Search Results (6)

The clustering methods of Software-Defined Networking (SDN) have gained popularity due to their ability to offer improved scalability, consistency, dependability, and load balancing within overlay networks and SDN partitions. This paper delved into the effects of increasing the number of OpenFlow-enabled southbound devices on the establishment and coordination of SDN-controller clusters. Specifically, we examined the volume of east–west cluster packet communications concerning the number of southbound devices within the topology. Many research studies have focused on bandwidth and the number of bytes in east–west communication. While bandwidth refers to the maximum rate at which data can be transferred, and the number of bytes reflects the volume of data being transmitted, the number of packet communications directly influences the efficiency and responsiveness of network operations. Our investigation encompassed the impact of SDN controller-to-controller communication within the cluster concerning the rising number of OpenFlow switches connected to various topologies, including tree (star-bus network), linear, and torus configurations. This study provided data on communication patterns within Open Network Operating Systems (ONOS) and OpenDaylight (ODL) clusters, revealing differing levels of controller communication with southbound network expansions. We evaluated the scalability of ODL and ONOS controllers by scrutinising the effect of increasing the number of southbound devices on the control communication volume. Our analysis revealed varied communication patterns within ONOS and ODL clusters, resulting in different volumes of control communication with southbound expansions. The findings indicated that in small-to-medium-sized SDNs, ODL outperformed ONOS, notably with faster cluster discovery. Conversely, ONOS demonstrated greater efficiency in larger networks owing to its centralised communication architecture. Finally, we provide recommendations for selecting the most suitable controllers based on the size of southbound networks, aiming to provide practical guidelines for optimal network performance. Full article

The Software-Defined Network (SDN) is a next-generation network that uses OpenFlow to decouple the control plane from the data plane of forwarding devices. Other protocols for southbound interfaces include ForCES and POF. However, some security issues might be in action on the SDN, so that attackers can take control of the SDN control plane. Since live video calling, QoS control, high bandwidth needs, and resource management are inevitable in any SDN/Software-Defined Cellular Network (SDCN), traffic monitoring is an integral approach for safeguarding against DDoS, heavy hitters, and superspreaders. In such a scenario, SDN traffic measurement comes into action. Thus, we survey SDN traffic measurement solutions to assess how these solutions can make a secure, efficient, and robust SDN/SDCN architecture. This research classifies SDN traffic measurement solutions according to network application behavior and compares several ML approaches. Furthermore, we find out the challenges related to SDN/SDCN traffic measurement and the future scope of research, which will guide the design and development of more advanced traffic measurement solutions for a scalable, heterogeneous, hierarchical, and widely deployed SDN/SDCN architecture. In more detail, we list different kinds of practical machine learning (ML) approaches to analyze how we can improve traffic measurement performances. We conclude that using ML in SDN traffic measurement solutions will help secure SDNs/SDCNs in complementary ways. Full article

With the rapid evolution of network technologies over recent years, emerging network services, especially industrial control networks, video conferencing, intelligent driving, and other scenarios, have put forward higher demand for the low-latency forwarding of network traffic. The existing flow caching and hardware acceleration methods only improve the overall forwarding performance of data-plane devices but cannot separate the forwarding process of low-latency traffic from others to reflect the priority of these flows. In this paper, we extend the POF southbound interface protocol and propose a marking method for low-latency flows, based on which we design a composite pipeline to achieve fast processing for low-latency traffic by introducing a fast-forwarding path. The experiments show that the fast path has a higher forwarding capability than the MAT pipeline in the POF Switch and can reduce the forwarding delay of low-latency flows by 62–68%. In a real network environment with a mixed traffic simulation, the reduction reaches 17–20% with no delay increment for the non-low-latency part. Full article

Software-Defined Network (SDN), which is recommended as a new generation of the network, a substitute for TCP/IP network, has the characteristics of separation of data plane and control plane. Although the separation of the control plane brings a high degree of freedom and simple operation and maintenance, it also increases the cost of north–south communication. There are many additional modules for SDN to modify and enhance the basic functions of SDN. This paper proposes a message queue-based northbound communication mechanism, which pre-categorizes messages from the data plane and accurately pushes them to the apps potentially interested. This mechanism improves the efficiency of northbound communication and apps’ execution. Furthermore, it supports both OpenFlow and the protocol-independent southbound interface, and it has strong compatibility. Experiments have proved that this mechanism can reduce the control-response latency by up to 41% when compared with the normal controller northbound communication system, and it also improves the network situation of the data plane, such as real-time bandwidth. Full article

Prediction systems present some challenges on two fronts: the relation between video quality and observed session features and on the other hand, dynamics changes on the video quality. Software Defined Networks (SDN) is a new concept of network architecture that provides the separation of control plane (controller) and data plane (switches) in network devices. Due to the existence of the southbound interface, it is possible to deploy monitoring tools to obtain the network status and retrieve a statistics collection. Therefore, achieving the most accurate statistics depends on a strategy of monitoring and information requests of network devices. In this paper, we propose an enhanced algorithm for requesting statistics to measure the traffic flow in SDN networks. Such an algorithm is based on grouping network switches in clusters focusing on their number of ports to apply different monitoring techniques. Such grouping occurs by avoiding monitoring queries in network switches with common characteristics and then, by omitting redundant information. In this way, the present proposal decreases the number of monitoring queries to switches, improving the network traffic and preventing the switching overload. We have tested our optimization in a video streaming simulation using different types of videos. The experiments and comparison with traditional monitoring techniques demonstrate the feasibility of our proposal maintaining similar values decreasing the number of queries to the switches. Full article

We explain the notion of software-defined networking (SDN), whose southbound interface may be implemented by the OpenFlow protocol. We describe the operation of OpenFlow and summarize the features of specification versions 1.0–1.4. We give an overview of existing SDN-based applications grouped by topic areas. Finally, we point out architectural design choices for SDN using OpenFlow and discuss their performance implications. Full article