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Detecting and analyzing potential anomalous performances in cloud computing systems is essential for avoiding losses to customers and ensuring the efficient operation of the systems. To this end, a variety of automated techniques have been…

Human-Computer Interaction · Computer Science 2019-08-01 Ke Xu , Yun Wang , Leni Yang , Yifang Wang , Bo Qiao , Si Qin , Yong Xu , Haidong Zhang , Huamin Qu

In recent past, big data opportunities have gained much momentum to enhance knowledge management in organizations. However, big data due to its various properties like high volume, variety, and velocity can no longer be effectively stored…

Distributed, Parallel, and Cluster Computing · Computer Science 2017-02-16 Mohammad Shorfuzzaman

Cloud resources have become increasingly important, with many businesses using cloud solutions to supplement or outright replace their existing IT infrastructure. However, as there is a plethora of providers with varying products, services,…

Distributed, Parallel, and Cluster Computing · Computer Science 2024-04-19 Valentin Haag , Maximilian Kiessler , Benedikt Pittl , Erich Schikuta

Serverless clouds allocate multiple tasks (e.g., micro-services) from multiple users on a shared pool of computing resources. This enables serverless cloud providers to reduce their resource usage by transparently aggregate similar tasks of…

Distributed, Parallel, and Cluster Computing · Computer Science 2020-12-14 Shangrui Wu , Chavit Denninnart , Xiangbo Li , Yang Wang , Mohsen Amini Salehi

The growing demand for computational resources in machine learning has made efficient resource allocation a critical challenge, especially in heterogeneous hardware clusters where devices vary in capability, age, and energy efficiency.…

Distributed, Parallel, and Cluster Computing · Computer Science 2025-10-20 Ahmad Raeisi , Mahdi Dolati , Sina Darabi , Sadegh Talebi , Patrick Eugster , Ahmad Khonsari

Cloud providers offer a variety of execution platforms in form of bare-metal, VM, and containers. However, due to the pros and cons of each execution platform, choosing the appropriate platform for a specific cloud-based application has…

Distributed, Parallel, and Cluster Computing · Computer Science 2020-06-04 Davood Ghatreh Samani , Chavit Denninnart , Josef Bacik , Mohsen Amini Salehi

Traffic for internet video streaming has been rapidly increasing and is further expected to increase with the higher definition videos and IoT applications, such as 360 degree videos and augmented virtual reality applications. While…

Networking and Internet Architecture · Computer Science 2018-07-04 Abubakr Alabbasi , Vaneet Aggarwal , Tian Lan , Yu Xiang , Moo-Ryong Ra , Yih-Farn R. Chen

We investigate video classification via a two-stream convolutional neural network (CNN) design that directly ingests information extracted from compressed video bitstreams. Our approach begins with the observation that all modern video…

Computer Vision and Pattern Recognition · Computer Science 2017-12-21 Aaron Chadha , Alhabib Abbas , Yiannis Andreopoulos

How can applications be deployed on the cloud to achieve maximum performance? This question is challenging to address with the availability of a wide variety of cloud Virtual Machines (VMs) with different performance capabilities. The…

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

The advent of 5G has driven the demand for high-quality, low-latency live streaming. However, challenges such as managing the increased data volume, ensuring synchronization across multiple streams, and maintaining consistent quality under…

Multimedia · Computer Science 2025-05-01 Aizierjiang Aiersilan , Zhiqiang Wang

Virtual machine (VM) scheduling is an important technique to efficiently operate the computing resources in a data center. Previous work has mainly focused on consolidating VMs to improve resource utilization and thus to optimize energy…

Distributed, Parallel, and Cluster Computing · Computer Science 2014-04-22 Xibo Jin , Fa Zhang , Lin Wang , Songlin Hu , Biyu Zhou , Zhiyong Liu

Current state-of-the-art models for video action recognition are mostly based on expensive 3D ConvNets. This results in a need for large GPU clusters to train and evaluate such architectures. To address this problem, we present a…

Computer Vision and Pattern Recognition · Computer Science 2021-07-27 Quanfu Fan , Chun-Fu Chen , Hilde Kuehne , Marco Pistoia , David Cox

Cloud rendering is widely used in gaming and XR to overcome limited client-side GPU resources and to support heterogeneous devices. Existing systems typically deliver the rendered scene as a 2D video stream, which tightly couples the…

Image and Video Processing · Electrical Eng. & Systems 2026-04-06 Matti Siekkinen , Teemu Kämäräinen

Today's intelligent computing environments, including Internet of Things, cloud computing and fog computing, allow many organizations around the world to optimize their resource allocation regarding time and energy consumption. Due to the…

Distributed, Parallel, and Cluster Computing · Computer Science 2022-02-09 Fatemeh Rahmani , Javad Hassannataj Joloudari , Shahab Shamshirband , Seyedakbar Mostafavi

The IceCube collaboration relies on GPU compute for many of its needs, including ray tracing simulation and machine learning activities. GPUs are however still a relatively scarce commodity in the scientific resource provider community, so…

Distributed, Parallel, and Cluster Computing · Computer Science 2021-11-02 Igor Sfiligoi , Shava Smallen , Frank Würthwein , Nicole Wolter , David Schultz , Benedikt Riedel

Traffic management systems capture tremendous video data and leverage advances in video processing to detect and monitor traffic incidents. The collected data are traditionally forwarded to the traffic management center (TMC) for in-depth…

Computer Vision and Pattern Recognition · Computer Science 2021-09-08 Guanxiong Liu , Hang Shi , Abbas Kiani , Abdallah Khreishah , Jo Young Lee , Nirwan Ansari , Chengjun Liu , Mustafa Yousef

Cameras are the defacto sensor. The growing demand for real-time and low-power computer vision, coupled with trends towards high-efficiency heterogeneous systems, has given rise to a wide range of image processing acceleration techniques at…

Hardware Architecture · Computer Science 2017-10-18 Amrita Mazumdar , Thierry Moreau , Sung Kim , Meghan Cowan , Armin Alaghi , Luis Ceze , Mark Oskin , Visvesh Sathe

Overlapping cameras offer exciting opportunities to view a scene from different angles, allowing for more advanced, comprehensive and robust analysis. However, existing visual analytics systems for multi-camera streams are mostly limited to…

Computer Vision and Pattern Recognition · Computer Science 2024-01-30 Chulhong Min , Juheon Yi , Utku Gunay Acer , Fahim Kawsar

In the recent years it can be observed increasing popularity of parallel processing using multi-core processors, local clusters, GPU and others. Moreover, currently one of the main requirements the IT users is the reduction of maintaining…

Distributed, Parallel, and Cluster Computing · Computer Science 2016-04-05 Łukasz P. Olech , Jan Kwiatkowski

Cloud computing is a technological advancement in the arena of computing and has taken the utility vision of computing a step further by providing computing resources such as network, storage, compute capacity and servers, as a service via…

Distributed, Parallel, and Cluster Computing · Computer Science 2014-12-30 Mansaf Alam , Kashish Ara Shakil
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