Papers by Cristian Machado
Software-Defined Networking (SDN) permits centralizing part of the decision-logic in controller d... more Software-Defined Networking (SDN) permits centralizing part of the decision-logic in controller devices. Thus, controllers can have an overall view of the network, assisting network programmers to configure network-wide services. Despite this, the behavior of network devices and their configurations are often written for specific situations directly in the controller. As an alternative, techniques such as Policy-Based Network Management (PBNM) can be used by business-level operators to write Service Level Agreements (SLAs) in a user-friendly interface without the need to change the code implemented in the controllers. In this paper, we introduce a framework for Policy Authoring to (i) facilitate the specification of businesslevel goals and (ii) automate the translation of these goals into the configuration of system-level components in an SDN. We use information from the network infrastructure obtained through SDN features and logic reasoning for analyzing policy objectives. As a re...
2015 IEEE 14th International Symposium on Network Computing and Applications, 2015
Software-Defined Networking (SDN) aims to alleviate the limitations imposed by traditional IP net... more Software-Defined Networking (SDN) aims to alleviate the limitations imposed by traditional IP networks by decoupling network tasks performed on each device in particular planes. This approach offers several benefits, such as standard communication protocols, centralized network functions, and specific network elements, for example, controller devices. Despite these benefits, there is still a lack of adequate support for performing tasks related to traffic classification, because (i) there are traffic profiles that are very similar, which makes their classification difficult (e.g., both HTTP and DNS flows are characterized by packet bursts); (ii) OpenFlow, the key SDN implementation today, only offers native flow features, such as packet and byte count, that do not describe intrinsic traffic profiles; and (iii) there is a lack of support to determine what is the optimal set of flow features to characterize different types of traffic profiles. In this paper, we introduce an architecture to collect, extend, and select flow features for traffic classification in OpenFlow-based networks. The main goal of our solution is to offer an extensive set of flow features that can be analyzed and refined and to be capable of finding the optimal subset of features to classify different types of traffic flows. The experimental evaluation of our proposal shows that some features emerge as meaningful, occupying the top positions for the classification of distinct flows in different experimental scenarios.
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Papers by Cristian Machado