کد مقاله کد نشریه سال انتشار مقاله انگلیسی ترجمه فارسی نسخه تمام متن
4950286 1364283 2018 11 صفحه PDF ندارد دانلود رایگان
عنوان انگلیسی مقاله
Reprint of “Multi-QoS constrained and Profit-aware scheduling approach for concurrent workflows on heterogeneous systems”
کلمات کلیدی
Quality of service; On-line scheduling; Deadline; Budget;
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر نظریه محاسباتی و ریاضیات
پیش نمایش صفحه اول مقاله
Reprint of “Multi-QoS constrained and Profit-aware scheduling approach for concurrent workflows on heterogeneous systems”
چکیده انگلیسی

•A new dynamic resource management algorithm for concurrent workflows.•Profit-aware algorithm that complies to users QoS requirements.•Concurrent scheduling constrained to individual time and cost constraints.•A realistic simulation that considers a bounded multi-port model.•Results for randomly generated graphs as well as for real-world applications.

The execution of a workflow application can result in an imbalanced workload among allocated processors, ultimately resulting in a waste of resources and a higher cost to the user. Here, we consider a dynamic resource management system in which processors are reserved not for a job but only to run a task, thus allowing a higher resource usage rate. This paper presents a scheduling algorithm that manages concurrent workflows in a dynamic environment in which jobs are submitted by users at any moment in time, on shared heterogeneous resources, and constrained to a specified budget and deadline for each job. Recent research attempted to propose dynamic strategies for concurrent workflows but only addressed fairness in resource sharing among applications while minimizing the execution time. The Multi-QoS Profit-Aware scheduling algorithm (MQ-PAS) proposed here is able to increase the profit achieved by the provider by considering the budget available for each job to define tasks priorities. We study the scalability of the algorithm with different types of workflows and infrastructures. The experimental results show that our strategy improves provider revenue significantly and obtains comparable successful rates of completed jobs.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Future Generation Computer Systems - Volume 78, Part 1, January 2018, Pages 402-412
نویسندگان
, ,