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Computation offloading is often used in mobile cloud, edge, and/or fog computing to cope with resource limitations of mobile devices in terms of computational power, storage, and energy. Computation offloading is particularly challenging in…

Distributed, Parallel, and Cluster Computing · Computer Science 2019-07-26 Artur Sterz , Lars Baumgärtner , Jonas höchst , Patrick Lampe , Bernd Freisleben

With the widespread adoption of 5G and Internet of Things (IoT) technologies, the low latency provided by edge computing has great importance for real-time processing. However, managing numerous simultaneous service requests poses a…

Distributed, Parallel, and Cluster Computing · Computer Science 2024-09-17 Wang Yatong , Pei Yuchen , Zhao Yuqi

Serverless cloud is an innovative cloud service model that frees customers from most cloud management duties. It also offers the same advantages as other cloud models but at much lower costs. As a result, the serverless cloud has been…

Distributed, Parallel, and Cluster Computing · Computer Science 2023-12-15 Tam N. Nguyen

Serverless computing relieves developers from the burden of resource management, thus providing ease-of-use to the users and the opportunity to optimize resource utilization for the providers. However, today's serverless systems lack…

Distributed, Parallel, and Cluster Computing · Computer Science 2024-01-26 Prasoon Sinha , Kostis Kaffes , Neeraja J. Yadwadkar

Serverless computing has rapidly grown following the launch of Amazon's Lambda platform. Function-as-a-Service (FaaS) a key enabler of serverless computing allows an application to be decomposed into simple, standalone functions that are…

Distributed, Parallel, and Cluster Computing · Computer Science 2021-03-11 Anshul Jindal , Michael Gerndt , Mohak Chadha , Vladimir Podolskiy , Pengfei Chen

Experimental data can aid in gaining insights about a system operation, as well as determining critical aspects of a modelling or simulation process. In this paper, we analyze the data acquired from an extensive experimentation process in a…

Recently, serverless computing has gained recognition as a leading cloud computing method. Providing a solution that does not require direct server and infrastructure management, this technology has addressed many traditional model problems…

Distributed, Parallel, and Cluster Computing · Computer Science 2025-01-20 Mohsen Ghorbian , Mostafa Ghobaei-Arani

Cloud-based computing infrastructure provides an efficient means to support real-time processing workloads, e.g., virtualized base station processing, and collaborative video conferencing. This paper addresses resource allocation for a…

Networking and Internet Architecture · Computer Science 2016-03-08 Yuhuan Du , Gustavo de Veciana

Service systems often face task-server assignment-constraints due to skill-based routing or geographical conditions. Redundancy scheduling responds to this limited flexibility by replicating tasks to specific servers in agreement with these…

Probability · Mathematics 2022-08-17 Ellen Cardinaels , Sem Borst , Johan S. H. van Leeuwaarden

Serverless computing has emerged as a prominent paradigm, with a significant adoption rate among cloud customers. While this model offers advantages such as abstraction from the deployment and resource scheduling, it also poses limitations…

Distributed, Parallel, and Cluster Computing · Computer Science 2025-03-26 Larissa Schmid , Marcin Copik , Alexandru Calotoiu , Laurin Brandner , Anne Koziolek , Torsten Hoefler

It is increasingly common to outsource network functions (NFs) to the cloud. However, no cloud providers offer NFs-as-a-Service (NFaaS) that allows users to run custom NFs. Our work addresses how a cloud provider can offer NFaaS. We use the…

Distributed, Parallel, and Cluster Computing · Computer Science 2019-10-18 Arjun Singhvi , Junaid Khalid , Aditya Akella , Sujata Banerjee

Serverless computing has emerged as a promising computing paradigm for edge computing. However, adopting the event driven model in highly dynamic, heterogeneous, and distributed edge systems poses significant challenges in request placement…

Distributed, Parallel, and Cluster Computing · Computer Science 2026-05-18 Chen Chen , Zihan Jia , Andrea Sabbioni , Reza Farahani , Lei Jiao

Cloud Computing is a paradigm of both parallel processing and distributed computing. It offers computing facilities as a utility service in pay as par use manner. Virtualization, self service provisioning, elasticity and pay per use are the…

Distributed, Parallel, and Cluster Computing · Computer Science 2016-12-20 Syed Arshad Ali , Mansaf Alam

Recent trends in Web development demonstrate an increased interest in serverless applications, i.e. applications that utilize computational resources provided by cloud services on demand instead of requiring traditional server management.…

Distributed, Parallel, and Cluster Computing · Computer Science 2021-05-31 Vladislav Tankov , Yaroslav Golubev , Timofey Bryksin

OpenMP is the de-facto standard for shared memory systems in High-Performance Computing (HPC). It includes a task-based model that offers a high-level of abstraction to effectively exploit highly dynamic structured and unstructured…

Distributed, Parallel, and Cluster Computing · Computer Science 2022-12-12 Chenle Yu , Sara Royuela , Eduardo Quiñones

Edge computing is an emerging paradigm to enable low-latency applications, like mobile augmented reality, because it takes the computation on processing devices that are closer to the users. On the other hand, the need for highly scalable…

Distributed, Parallel, and Cluster Computing · Computer Science 2021-09-21 Claudio Cicconetti , Marco Conti , Andrea Passarella

Cloud platforms have emerged as a prominent environment to execute high performance computing (HPC) applications providing on-demand resources as well as scalability. They usually offer different classes of Virtual Machines (VMs) which…

Distributed, Parallel, and Cluster Computing · Computer Science 2018-10-25 Luan Teylo , Lúcia Maria de A. Drummond , Luciana Arantes , Pierre Sens

Graph processing systems are essential for analyzing large-scale data with complex relationships, yet most existing frameworks rely on statically provisioned clusters, resulting in poor elasticity and inefficient resource utilization under…

Distributed, Parallel, and Cluster Computing · Computer Science 2026-05-13 Chen Zhao , Parsa Poorsistani , Mohammad Goudarzi , Tawfiq Islam , Adel N. Toosi

Temporal planning offers numerous advantages when based on an expressive representation. Timelines have been known to provide the required expressiveness but at the cost of search efficiency. We propose here a temporal planner, called FAPE,…

Artificial Intelligence · Computer Science 2020-10-27 Arthur Bit-Monnot , Malik Ghallab , Félix Ingrand , David E. Smith

Modern computing workloads are often composed of parallelizable jobs. A parallelizable job can be completed more quickly when run on additional servers. However, each job can only use a limited number of servers, known as its…

Performance · Computer Science 2025-12-30 Benjamin Berg , Benjamin Moseley , Weina Wang , Mor Harchol-Balter