دانلود مقاله ISI انگلیسی شماره 79259
عنوان فارسی مقاله

الگوریتم های زمان بندی برای انجام اندازه گیری های رایگان از درگیری در شبکه های پوشش

کد مقاله سال انتشار مقاله انگلیسی ترجمه فارسی تعداد کلمات
79259 2008 12 صفحه PDF سفارش دهید محاسبه نشده
خرید مقاله
پس از پرداخت، فوراً می توانید مقاله را دانلود فرمایید.
عنوان انگلیسی
Scheduling algorithms for conducting conflict-free measurements in overlay networks
منبع

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

Journal : Computer Networks, Volume 52, Issue 15, 23 October 2008, Pages 2819–2830

کلمات کلیدی
برنامه ریزی اندازه گیری؛ شبکه های پوشش؛ تضاد اندازه گیری؛ نظارت بر شبکه
پیش نمایش مقاله
پیش نمایش مقاله الگوریتم های زمان بندی برای انجام اندازه گیری های رایگان از درگیری در شبکه های پوشش

چکیده انگلیسی

Network monitoring is essential to the correct and efficient operation of ISP networks and the kind of applications they support, and active measurement is a key design problem in network monitoring. Unfortunately, almost all active probing algorithms ignore the measurement conflict problem: Active measurements conflict with each other – due to the nature of these measurements, the associated overhead, and the network topology – which leads to reporting incorrect results. In this paper, we consider the problem of scheduling periodic QoS measurement tasks in overlay networks. We first show that this problem is NP-hard, and then propose two conflict-aware scheduling algorithms for uniform and non-uniform tasks whose goal is to maximize the number of measurement tasks that can run concurrently, based on a well-known approximation algorithm. We incorporate topological information to devise a topology-aware scheduling algorithm that reduces the number of time slots required to produce a feasible measurement schedule. Also, we study the conflict-causing overlap among overlay paths using various real-life Internet topologies of the two major service carriers in the US. Experiments conducted using the PlanetLab testbed confirm that measurement conflict is a real issue that needs to be addressed. Simulation results show that our algorithms achieve at least 25% better schedulability over an existing algorithm. Finally, we discuss various practical considerations, and identify several interesting research problems in this context.

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