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Reliable and Sustainable Cloud Computing, IoT and Blockchain Applications for Smart Grids

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Prof. Dr. Tihana Galinac Grbac

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Faculty of Engineering, Juraj Dobrila University of Pula, 52100 Pula, Croatia
Interests: complex systems; software and system engineering; topological analysis; sustainability; reliability; security

Special Issue Information

Dear Colleagues,

New technologies shape our future. We are witnessing increased digitalization and a transformation into a digital and intelligent society. As result, software appears in every aspect of human life. Software is growing increasingly complex and is frequently used as middleware, interconnecting various application domains and having to satisfy reliable and sustainable operation in harmony with a variety of interconnecting systems. The dominant technologies are blockchain services, Internet of things and cloud. In this setup, numerous computing issues have to be resolved. We still lack the systematic knowledge needed to engineer these varieties in software systems across various application domains that are interconnected within smart grids and cope with their integration, interconnection and complexity.

In order to address this research gap, this Special Issue welcomes papers that offer novel research contributions to any aspect characterizing the role and impact of Cloud Computing, Internet of Things and Blockchain technologies on the reliable and sustainable operation of smart grids.

High-quality papers that explore this area and provide emerging solutions and visions for future research activities are sought. Theoretical and empirical studies, as well as state-of-the-art surveys, are welcome. Prospective authors are invited to submit manuscripts for review for publication in this Special Issue.

The scope of the Special Issue includes, but is not limited to:

New advances in engineering Cloud, IoT and blockchains;
Architecture, software and system composition of smart grids;
Engineering challenges in big data within Cloud, IoT and blockchains;
Management of reliability and sustainability properties of smart grids;
Programming concepts, languages and frameworks for smart grids;
Design concepts for software system evolution, adaptability, maintainability and reuse;
Engineering concepts for availability, reliability and safety;
Automotive solutions for continuous integration, runtime verification;
Runtime certification and system safety;
Management considerations of smart grids, software and system process improvement;
Evolution aware engineering for systems of systems;
Engineering concepts, design principles and solutions for Internet of Everything, Internet of Things;
Engineering of user interfaces in interactions with complex system functions;
Human interaction with complex systems and software functions;
Artificial intelligence in software and system engineering of smart grids;
Challenges of engineering systems and software in various application domains;
Systems/software interaction and compatibility;
Metrics for evaluating systems and software in relation to sustainable and reliable operation of software and system.

Especially we are encouraging papers with case studies in green computing with respect to energies and application domains such as green traffic, green buildings and renewable energies.

Prof. Dr. Tihana Galinac Grbac
Guest Editor

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Research

17 pages, 3850 KiB

Open AccessArticle

Image Detection of Insulator Defects Based on Morphological Processing and Deep Learning

by Zhaoyun Zhang, Shihong Huang, Yanxin Li, Hui Li and Houtang Hao

Energies 2022, 15(7), 2465; https://doi.org/10.3390/en15072465 - 27 Mar 2022

Cited by 30 | Viewed by 3046

Abstract

Insulators are an important part of transmission lines; failure may threaten the operation of these transmission lines. For insulator defect detection, an optical image detection method based on deep learning and morphological detection is proposed. First of all, the Faster RCNN is used to locate the insulator and extract its target image from the detection image. In the second place, a segmentation method of insulator image is proposed to remove the background of the target image. In order to simplify insulator defect detection, an insulator shape transformation method is proposed to unify all types of insulator detection. Finally, a mathematical model is established in the binary image to describe the defect of the insulator. Experiments show that our proposed Faster RCNN can accurately detect the insulators in the image. Its AP is as high as 0.9175, and its Recall rate is as high as 0.98, which is higher than the common insulator recognition algorithm. The accuracy of the proposed defect detection method is 0.98, which can accurately locate the defect position of the insulator. In order to prove the efficiency of the proposed method, we compared several common detection methods. Full article

(This article belongs to the Special Issue Reliable and Sustainable Cloud Computing, IoT and Blockchain Applications for Smart Grids)

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20 pages, 431 KiB

Open AccessArticle

Stress-Testing MQTT Brokers: A Comparative Analysis of Performance Measurements

by Biswajeeban Mishra, Biswaranjan Mishra and Attila Kertesz

Energies 2021, 14(18), 5817; https://doi.org/10.3390/en14185817 - 14 Sep 2021

Cited by 31 | Viewed by 8746

Abstract

Presently, Internet of Things (IoT) protocols are at the heart of Machine-to-Machine (M2M) communication. Irrespective of the radio technologies used for deploying an IoT/M2M network, all independent data generated by IoT devices (sensors and actuators) rely heavily on the special messaging protocols used for M2M communication in IoT applications. As the demand for IoT services is growing, the need for reduced power consumption of IoT devices and services is also growing to ensure a sustainable environment for future generations. The Message-Queuing Telemetry Transport or in short MQTT is a widely used IoT protocol. It is a low-resource-consuming messaging solution based on the publish–subscribe type communication model. This paper aims to assess the performance of several MQTT broker implementations (also known as MQTT servers) using stress testing, and to analyze their relationship with system design. The evaluation of the brokers is performed by a realistic test scenario, and the analysis of the test results is done with three different metrics: CPU usage, latency, and message rate. As the main contribution of this work, we analyzed six MQTT brokers (Mosquitto, Active-MQ, Hivemq, Bevywise, VerneMQ, and EMQ X) in detail, and classified them using their main properties. Our results showed that Mosquitto outperforms the other considered solutions in most metrics; however, ActiveMQ is the best performing one in terms of scalability due to its multi-threaded implementation, while Bevywise has promising results for resource-constrained scenarios. Full article

(This article belongs to the Special Issue Reliable and Sustainable Cloud Computing, IoT and Blockchain Applications for Smart Grids)

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