دانلود مقاله ISI انگلیسی شماره 76295
ترجمه فارسی عنوان مقاله

مدیریت منابع خود مختار مبتنی بر مجازی سازی برای برنامه های وب چند لایه در مرکز داده های مشترک

عنوان انگلیسی
Virtualization-based autonomic resource management for multi-tier Web applications in shared data center
کد مقاله سال انتشار تعداد صفحات مقاله انگلیسی
76295 2008 18 صفحه PDF
منبع

Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)

Journal : Journal of Systems and Software, Volume 81, Issue 9, September 2008, Pages 1591–1608

ترجمه کلمات کلیدی
محاسبات خود مختار؛ تخصیص منابع؛ نرم افزار وب سایت چند لایه؛ مدل سازی عملکرد
کلمات کلیدی انگلیسی
Autonomic computing; Resource allocation; Multi-tier Web application; Performance modeling
پیش نمایش مقاله
پیش نمایش مقاله  مدیریت منابع خود مختار مبتنی بر مجازی سازی برای برنامه های وب چند لایه در مرکز داده های مشترک

چکیده انگلیسی

As large data centers emerge, which host multiple Web applications, it is critical to isolate different application environments for security reasons and to provision shared resources effectively and efficiently to meet different service quality targets at minimum operational cost. To address this problem, we developed a novel architecture of resource management framework for multi-tier applications based on virtualization mechanisms. Key techniques presented in this paper include (1) establishment of the analytic performance model which employs probabilistic analysis and overload management to deal with non-equilibrium states; (2) a general formulation of the resource management problem which can be solved by incorporating both deterministic and stochastic optimizing algorithms; (3) deployment of virtual servers to partition resource at a much finer level; and (4) investigation of the impact of the failure rate to examine the effect of application isolation. Simulation experiments comparing three resource allocation schemes demonstrate the advantage of our dynamic approach in providing differentiated service qualities, preserving QoS levels in failure scenarios and also improving the overall performance while reducing the resource usage cost.