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This study presents a machine learning-assisted approach to optimize task scheduling in cluster systems, focusing on node-affinity constraints. Traditional schedulers like Kubernetes struggle with real-time adaptability, whereas the…

Distributed, Parallel, and Cluster Computing · Computer Science 2025-09-30 Leszek Sliwko , Jolanta Mizera-Pietraszko

The use of cloud computational resources has become increasingly important for companies and researchers to access on-demand and at any moment high-performance resources. However, given the wide variety of virtual machine types, network…

Distributed, Parallel, and Cluster Computing · Computer Science 2020-06-30 Vanderson Martins Do Rosario , Thais A. Silva Camacho , Otávio O. Napoli , Edson Borin

The computational power of High-Performance Computing (HPC) systems is constantly increasing, however, their input/output (IO) performance grows relatively slowly, and their storage capacity is also limited. This unbalance presents…

In business process landscapes, a common challenge is to provide the necessary computational resources to enact the single process steps. One well-known approach to solve this issue in a cost-efficient way is to use the notion of…

Distributed, Parallel, and Cluster Computing · Computer Science 2022-09-15 Gerta Sheganaku , Stefan Schulte , Philipp Waibel , Ingo Weber

Interactive high-performance computing is doubtlessly beneficial for many computational science and engineering applications whenever simulation results should be visually processed in real time, i.e. during the computation process.…

Computational Engineering, Finance, and Science · Computer Science 2018-07-03 Ralf-Peter Mundani , Jérôme Frisch , Vasco Varduhn , Ernst Rank

Optimizing resource utilization in high-performance computing (HPC) clusters is essential for maximizing both system efficiency and user satisfaction. However, traditional rigid job scheduling often results in underutilized resources and…

Distributed, Parallel, and Cluster Computing · Computer Science 2026-02-20 Patrick Zojer , Jonas Posner , Taylan Özden

Scientific workflows have been predominantly used for complex and large scale data analysis and scientific computation/automation and the need for robust workflow scheduling techniques has grown considerably. But, most of the existing…

Distributed, Parallel, and Cluster Computing · Computer Science 2019-11-04 S. Jaya Nirmala , Amrith Rajagopal Setlur , Har Simrat Singh , Sudhanshu Khoriya

The rise of AI and the economic dominance of cloud computing have created a new nexus of innovation for high performance computing (HPC), which has a long history of driving scientific discovery. In addition to performance needs, scientific…

Distributed, Parallel, and Cluster Computing · Computer Science 2025-06-10 Vanessa Sochat , Daniel Milroy , Abhik Sarkar , Aniruddha Marathe , Tapasya Patki

High Performance Distributed Computing is essential to boost scientific progress in many areas of science and to efficiently deploy a number of complex scientific applications. These applications have different characteristics that require…

Distributed, Parallel, and Cluster Computing · Computer Science 2014-12-04 Mariza Ferro , Antonio R. Mury , Laion F. Manfroi , Bruno Schlze

Cloud computing has permeated into the information technology industry in the last few years, and it is emerging nowadays in scientific environments. Science user communities are demanding a broad range of computing power to satisfy the…

Distributed, Parallel, and Cluster Computing · Computer Science 2017-09-26 Álvaro López García , Enol Fernández-del-Castillo , Pablo Orviz Fernández , Isabel Campos Plasencia , Jesús Marco de Lucas

With the increasing prevalence of computationally intensive workflows in cloud environments, it has become crucial for cloud platforms to optimize energy consumption while ensuring the feasibility of user workflow schedules with respect to…

Distributed, Parallel, and Cluster Computing · Computer Science 2025-05-23 Suvarthi Sarkar , Dhanesh V , Ketan Singh , Aryabartta Sahu

Cloud-native applications have significantly advanced the development and scalability of online services through the use of microservices and modular architectures. However, achieving adaptability, resilience, and efficient performance…

Distributed, Parallel, and Cluster Computing · Computer Science 2025-09-30 Apostolos Angelis , George Kousiouris

Optimising the execution of Bag-of-Tasks (BoT) applications on the cloud is a hard problem due to the trade- offs between performance and monetary cost. The problem can be further complicated when multiple BoT applications need to be…

Distributed, Parallel, and Cluster Computing · Computer Science 2016-11-15 Long Thai , Blesson Varghese , Adam Barker

Dynamic nature of the cloud environment has made distributed resource management process a challenge for cloud service providers. The importance of maintaining the quality of service in accordance with customer expectations as well as the…

Distributed, Parallel, and Cluster Computing · Computer Science 2018-08-08 Sara Kardani-Moghaddam , Rajkumar Buyya , Kotagiri Ramamohanarao

Many important computational problems require utilization of high performance computing (HPC) systems that consist of multi-level structures combining higher and higher numbers of devices with various characteristics. Utilizing full power…

Distributed, Parallel, and Cluster Computing · Computer Science 2018-09-21 Paweł Rościszewski

Shared resource interference is observed by applications as dynamic performance asymmetry. Prior art has developed approaches to reduce the impact of performance asymmetry mainly at the operating system and architectural levels. In this…

Distributed, Parallel, and Cluster Computing · Computer Science 2020-09-24 Jing Chen , Pirah Noor Soomro , Mustafa Abduljabbar , Madhavan Manivannan , Miquel Pericas

Elasticity is a form of self-adaptivity in cloud-based software systems that is typically restricted to the infrastructure layer and realized through auto-scaling. However, both reactive and proactive forms of infrastructure auto-scaling…

Distributed, Parallel, and Cluster Computing · Computer Science 2020-10-16 Mohan Baruwal Chhetri , Abdur Rahim Mohammad Forkan , Anton V. Uzunov , Surya Nepal

Cloud computing is a new archetype that provides dynamic computing services to cloud users through the support of datacenters that employs the services of datacenter brokers which discover resources and assign them Virtually. The focus of…

Distributed, Parallel, and Cluster Computing · Computer Science 2016-11-29 J. Kok Konjaang , J. Y. Maipan-uku , Kumangkem Kennedy Kubuga

Different departments of a large organization often run dedicated cluster systems for different computing loads, like HPC (high performance computing) jobs or Web service applications. In this paper, we have designed and implemented a cloud…

Distributed, Parallel, and Cluster Computing · Computer Science 2010-07-20 Jianfeng Zhan , Lei Wang , Bibo Tu , Yong Li , Peng Wang , Wei Zhou , Dan Meng

Big data processing applications are becoming more and more complex. They are no more monolithic in nature but instead they are composed of decoupled analytical processes in the form of a workflow. One type of such workflow applications is…

Distributed, Parallel, and Cluster Computing · Computer Science 2019-12-19 Mutaz Barika , Saurabh Garg , Andrew Chan , Rodrigo N. Calheiros