Analyzing Methods and Opportunities in Software-Defined (SDN) Networks for Data Traffic Optimizations

Computer networks are dynamic and require constant updating and monitoring of operations to meet the growing volume of data trafficked. This generates a number of cost issues as well as performance management and tuning to deliver granular quality of service (QoS), balancing data load, and controlling the occurrence of bottlenecks. As an alternative, a new programmable network paradigm has been used under the name of Software Defined Networks (SDN). The SDN consists of decoupling the data plane and controlling the network, where a programmable controller is responsible for managing rules for routing the data to various devices. Thus, the hardware that remains in the network data stream simply addresses the routing of the packets quickly according to these rules. In this context, this article conducts a study on different methods and approaches that are being used in the literature to solve problems in the optimization of data traffic in the network through the use of SDN. In particular, this study differs from other reviews of SDN because it focuses on issues such as QoS, load balancing, and congestion control. Finally, in addition to the review of the SDN's state-of-the-art in the areas mentioned, a survey of future challenges and research opportunities in the area is also presented. load balancing and congestion control. Finally, in addition to the review of the SDN's state-of-the-art in the areas mentioned, a survey of future challenges and research opportunities in the area is also presented. load balancing and congestion control. Finally, in addition to the review of the SDN's state-of-the-art in the areas mentioned, a survey of future challenges and research opportunities in the area is also presented

Acknowledge-Based Non-Congestion Estimation: An Indirect Queue Management Approach for Concurrent TCP and UDP-Like Flows

This paper presents a new approach for indirect Active Queue Management (indirect AQM) technique called Acknowledge-based Non-Congestion Estimation (ANCE), which employs end-to-end queue management along a network instead to use Explicit Congestion Notification (ECN) bit or to drop packets in the queue. The ANCE performance was compared with Random Early Detection (RED), Control Delay (CoDel), Proportional Integral controller Enhanced (PIE), Explicit Non-Congestion Notification (ENCN), TCP-Jersey and E-DCTCP schemes in a daisychain and in a dumbbell cenario, with TCP flows and UDP-like Networked Control Systems (NCS) flow sharing the same network topology. On the other hand, this paper presents a method for modeling, simulation and verification of communication systems and NCS, using UPPAAL software tool, on which, all network components (channels, routers, transmitters, receivers, plants, and Controllers) were modeled using timed automata making easy a formal verification of the whole modeled system. Simulations and statistical verification show that despite using fewer resources (since ANCE does not need the ECN bit) ANCE presents a very close performance  to ENCN overcoming Drop Tail, RED, CoDel, PIE and E-DCTCP in terms of Integral Time Absolute Error (ITAE) for NCS and fairness for TCP flows. ANCE also attains better performance than RED, PIE, TCP-Jersey and E-DCTCP in terms of throughput for TCP flows