New-flow based DDoS attacks in SDN: Taxonomy, rationales, and research challenges

A comprehensive survey of load balancing techniques in software-defined network

Software Defined Networking (SDN) is a new technology that makes computer networks farther programmable. SDN is currently attracting significant consideration from both academia and industry. SDN is simplifying organisations to implement applications and assist flexible delivery, offering the capability of scaling network resources in lockstep with application and data. This technology allows the user to manage the network easily by permitting the user to control the applications and operating system. SDN not only introduces new ways of interaction within network devices, but it also gives more flexibility for the existing and future networking designs and operations. SDN is an innovative approach to design, implement, and manage networks that separate the network control (control plane) and the forwarding process (data plane) for a better user experience. The main differentiation between SDN and Traditional Networking is that SDN removes the decision-making part from the routers and it provides, logically, a centralised Control-Plane that creates a network view for the control and management applications. Through the establishment of SDN, many new network capabilities and services have been enabled, such as Software Engineering, Traffic Engineering, Network Virtualisation and Automation, and Orchestration for Cloud Applications. This paper surveys the state-of-the-art contribution such as a comparison between SDN and traditional networking. Also, comparison with other survey works on SDN, new information about controller, details about OpenFlow architecture, configuration, comprehensive contribution about SDN security threat and countermeasures, SDN applications, benefit of SDN, and Emulation & Tested for SDN. In addition, some existing and representative SDN tools from both industry and academia are explained. Moreover, future direction of SDN security solutions is discussed in detail.

A survey on the architecture, application, and security of software defined networking: challenges and open issues

Toward an optimal solution against Denial of Service attacks in Software Defined Networks

In order to adapt to the rapid development of cloud computing, big data, and other technologies, the combination of data center networks and SDN is proposed to make network management more convenient and flexible. With this advantage, routing strategies have been extensively studied by researchers. However, the strategies in the controller mainly rely on manual design, the optimal solutions are difficult to be obtained in the dynamic network environment. So the strategies based on artificial intelligence (AI) are being considered. This paper proposes a novel routing strategy based on deep Q-learning (DQL) to generate optimal routing paths autonomously for SDN-based data center networks. To satisfy the different demands of mice-flows and elephant-flows in data center networks, deep Q networks are trained for them respectively to achieve low latency and low packet loss rate for mice-flows as well as high throughput and low packet loss rate for elephant-flows. Furthermore, with the consideration of the distribution of traffic and the limited resources of data center networks and SDN, we choose port rate and flow table utilization to describe the network state. Simulation results show that compared with Equal-Cost Multipath (ECMP) routing and Selective Randomized Load Balancing (SRL)+FlowFit, the proposed routing scheme can reduce both the average delay of mice-flows and average packet loss rate, while increase the average throughput of elephant-flows.

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Kuan yin Chen

Papers

Balancing flow table occupancy and link utilization in software-defined networks