstract
We consider a wireless sensor node that gathers energy through harvesting and reaps data through sensing. The node has a wireless transmitter that sends out a data packet whenever there is at least one “energy packet” and one “data packet”, where an [...] Read more.
We consider a wireless sensor node that gathers energy through harvesting and reaps data through sensing. The node has a wireless transmitter that sends out a data packet whenever there is at least one “energy packet” and one “data packet”, where an energy packet represents the amount of accumulated energy at the node that can allow the transmission of a data packet. We show that such a system is unstable when both the energy storage space and the data backlog buffer approach infinity, and we obtain the stable stationary solution when both buffers are finite. We then show that if a single energy packet is not sufficient to transmit a data packet, there are conditions under which the system is stable, and we provide the explicit expression for the joint probability distribution of the number of energy and data packets in the system. Since the two flows of energy and data can be viewed as flows that are instantaneously synchronised, this paper also provides a mathematical analysis of a fundamental problem in computer science related to the stability of the “join” synchronisation primitive. Full article
(This article belongs to the Special Issue Green IT and IT for Smart Energy Savings)
Open AccessCommunication Performance Analyses of Renewable and Fuel Power Supply Systems for Different Base Station Sites
Energies 2014, 7(12), 7816-7846; doi:10.3390/en7127816
Received: 11 April 2014 / Revised: 10 November 2014 / Accepted: 10 November 2014 / Published: 25 November 2014
Cited by 1 | PDF Full-text (3696 KB) | HTML Full-text | XML Full-text
Abstract
Base station sites (BSSs) powered with renewable energy sources have gained the attention of cellular operators during the last few years. This is because such “green” BSSs impose significant reductions in the operational expenditures (OPEX) of telecom operators due to the possibility [...] Read more.
Base station sites (BSSs) powered with renewable energy sources have gained the attention of cellular operators during the last few years. This is because such “green” BSSs impose significant reductions in the operational expenditures (OPEX) of telecom operators due to the possibility of on-site renewable energy harvesting. In this paper, the green BSSs power supply system parameters detected through remote and centralized real time sensing are presented. An implemented sensing system based on a wireless sensor network enables reliable collection and post-processing analyses of many parameters, such as: total charging/discharging current of power supply system, battery voltage and temperature, wind speed, etc. As an example, yearly sensing results for three different BSS configurations powered by solar and/or wind energy are discussed in terms of renewable energy supply (RES) system performance. In the case of powering those BSS with standalone systems based on a fuel generator, the fuel consumption models expressing interdependence among the generator load and fuel consumption are proposed. This has allowed energy-efficiency comparison of the fuel powered and RES systems, which is presented in terms of the OPEX and carbon dioxide (CO2) reductions. Additionally, approaches based on different BSS air-conditioning systems and the on/off regulation of a daily fuel generator activity are proposed and validated in terms of energy and capital expenditure (CAPEX) savings. Full article
(This article belongs to the Special Issue Green IT and IT for Smart Energy Savings)
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Open AccessArticle Powering-up Wireless Sensor Nodes Utilizing Rechargeable Batteries and an Electromagnetic Vibration Energy Harvesting System
Energies 2014, 7(10), 6323-6339; doi:10.3390/en7106323
Received: 9 June 2014 / Revised: 29 August 2014 / Accepted: 1 September 2014 / Published: 2 October 2014
Cited by 4 | PDF Full-text (3001 KB) | HTML Full-text | XML Full-text
Abstract
This paper presents a wireless sensor node (WSN) system where an electromagnetic (EM) energy harvester is utilized for charging its rechargeable batteries while the system is operational. The capability and the performance of an in-house low-frequency EM energy harvester for charging rechargeable [...] Read more.
This paper presents a wireless sensor node (WSN) system where an electromagnetic (EM) energy harvester is utilized for charging its rechargeable batteries while the system is operational. The capability and the performance of an in-house low-frequency EM energy harvester for charging rechargeable NiMH batteries were experimentally verified in comparison to a regular battery charger. Furthermore, the power consumption of MicaZ motes, used as the WSN, was evaluated in detail for different operation conditions. The battery voltage and current were experimentally monitored during the operation of the MicaZ sensor node equipped with the EM vibration energy harvester. A compact (24.5 cm3) in-house EM energy harvester provides approximately 65 µA charging current to the batteries when excited by 0.4 g acceleration at 7.4 Hz. It has been shown that the current demand of the MicaZ mote can be compensated for by the energy harvester for a specific low-power operation scenario, with more than a 10-fold increase in the battery lifetime. The presented results demonstrate the autonomous operation of the WSN, with the utilization of a vibration-based energy harvester. Full article
(This article belongs to the Special Issue Green IT and IT for Smart Energy Savings)
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Open AccessArticle A Semantic Middleware Architecture Focused on Data and Heterogeneity Management within the Smart Grid
Energies 2014, 7(9), 5953-5994; doi:10.3390/en7095953
Received: 3 June 2014 / Revised: 23 August 2014 / Accepted: 2 September 2014 / Published: 10 September 2014
Cited by 5 | PDF Full-text (2615 KB) | HTML Full-text | XML Full-text
Abstract
There is an increasing tendency of turning the current power grid, essentially unaware of variations in electricity demand and scattered energy sources, into something capable of bringing a degree of intelligence by using tools strongly related to information and communication technologies, thus [...] Read more.
