دانلود مقاله ISI انگلیسی شماره 79169
عنوان فارسی مقاله

الگوریتم زمان بندی ترکیبی منابع آگاه در محاسبات توزیع شده ناهمگن

کد مقاله سال انتشار مقاله انگلیسی ترجمه فارسی تعداد کلمات
79169 2015 11 صفحه PDF سفارش دهید 7100 کلمه
خرید مقاله
پس از پرداخت، فوراً می توانید مقاله را دانلود فرمایید.
عنوان انگلیسی
Resource-aware hybrid scheduling algorithm in heterogeneous distributed computing
منبع

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

Journal : Future Generation Computer Systems, Volume 51, October 2015, Pages 61–71

کلمات کلیدی
تأمین منابع؛ زمانبندی وظایف؛ خوشه؛ محاسبات توزیع شده ناهمگن؛ برنامه های کاربردی رانده محتوای چند رسانه ای
پیش نمایش مقاله
پیش نمایش مقاله الگوریتم زمان بندی ترکیبی منابع آگاه در محاسبات توزیع شده ناهمگن

چکیده انگلیسی

Today, almost everyone is connected to the Internet and uses different Cloud solutions to store, deliver and process data. Cloud computing assembles large networks of virtualized services such as hardware and software resources. The new era in which ICT penetrated almost all domains (healthcare, aged-care, social assistance, surveillance, education, etc.) creates the need of new multimedia content-driven applications. These applications generate huge amount of data, require gathering, processing and then aggregation in a fault-tolerant, reliable and secure heterogeneous distributed system created by a mixture of Cloud systems (public/private), mobile devices networks, desktop-based clusters, etc. In this context dynamic resource provisioning for Big Data application scheduling became a challenge in modern systems. We proposed a resource-aware hybrid scheduling algorithm for different types of application: batch jobs and workflows. The proposed algorithm considers hierarchical clustering of the available resources into groups in the allocation phase. Task execution is performed in two phases: in the first, tasks are assigned to groups of resources and in the second phase, a classical scheduling algorithm is used for each group of resources. The proposed algorithm is suitable for Heterogeneous Distributed Computing, especially for modern High-Performance Computing (HPC) systems in which applications are modeled with various requirements (both IO and computational intensive), with accent on data from multimedia applications. We evaluate their performance in a realistic setting of CloudSim tool with respect to load-balancing, cost savings, dependency assurance for workflows and computational efficiency, and investigate the computing methods of these performance metrics at runtime.

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