{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,23]],"date-time":"2026-01-23T19:41:49Z","timestamp":1769197309314,"version":"3.49.0"},"reference-count":33,"publisher":"MDPI AG","issue":"4","license":[{"start":{"date-parts":[[2022,2,14]],"date-time":"2022-02-14T00:00:00Z","timestamp":1644796800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Fault tolerance, performance, and throughput have been major areas of research and development since the evolution of large-scale networks. Internet-based applications are rapidly growing, including large-scale computations, search engines, high-definition video streaming, e-commerce, and video on demand. In recent years, energy efficiency and fault tolerance have gained significant importance in data center networks and various studies directed the attention towards green computing. Data centers consume a huge amount of energy and various architectures and techniques have been proposed to improve the energy efficiency of data centers. However, there is a tradeoff between energy efficiency and fault tolerance. The objective of this study is to highlight a better tradeoff between the two extremes: (a) high energy efficiency and (b) ensuring high availability through fault tolerance and redundancy. The main objective of the proposed Energy-Aware Fault-Tolerant (EAFT) approach is to keep one level of redundancy for fault tolerance while scheduling resources for energy efficiency. The resultant energy-efficient data center network provides availability as well as fault tolerance at reduced operating cost. The main contributions of this article are: (a) we propose an Energy-Aware Fault-Tolerant (EAFT) data center network scheduler; (b) we compare EAFT with energy efficient resource scheduling techniques to provide analysis of parameters such as, workload distribution, average task per servers, and energy consumption; and (c) we highlight effects of energy efficiency techniques on the network performance of the data center.<\/jats:p>","DOI":"10.3390\/s22041482","type":"journal-article","created":{"date-parts":[[2022,2,14]],"date-time":"2022-02-14T20:58:03Z","timestamp":1644872283000},"page":"1482","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":21,"title":["Balanced Energy-Aware and Fault-Tolerant Data Center Scheduling"],"prefix":"10.3390","volume":"22","author":[{"given":"Muhammad","family":"Shaukat","sequence":"first","affiliation":[{"name":"Department of Computer Science, COMSATS University Islamabad, Abbottabad Campus, Abbottabad 22060, Pakistan"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4349-144X","authenticated-orcid":false,"given":"Waleed","family":"Alasmary","sequence":"additional","affiliation":[{"name":"Computer Engineering Department, College of Computer and Information Systems, Umm Al-Qura University, Makkah 21955, Saudi Arabia"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5560-1116","authenticated-orcid":false,"given":"Eisa","family":"Alanazi","sequence":"additional","affiliation":[{"name":"Department of Computer Science, Umm Al-Qura University, Makkah 21955, Saudi Arabia"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0726-5311","authenticated-orcid":false,"given":"Junaid","family":"Shuja","sequence":"additional","affiliation":[{"name":"Department of Computer Science, COMSATS University Islamabad, Abbottabad Campus, Abbottabad 22060, Pakistan"}]},{"given":"Sajjad A.","family":"Madani","sequence":"additional","affiliation":[{"name":"Department of Computer Science, COMSATS University Islamabad, Abbottabad Campus, Abbottabad 22060, Pakistan"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2440-2771","authenticated-orcid":false,"given":"Ching-Hsien","family":"Hsu","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Information Engineering, Asia University, Taichung City 41354, Taiwan"},{"name":"Department of Medical Research, China Medical University Hospital, China Medical University, Taichung City 406040, Taiwan"},{"name":"Guangdong-Hong Kong-Macao Joint Laboratory for Intelligent Micro-Nano Optoelectronic Technology, School of Mathematics and Big Data, Foshan University, Foshan 528000, China"}]}],"member":"1968","published-online":{"date-parts":[[2022,2,14]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"145767","DOI":"10.1109\/ACCESS.2019.2945499","article-title":"Characterizing dynamic load balancing in cloud environments using virtual machine deployment models","volume":"7","author":"Liaqat","year":"2019","journal-title":"IEEE Access"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"507","DOI":"10.1109\/JSYST.2014.2315823","article-title":"Survey of Techniques and Architectures for Designing Energy-Efficient Data Centers","volume":"10","author":"Shuja","year":"2016","journal-title":"IEEE Syst. 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