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When a computer system schedules jobs there is typically a significant cost associated with preempting a job during execution. This cost can be from the expensive task of saving the memory's state and loading data into and out of memory. It…

Data Structures and Algorithms · Computer Science 2018-03-01 Giorgio Lucarelli , Benjamin Moseley , Nguyen Kim Thang , Abhinav Srivastav , Denis Trystram

We investigate the global scheduling of sporadic, implicit deadline, real-time task systems on multiprocessor platforms. We provide a task model which integrates job parallelism. We prove that the time-complexity of the feasibility problem…

Operating Systems · Computer Science 2008-05-22 S. Collette , L. Cucu , J. Goossens

Over the years, many multiprocessor locking protocols have been designed and analyzed. However, the performance of these protocols highly depends on how the tasks are partitioned and prioritized and how the resources are shared locally and…

Operating Systems · Computer Science 2018-09-11 Jian-Jia Chen , Georg von der Brüggen , Junjie Shi , Niklas Uete

With the rapidly growing demand of graph processing in the real scene, they have to efficiently handle massive concurrent jobs. Although existing work enable to efficiently handle single graph processing job, there are plenty of memory…

Distributed, Parallel, and Cluster Computing · Computer Science 2018-06-05 Jin Zhao

We consider non-preemptive scheduling of MapReduce jobs with multiple tasks in the practical scenario where each job requires several map-reduce rounds. We seek to minimize the average weighted completion time and consider scheduling on…

Data Structures and Algorithms · Computer Science 2016-02-18 Dimitris Fotakis , Ioannis Milis , Orestis Papadigenopoulos , Vasilis Vassalos , Georgios Zois

Machine learning algorithms are designed to make accurate predictions of the future based on existing data, while online algorithms seek to bound some performance measure (typically the competitive ratio) without knowledge of the future.…

Machine Learning · Computer Science 2021-09-30 Kevin Rao

Distributed computing, such as cloud computing, provides promising platforms to execute multiple workflows. Workflow scheduling plays an important role in multi-workflow execution with multi-objective requirements. Although there exist many…

Artificial Intelligence · Computer Science 2022-05-24 Feng Li , Wen Jun , Tan , Wentong , Cai

We consider the online buffer minimization in multiprocessor systems with conflicts problem (in short, the buffer minimization problem) in the recently introduced flow model. In an online fashion, workloads arrive on some of the $n$…

Data Structures and Algorithms · Computer Science 2025-11-26 Niklas Haas , Sören Schmitt , Rob van Stee

Task graph scheduling is a relevant problem in computer science with application to diverse real world domains. Task graph scheduling suffers from a combinatorial explosion and thus finding optimal schedulers is a difficult task. In this…

Distributed, Parallel, and Cluster Computing · Computer Science 2020-02-26 Anne Ejsing , Martin Jensen , Marco Muñiz , Jacob Nørhave , Lars Rechter

In malleable job scheduling, jobs can be executed simultaneously on multiple machines with the processing time depending on the number of allocated machines. In this setting, jobs are required to be executed non-preemptively and in unison,…

Data Structures and Algorithms · Computer Science 2020-04-08 Dimitris Fotakis , Jannik Matuschke , Orestis Papadigenopoulos

We study the $b$-matching problem in bipartite graphs $G=(S,R,E)$. Each vertex $s\in S$ is a server with individual capacity $b_s$. The vertices $r\in R$ are requests that arrive online and must be assigned instantly to an eligible server.…

Data Structures and Algorithms · Computer Science 2022-07-01 Susanne Albers , Sebastian Schubert

This paper formulates a multitask optimization problem where agents in the network have individual objectives to meet, or individual parameter vectors to estimate, subject to a smoothness condition over the graph. The smoothness condition…

Multiagent Systems · Computer Science 2019-11-18 Roula Nassif , Stefan Vlaski , Cedric Richard , Ali H. Sayed

The interval scheduling problem is one variant of the scheduling problem. In this paper, we propose a novel variant of the interval scheduling problem, whose definition is as follows: given jobs are specified by their {\em release times},…

Data Structures and Algorithms · Computer Science 2018-05-16 Koji M. Kobayashi

We study a fundamental online job admission problem where jobs with deadlines arrive online over time at their release dates, and the task is to determine a preemptive single-server schedule which maximizes the number of jobs that complete…

Data Structures and Algorithms · Computer Science 2018-11-21 Lin Chen , Franziska Eberle , Nicole Megow , Kevin Schewior , Cliff Stein

This work studies online scheduling algorithms for buffer management, develops new algorithms, and analyzes their performances. Packets arrive at a release time r, with a non-negative weight w and an integer deadline d. At each time step,…

Data Structures and Algorithms · Computer Science 2025-11-21 Nourhan Sakr , Cliff Stein

Many scientific workflows can be represented by a Directed Acyclic Graph (DAG) where each node represents a task, and there will be a directed edge between two tasks if and only if there is a dependency relationship between the two i.e. the…

Distributed, Parallel, and Cluster Computing · Computer Science 2022-12-20 Atharva Tekawade , Suman Banerjee

A queue is required when a service provider is not able to handle jobs arriving over the time. In a highly flexible and dynamic environment, some jobs might demand for faster execution at run-time especially when the resources are limited…

Performance · Computer Science 2015-03-24 Yash Gupta , Kamalakar Karlapalem

In this paper, we consider the problem of real-time transmission scheduling over time-varying channels. We first formulate the transmission scheduling problem as a Markov decision process (MDP) and systematically unravel the structural…

Machine Learning · Computer Science 2010-03-15 Fangwen Fu , Mihaela van der Schaar

In moldable job scheduling, we are provided $m$ identical machines and $n$ jobs that can be executed on a variable number of machines. The execution time of each job depends on the number of machines assigned to execute that job. For the…

Data Structures and Algorithms · Computer Science 2026-01-07 Klaus Jansen , Felix Ohnesorge

We consider online preemptive scheduling of jobs arriving one by one, to be assigned to two identical machines, with the goal of makespan minimization. We study the effect of selecting the best solution out of two independent solutions…

Data Structures and Algorithms · Computer Science 2022-10-12 Leah Epstein
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