@inproceedings{14441be2a383464c988247f9a51338be,
title = "Brief announcement: Scheduling parallelizable jobs online to maximize throughput",
abstract = "We consider scheduling parallelizable jobs online to maximize the throughput or profit of the schedule. A set of n jobs arrive online and each job Ji has an associated function pi (t ), the profit obtained for finishing job Ji at time t. Each job has its own arbitrary nonincreasing profit function. We consider the case where each job is a parallel job that can be represented as a directed acyclic graph (DAG).We give the first non-trivial results for the profit scheduling problem for DAG jobs showing O(1)-competitive algorithms using resource augmentation.",
author = "Kunal Agrawal and Jing Li and Kefu Lu and Benjamin Moseley",
note = "Publisher Copyright: {\textcopyright} 2017 Copyright held by the owner/author(s).; 29th ACM Symposium on Parallelism in Algorithms and Architectures, SPAA 2017 ; Conference date: 24-07-2017 Through 26-07-2017",
year = "2017",
month = jul,
day = "24",
doi = "10.1145/3087556.3087590",
language = "English (US)",
series = "Annual ACM Symposium on Parallelism in Algorithms and Architectures",
publisher = "Association for Computing Machinery",
pages = "87--89",
booktitle = "SPAA 2017 - Proceedings of the 29th ACM Symposium on Parallelism in Algorithms and Architectures",
}