There is an increasing tendency of turning the current power grid, essentially unaware of variations in electricity demand and scattered energy sources, into something capable of bringing a degree of intelligence by using tools strongly related to information and communication technologies, thus turning into the so-called Smart Grid. In fact, it could be considered that the Smart Grid is an extensive smart system that spreads throughout any area where power is required, providing a significant optimization in energy generation, storage and consumption. However, the information that must be treated to accomplish these tasks is challenging both in terms of complexity (semantic features, distributed systems, suitable hardware) and quantity (consumption data, generation data, forecasting functionalities, service reporting), since the different energy beneficiaries are prone to be heterogeneous, as the nature of their own activities is. This paper presents a proposal on how to deal with these issues by using a semantic middleware architecture that integrates different components focused on specific tasks, and how it is used to handle information at every level and satisfy end user requests. Full article
(This article belongs to the Special Issue Green IT and IT for Smart Energy Savings)
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Open AccessArticle Shadow Replication: An Energy-Aware, Fault-Tolerant Computational Model for Green Cloud Computing
Energies 2014, 7(8), 5151-5176; doi:10.3390/en7085151
Received: 4 June 2014 / Revised: 30 July 2014 / Accepted: 5 August 2014 / Published: 12 August 2014
Cited by 1 | PDF Full-text (881 KB) | HTML Full-text | XML Full-text
Abstract
As the demand for cloud computing continues to increase, cloud service providers face the daunting challenge to meet the negotiated SLA agreement, in terms of reliability and timely performance, while achieving cost-effectiveness. This challenge is increasingly compounded by the increasing likelihood of [...] Read more.
As the demand for cloud computing continues to increase, cloud service providers face the daunting challenge to meet the negotiated SLA agreement, in terms of reliability and timely performance, while achieving cost-effectiveness. This challenge is increasingly compounded by the increasing likelihood of failure in large-scale clouds and the rising impact of energy consumption and CO2 emission on the environment. This paper proposes Shadow Replication, a novel fault-tolerance model for cloud computing, which seamlessly addresses failure at scale, while minimizing energy consumption and reducing its impact on the environment. The basic tenet of the model is to associate a suite of shadow processes to execute concurrently with the main process, but initially at a much reduced execution speed, to overcome failures as they occur. Two computationally-feasible schemes are proposed to achieve Shadow Replication. A performance evaluation framework is developed to analyze these schemes and compare their performance to traditional replication-based fault tolerance methods, focusing on the inherent tradeoff between fault tolerance, the specified SLA and profit maximization. The results show that Shadow Replication leads to significant energy reduction, and is better suited for compute-intensive execution models, where up to 30% more profit increase can be achieved due to reduced energy consumption. Full article
(This article belongs to the Special Issue Green IT and IT for Smart Energy Savings)
Open AccessArticle Energy-Efficient Power Allocation Using Probabilistic Interference Model for OFDM-Based Green Cognitive Radio Networks
Energies 2014, 7(4), 2535-2557; doi:10.3390/en7042535
Received: 20 January 2014 / Revised: 8 April 2014 / Accepted: 9 April 2014 / Published: 22 April 2014
Cited by 3 | PDF Full-text (348 KB) | HTML Full-text | XML Full-text
Abstract
We study the energy-efficient power allocation techniques for OFDM-based cognitive radio (CR) networks, where a CR transmitter is communicating with CR receivers on a channel borrowed from licensed primary users (PUs). Due to non-orthogonality of the transmitted signals in the adjacent bands, [...] Read more.
We study the energy-efficient power allocation techniques for OFDM-based cognitive radio (CR) networks, where a CR transmitter is communicating with CR receivers on a channel borrowed from licensed primary users (PUs). Due to non-orthogonality of the transmitted signals in the adjacent bands, both the PU and the cognitive secondary user (SU) cause mutual-interference. We assume that the statistical channel state information between the cognitive transmitter and the primary receiver is known. The secondary transmitter maintains a specified statistical mutual-interference limits for all the PUs communicating in the adjacent channels. Our goal is to allocate subcarrier power for the SU so that the energy efficiency metric is optimized as well as the mutual-interference on all the active PU bands are below specified bounds. We show that the green power loading problem is a fractional programming problem. We use Charnes-Cooper transformation technique to obtain an equivalent concave optimization problem for what the solution can be readily obtained. We also propose iterative Dinkelbach method using parametric objective function for the fractional program. Numerical results are given to show the effect of different interference parameters, rate and power thresholds, and number of PUs. Full article
(This article belongs to the Special Issue Green IT and IT for Smart Energy Savings)

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