Wan Nor Shuhadah Wan Nik, Universiti Sultan Zainal Abidin, Malaysia
Wan Nor Shuhadah Wan Nik is currently a senior lecturer in the Faculty of Informatics and Computing, University Sultan Zainal Abidin (UniSA), Malaysia. She received a Ph.D. in Computer Science (Distributed Systems) from the University of Sydney, Australia in 2012 before being appointed as a Deputy Director (Infrastructure & Services) at Information Technology Centre, UniSA from the year 2014 - 2017. She has been involved in more than ten research grants and led five national grants in Distributed Systems. Her main research interest includes the area of Computer Networks and Distributed Systems, including Scheduling in Grid / Cloud / Edge and Utility Computing, Wireless Sensor Networks, IoT, Heuristics and Optimization, and Blockchain.
Speech Title: Job Scheduling in Cloud and Fog Computing: A Recent Systematic Review
Abstract: Cloud and Fog computing have emerged as pivotal paradigms in distributed computing, providing flexible and scalable resources for diverse applications, with efficient job scheduling being a critical factor in optimizing resource utilization and enhancing system performance. Job scheduling in these environments presents complex challenges due to their dynamic and heterogeneous nature, as balancing resource allocation, minimizing latency, and improving energy efficiency raise significant research questions. This systematic review aims to offer an up-to-date overview of the state-of-the-art research in job scheduling for Cloud and Fog computing, with objectives including assessing the current landscape of job scheduling techniques, analyzing key challenges and trends in the field, and highlighting recent advancements and innovations to provide insights for future research directions. Following the PRISMA framework, a comprehensive advance search was conducted on peer-reviewed articles (n=48) published in 2023 from Scopus and IEEE databases, with rigorous search and selection criteria ensuring the inclusion of relevant studies and subsequent analysis to extract key findings and identify emerging trends. By summarizing the state-of-the-art, this review delivers valuable insights for researchers and practitioners, guiding future research efforts to address the evolving demands of these dynamic computing paradigms.
Riswan Efendi, Universiti Pendidikan Sultan Idris (UPSI), Malaysia
Riswan Efendi is a senior lecturer at the Mathematics Department of Universiti Pendidikan Sultan Idris (UPSI) in Malaysia. His research topics are mainly focused on fuzzy time series and fuzzy-regression models for prediction. Currently, his research centers on integrating rough set theory into regression models to reduce inconsistent samples or elements. He is actively involved in research grants, has a Scopus h-index of 10 in his publications, and participates in conferences. He is also active as a reviewer in several reputable journals including Neural Computing and Applications (Springer), Applied Soft Computing (Elsevier), Transaction on Fuzzy Systems (IEEE), Computational Economics (Springer), Axioms, Symmetry and Applied Sciences Journals (MDPI), and Journal of Psychology (Taylor and France). Moreover, he serves on the scientific committee of international conferences such as HP3C 2020 - 2025 and WSAI 2021.
2017-2025 © HP3C. All Rights Reserved.