کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
431931 688662 2011 14 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Task assignment in multiple server farms using preemptive migration and flow control
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر نظریه محاسباتی و ریاضیات
پیش نمایش صفحه اول مقاله
Task assignment in multiple server farms using preemptive migration and flow control
چکیده انگلیسی

Existing task assignment policies proposed for assigning tasks in stand-alone server farms are not efficient in multiple server farm environments because they have not been designed to exploit the properties of such environments. With the emergence of high speed networks and operating systems that have features such as preemptive migration, the importance of designing task assignment policies for assigning tasks in multiple server farms has increased. Such policies can result in better overall performance compared to those that optimise performance in stand-alone server farms.This paper proposes a task assignment policy suitable for assigning tasks in multiple server farms. The proposed policy, called Multi-Cluster Task Assignment based on Preemptive Migration (MCTPM) is based on a multi-tier host architecture that reduces the variance of task sizes in host queues by processing tasks with similar sizes using a set of hosts that have a distinct task size range. MCTPM controls the traffic flow into server farms via a global dispatching device so as to optimise the performance. MCTPM supports preemptive task migration between servers in the same farm and between servers in different farms.Performance analysis of the proposed policy indicates that significant performance improvements are possible under a wide range of workload scenarios. For example, MCTPM outperforms existing policies such as MC-Random, MC-TAGSPM and MC-MTTPM by factors of 190190, 55 and 10.510.5 respectively under certain scenarios.

▸ An efficient task assignment policy for assigning tasks in multiple server farms. ▸ Multi-tier host architectures provide greater flexibility and variance reduction. ▸ An analytical model which incorporates the migration cost. ▸ Preemptive migration and flow control can result in better performance.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Journal of Parallel and Distributed Computing - Volume 71, Issue 12, December 2011, Pages 1608–1621
نویسندگان
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