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We study online mechanisms for preemptive scheduling with deadlines, with the goal of maximizing the total value of completed jobs. This problem is fundamental to deadline-aware cloud scheduling, but there are strong lower bounds even for…

Data Structures and Algorithms · Computer Science 2015-07-06 Yossi Azar , Inna Kalp-Shaltiel , Brendan Lucier , Ishai Menache , Joseph , Naor , Jonathan Yaniv

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

We consider the online resource minimization problem in which jobs with hard deadlines arrive online over time at their release dates. The task is to determine a feasible schedule on a minimum number of machines. We rigorously study this…

Data Structures and Algorithms · Computer Science 2015-12-09 Lin Chen , Nicole Megow , Kevin Schewior

We consider a fundamental online scheduling problem in which jobs with processing times and deadlines arrive online over time at their release dates. The task is to determine a feasible preemptive schedule on a single or multiple possibly…

Data Structures and Algorithms · Computer Science 2021-12-02 Franziska Eberle , Nicole Megow , Kevin Schewior

In this study, we investigated several online and semi-online scheduling problems on two hierarchical machines with a common due date to maximize the total early work. For the pure online case, we designed an optimal online algorithm with a…

Data Structures and Algorithms · Computer Science 2022-09-20 Man Xiao , Xiaoqiao Liu , Weidong Li , Xin Chen , Malgorzata Sterna , Jacek Blazewicz

We investigate online scheduling with commitment for parallel identical machines. Our objective is to maximize the total processing time of accepted jobs. As soon as a job has been submitted, the commitment constraint forces us to decide…

Data Structures and Algorithms · Computer Science 2019-04-15 Chris Schwiegelshohn , Uwe Schwiegelshohn

We investigate deterministic non-preemptive online scheduling with delayed commitment for total completion time minimization on parallel identical machines. In this problem, jobs arrive one-by-one and their processing times are revealed…

Data Structures and Algorithms · Computer Science 2022-07-19 Uwe Schwiegelshohn

We study the online preemptive scheduling of intervals and jobs (with restarts). Each interval or job has an arrival time, a deadline, a length and a weight. The objective is to maximize the total weight of completed intervals or jobs.…

Data Structures and Algorithms · Computer Science 2012-04-16 Stanley P. Y. Fung , Chung Keung Poon , Feifeng Zheng

We consider an online preemptive scheduling problem where jobs with deadlines arrive sporadically. A commitment requirement is imposed such that the scheduler has to either accept or decline a job immediately upon arrival. The scheduler's…

Data Structures and Algorithms · Computer Science 2011-10-07 Shiyao Chen , Lang Tong , Ting He

The problem of online scheduling of multi-server jobs is considered, where there are a total of $K$ servers, and each job requires concurrent service from multiple servers for it to be processed. Each job on its arrival reveals its…

Data Structures and Algorithms · Computer Science 2024-07-02 Rahul Vaze

We study a fundamental online scheduling problem where jobs with processing times, weights, and deadlines arrive online over time at their release dates. The task is to preemptively schedule these jobs on a single or multiple (possibly…

Data Structures and Algorithms · Computer Science 2023-10-26 Franziska Eberle

We explore the machine-minimizing job scheduling problem, which has a rich history in the line of research, under an online setting. We consider systems with arbitrary job arrival times, arbitrary job deadlines, and unit job execution time.…

Data Structures and Algorithms · Computer Science 2013-09-24 Mong-Jen Kao , Jian-Jia Chen , Ignaz Rutter , Dorothea Wagner

We propose a new approach to competitive analysis in online scheduling by introducing the novel concept of competitive-ratio approximation schemes. Such a scheme algorithmically constructs an online algorithm with a competitive ratio…

Data Structures and Algorithms · Computer Science 2012-11-01 Elisabeth Günther , Olaf Maurer , Nicole Megow , Andreas Wiese

We study the online busy time scheduling model on heterogeneous machines. In our setting, jobs with uniform length arrive online with a deadline that becomes known to the algorithm at the job's arrival time. An algorithm has access to…

Data Structures and Algorithms · Computer Science 2026-03-09 Gruia Calinescu , Sami Davies , Samir Khuller , Shirley Zhang

A speed scaling problem is considered, where time is divided into slots, and jobs with payoff $v$ arrive at the beginning of the slot with associated deadlines $d$. Each job takes one slot to be processed, and multiple jobs can be processed…

Data Structures and Algorithms · Computer Science 2017-11-15 Goonwanth Reddy , Rahul Vaze

We consider the classical online scheduling problem P||C_{max} in which jobs are released over list and provide a nearly optimal online algorithm. More precisely, an online algorithm whose competitive ratio is at most (1+\epsilon) times…

Data Structures and Algorithms · Computer Science 2013-02-19 Lin Chen , Deshi Ye , Guochuan Zhang

In this paper, we consider the online version of the machine minimization problem (introduced by Chuzhoy et al., FOCS 2004), where the goal is to schedule a set of jobs with release times, deadlines, and processing lengths on a minimum…

Discrete Mathematics · Computer Science 2014-03-06 Nikhil Devanur , Konstantin Makarychev , Debmalya Panigrahi , Grigory Yaroslavtsev

This paper considers the basic problem of scheduling jobs online with preemption to maximize the number of jobs completed by their deadline on $m$ identical machines. The main result is an $O(1)$ competitive deterministic algorithm for any…

Data Structures and Algorithms · Computer Science 2024-08-26 Benjamin Moseley , Kirk Pruhs , Clifford Stein , Rudy Zhou

We consider a parallel system of $m$ identical machines prone to unpredictable crashes and restarts, trying to cope with the continuous arrival of tasks to be executed. Tasks have different computational requirements (i.e., processing time…

Distributed, Parallel, and Cluster Computing · Computer Science 2016-03-21 Elli Zavou , Antonio Fernández Anta

In this paper, we consider the online problem of scheduling independent jobs \emph{non-preemptively} so as to minimize the weighted flow-time on a set of unrelated machines. There has been a considerable amount of work on this problem in…

Data Structures and Algorithms · Computer Science 2018-04-24 Giorgio Lucarelli , Benjamin Moseley , Nguyen Kim Thang , Abhinav Srivastav , Denis Trystram
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