دانلود مقاله ISI انگلیسی شماره 74227
عنوان فارسی مقاله

کشف منابع تطبیقی در رایانش ابری موبایل

کد مقاله سال انتشار مقاله انگلیسی ترجمه فارسی تعداد کلمات
74227 2014 11 صفحه PDF سفارش دهید محاسبه نشده
خرید مقاله
پس از پرداخت، فوراً می توانید مقاله را دانلود فرمایید.
عنوان انگلیسی
Adaptive resource discovery in mobile cloud computing
منبع

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

Journal : Computer Communications, Volume 50, 1 September 2014, Pages 119–129

کلمات کلیدی
کشف منابع تطبیقی؛ صرفه جویی در انرژی - شبکه های بی سیم ناهمگن؛ رایانش ابری موبایل
پیش نمایش مقاله
پیش نمایش مقاله کشف منابع تطبیقی در رایانش ابری موبایل

چکیده انگلیسی

Mobile cloud computing (MCC) is aimed at integrating mobile devices with cloud computing. It is one of the most important concepts that have emerged in the last few years. Mobile devices, in the traditional agent-client architecture of MCC, only utilize resources in the cloud to enhance their functionalities. However, modern mobile devices have many more resources than before. As a result, researchers have begun to consider the possibility of mobile devices themselves sharing resources. This is called the cooperation-based architecture of MCC. Resource discovery is one of the most important issues that need to be solved to achieve this goal. Most of the existing work on resource discovery has adopted a fixed choice of centralized or flooding strategies. Many improved versions of energy-efficient methods based on both strategies have been proposed by researchers due to the limited battery life of mobile devices. This paper proposes a novel adaptive method of resource discovery from a different point of view to distinguish it from existing work. The proposed method automatically transforms between centralized and flooding strategies to save energy according to different network environments. Theoretical models of both energy consumption and the quality of response information are presented in this paper. A heuristic algorithm was also designed to implement the new adaptive method of resource discovery. The results from simulations demonstrated the effectiveness of the strategy and the efficiency of the proposed heuristic method.

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