Scalability of ONOS reactive forwarding applications in ISP networks

Software Defined Networking (SDN) is a powerful approach that enhances network control and management, and provides a flexible way to develop network applications. However, scalability of SDN networks is an important concern for many network operators. The main peculiarities of SDN when applied to an Internet Service Provider (ISP) network are the large geographical extension and the need of in-band transmission of control traffic. Therefore, the control traffic exchanged between the SDN controller and the network nodes must be carefully evaluated for the network design and dimensioning. We consider an ISP network controlled by the recently ONOS (Open Network Operating System) controller developed by ON.Lab. We devise a quantitative model to compute the exact number of exchanged OpenFlow messages and the corresponding bandwidth needed to install a traffic flow when running the default ONOS layer-2 forwarding applications. We compute also the exact number of flow rules installed in each switch. We show the general applicability of our models for a Point Of Presence (POP) network and for a large set of real nation-wide and world-wide ISP networks. Our quantitative models can be used for a safe network planning also when the network applications are not fully reactive

ONOS-Controlled Disaggregated Optical Networks

State-of-art, potentials and limitations of the ONOS controller applied to disaggregated optical networks are reported. Focus is on the on-going ODTN project. Results of experimental demonstrations are reported to prove the feasibility of proposed approach

On routing scalability in flat SDN architectures

The rigidity of traditional network architectures, with tightly coupled control and data planes, impair their ability to adapt to the dynamic requirements of future application domains, such as the Tactile Internet or Holographic-Type Communications. Software-Defined Networking (SDN) architectures, which provide programmability to configure the network, have the potential to provide the required dynamism. However, given its centralized essence, SDN suffers from scalability issues. Therefore, efforts have been made to propose alternative decentralized solutions, such as the flat distributed SDN architecture. Despite its potential, the real applicability and scalability of decentralized SDN solutions are still open research questions. This paper presents a comparative analysis of the effects of different routing approaches on the scalability of flat distributed SDN architectures. Using the Open Network Operating System (ONOS) as our evaluation architecture, we have studied the tradeoff between routing overhead in the control data plane and inter-controller communications for different degrees of decentralization. We have found that routing applications, which only require control-data plane communication for setting the path, benefit more from decentralization than the ones which utilize inter-controller communications and ensure Quality of Service (QoS). Our findings highlight the need for efficient routing mechanisms to deal with inter-controller overhead while lowering the amount of control-data plane communication

Traffic management with elephant flow detection in software defined networks (SDN)

Multipath routing is to distribute the incoming traffic load among available paths between source and destination hosts. Instead of using the single best path, multipath scheme can avoid the congested path. Equal Cost Multi-Path (ECMP) performs the static traffic splitting based on some tuples of the packet headers. The limitation of ECMP does not consider the network parameters such as bandwidth and delay. Unlike the traditional networks, Software-Defined Network (SDN) has many advantages to support dynamic multipath forwarding due to its special characteristics, such as separation of control and data planes, global centralized control, and programmability of network behavior. In this paper, we propose a new architecture design for dynamic multipath-based traffic management approach in the SDN, which comprises of five components: detecting long (elephant) flow, computing shortest paths, estimating end-to-end delay and bandwidth utilization, calculating least cost path and rerouting traffic flow from the ongoing path to the best path. The simulation environment is created through the usage of Mininet emulator and ONOS controller. The evaluation outcomes show that the proposed traffic management method outperforms the ECMP and reactive forwarding method for both TCP and UDP traffic

Tennison: A Distributed SDN Framework for Scalable Network Security

Despite the relative maturity of the Internet, the computer networks of today are still susceptible to attack. The necessary distributed nature of networks for wide area connectivity has traditionally led to high cost and complexity in designing and implementing secure networks. With the introduction of software-defined networks (SDNs) and network functions virtualization, there are opportunities for efficient network threat detection and protection. SDN's global view provides a means of monitoring and defense across the entire network. However, current SDN-based security systems are limited by a centralized framework that introduces significant control plane overhead, leading to the saturation of vital control links. In this paper, we introduce TENNISON, a novel distributed SDN security framework that combines the efficiency of SDN control and monitoring with the resilience and scalability of a distributed system. TENNISON offers effective and proportionate monitoring and remediation, compatibility with widely available networking hardware, support for legacy networks, and a modular and extensible distributed design. We demonstrate the effectiveness and capabilities of the TENNISON framework through the use of four attack scenarios. These highlight multiple levels of monitoring, rapid detection, and remediation, and provide a unique insight into the impact of multiple controllers on network attack detection at scale