کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
6882572 1443875 2018 16 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
An intelligent rule management scheme for Software Defined Networking
ترجمه فارسی عنوان
یک قانون مدیریت هوشمند برای شبکه های تعریف شده توسط نرم افزار
کلمات کلیدی
نرم افزار تعریف شده شبکه، مدیریت حکومت، به روز رسانی قانون، کش،
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر شبکه های کامپیوتری و ارتباطات
چکیده انگلیسی
Software Defined Networking (SDN) enables network innovation and brings flexibility by separation of the control and data planes and logically centralized control. However, this network paradigm complicates flow rule management. Current approaches generally install rules reactively after table misses or pre-installs them by flow prediction. Such approaches consume nontrivial network resources during interactions between the controller and switches (especially for maintaining consistency). In this paper, we explore an intelligent rule management scheme (IRMS), which extends the one-big-switch model and employs a hybrid rule management approach. To achieve this, we first transform all rules into path-based and node-based rules. Path-based rules are pre-installed whilst the paths for flows are selected at the edge switches of the network. To maintain consistency of forwarding paths, we update path-based rules as a whole and employ a lazy update policy. Node-based rules are optimally partitioned into disjoint chunks by an intelligent partition algorithm and organized hierarchically in the flow table. In this way, we significantly reduce the interaction cost between the control and data planes. This scheme enforces an efficient sliding window policy to enhance the hit rate for the installed chunks. We evaluate our scheme by comprehensive experiments. The results show that IRMS reduces the total flow entries by more than 59.9% on average and the update time by over 56%. IRMS also reduces the flow setup requests by more than one order of magnitude.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Computer Networks - Volume 144, 24 October 2018, Pages 77-88
نویسندگان
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