Related papers: KubeAdaptor: A Docking Framework for Workflow Cont…

This project investigates the benefits of containerization technology in modern software development and deployment. The study emphasizes the advantages of using Kubernetes and Docker in the development process, including the easy packaging…

This paper introduces Dodoor, an efficient randomized decentralized scheduler designed for task scheduling in modern data centers. Dodoor leverages advanced research on the weighted balls-into-bins model with b-batched setting. Unlike other…

In neural network topologies, algorithms are running on batches of data tensors. The batches of data are typically scheduled onto the computing cores which execute in parallel. For the algorithms running on batches of data, an optimal batch…

With the rapid rise of intelligent data services, modern enterprises increasingly require efficient, multimodal, and cost-effective data analytics infrastructures. However, in ByteDance's production environments, existing systems fall short…

In distributed computing frameworks like MapReduce, Spark, and Dyrad, a coflow is a set of flows transferring data between two stages of a job. The job cannot start its next stage unless all flows in the coflow finish. To improve the…

Since emerging edge applications such as Internet of Things (IoT) analytics and augmented reality have tight latency constraints, hardware AI accelerators have been recently proposed to speed up deep neural network (DNN) inference run by…

Containerization is a virtualization technique that allows one to create and run executables consistently on any infrastructure. Compared to virtual machines, containers are lighter since they do not bundle a (guest) operating system but…

Before media playback is possible, live and video-on-demand content alike usually undergoes various operations described as tasks within a multimedia workflow. Where previously ingest, transcode, packaging and delivery tasks might have run…

This study investigates the potential of WebAssembly as a more secure and efficient alternative to Linux containers for executing untrusted code in cloud computing with Kubernetes. Specifically, it evaluates the security and performance…

Selecting appropriate values for the configurable parameters of Database Management Systems (DBMS) to improve performance is a significant challenge. Recent machine learning (ML)-based tuning systems have shown strong potential, but their…

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…

The CODECO Experimentation Framework is an open-source solution designed for the rapid experimentation of Kubernetes-based edge cloud deployments. It adopts a microservice-based architecture and introduces innovative abstractions for (i)…

Quadrotors are agile platforms. With human experts, they can perform extremely high-speed flights in cluttered environments. However, fully autonomous flight at high speed remains a significant challenge. In this work, we propose a motion…

Edge computing is becoming more and more popular among researchers who seek to take advantage of the edge resources and the minimal time delays, in order to run their robotic applications more efficiently. Recently, many edge architectures…

Cloud providers usually offer diverse types of hardware for their users. Customers exploit this option to deploy cloud instances featuring GPUs, FPGAs, architectures other than x86 (e.g., ARM, IBM Power8), or featuring certain specific…

The increasing complexity of industrial scheduling and transport routing problems motivates the study of alternative optimization formulations and computational paradigms. In this work, we study how higher-order unconstrained binary…

In Cloud computing environment the resources are managed dynamically based on the need and demand for resources for a particular task. With a lot of challenges to be addressed our concern is Load balancing where load balancing is done for…

Modern cloud orchestrators like Kubernetes provide a versatile and robust way to host applications at scale. One of their key features is autoscaling, which automatically adjusts cloud resources (compute, memory, storage) in order to adapt…

Virtualization is a promising technology that has facilitated cloud computing to become the next wave of the Internet revolution. Adopted by data centers, millions of applications that are powered by various virtual machines improve the…

In Mobile Edge Computing (MEC), Internet of Things (IoT) devices offload computationally-intensive tasks to edge nodes, where they are executed within containers, reducing the reliance on centralized cloud infrastructure. Frequent upgrades…