ETDP: enhanced topology discovery protocol for software-defined networks

Discovering network elements in a dynamic and optimized manner and being able to contend with ever-growing traffic is a key requirement for current networking environments. In software-defined networks (SDNs), the controller collects the topology information from the data plane and maintains an abstract view of the entire network, which is crucial for the proper functioning of applications and network services. However, there is still the need for an enhanced protocol for automatic discovery and mechanisms of autoconfiguration of network elements according to new policies and business requirements. To overcome this challenge, this paper presents a novel protocol that, unlike existing approaches, enables a distributed layer-2 discovery without the need for previous network configurations or controller knowledge of the network. By using this mechanism, the SDN controller can discover the network view without incurring scalability issues, while taking advantage of the shortest control paths toward each switch. The obtained results show that our enhanced protocol is efficient in terms of time and message load over a wide range of generated networks and outperforms the state-of-the-art techniques.Peer ReviewedPostprint (published version

A flow-level extension to OMNeT++ for long simulations of large networks

This letter presents a Flow-Level Extension to OMNeT++ (FLEO) that allows a discrete event simulator to operate on flows of traffic, and so simulate larger networks for longer periods of time for a given set of computation and memory resources compared with packet-based simulation. FLEO simulations of link utilization are accurate to within 0.2% of a packet-based simulation, yet run 30 to 90 times faster than packet-based simulation. These characteristics make it suitable for the simulation of streaming media, which comprises the majority of data usage today, as well as investigation of traffic engineering within a network, for example, using software-defined networking