Online weighted flow time and deadline scheduling
نویسندگان
چکیده
منابع مشابه
Online Weighted Flow Time and Deadline Scheduling
In this paper we study some aspects of weighted flow time. We first show that the online algorithm Highest Density First is an O(1)-speed O(1)-approximation algorithm for P |ri ,pmtn| ∑ wiFi . We then consider a related Deadline Scheduling Problem that involves minimizing the weight of the jobs unfinished by some unknown deadline D on a uniprocessor. We show that any c-competitive online algori...
متن کاملAggressive Online Deadline Scheduling
This paper is concerned with online algorithms for scheduling jobs with deadlines on a single processor. It has been known for long that unless the system is underloaded, no online scheduling algorithm can be 1-competitive, i.e., matching the performance of the optimal offline algorithm. Nevertheless, recent work has revealed that some online algorithms using a moderately faster processor (or e...
متن کاملFuzzy Programming for Parallel Machines Scheduling: Minimizing Weighted Tardiness/Earliness and Flow Time through Genetic Algorithm
Appropriate scheduling and sequencing of tasks on machines is one of the basic and significant problems that a shop or a factory manager encounters; this is why in recent decades extensive studies have been done on scheduling issues. One type of scheduling problems is just-in-time (JIT) scheduling and in this area, motivated by JIT manufacturing, this study investigates a mathematical model for...
متن کاملOnline Deadline Scheduling with Bounded Energy Efficiency
Existing work on scheduling with energy concern has focused on minimizing the energy for completing all jobs or achieving maximum throughput [19, 2, 7, 13, 14]. That is, energy usage is a secondary concern when compared to throughput and the schedules targeted may be very poor in energy efficiency. In this paper, we attempt to put energy efficiency as the primary concern and study how to maximi...
متن کاملEfficient Online Scheduling for Deadline-Sensitive Jobs
We consider mechanisms for online deadline-aware scheduling in large computing clusters. Batch jobs that run on such clusters often require guarantees on their completion time (i.e., deadlines). However, most existing scheduling systems implement fair-share resource allocation between users, an approach that ignores heterogeneity in job requirements and may cause deadlines to be missed. In our ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Journal of Discrete Algorithms
سال: 2006
ISSN: 1570-8667
DOI: 10.1016/j.jda.2005.12.001