Multicasting in Network Function Virtualization (NFV) Environment

Network Function Virtualization is a growing concept in the research field because of its ability to decouple network functions, like network address translation (NAT), domain name service (DNS), firewall, intrusion detection (IDS) etc., from proprietary hardware equipment. They can now run in software making the network more flexible and agile. This also reduces hardware and maintenance costs of the network. Nowadays many applications use multicasting as it saves a huge amount of communication bandwidth. But many packets need intermediary processing before reaching their destinations. For this processing, Virtual Network functions (VNFs) are implemented in the network where processing of packets takes place. Because of this the path through which the packets traverse changes, and delay increases. This project considers different number and placements of VNFs in four real-world topologies namely NSFNET, Cost239, Arpanet and Random12, and observes the delay for every case. As the VNFs are duplicated on different nodes in the network, the cost of deployment and maintenance of VNFs is increased, but the delay decreases up to a certain number of VNFs. After this, the delay becomes constant. This project presents this trade-off between cost and delay

Online Multicast Traffic Engineering for Software-Defined Networks

Previous research on SDN traffic engineering mostly focuses on static traffic, whereas dynamic traffic, though more practical, has drawn much less attention. Especially, online SDN multicast that supports IETF dynamic group membership (i.e., any user can join or leave at any time) has not been explored. Different from traditional shortest-path trees (SPT) and graph theoretical Steiner trees (ST), which concentrate on routing one tree at any instant, online SDN multicast traffic engineering is more challenging because it needs to support dynamic group membership and optimize a sequence of correlated trees without the knowledge of future join and leave, whereas the scalability of SDN due to limited TCAM is also crucial. In this paper, therefore, we formulate a new optimization problem, named Online Branch-aware Steiner Tree (OBST), to jointly consider the bandwidth consumption, SDN multicast scalability, and rerouting overhead. We prove that OBST is NP-hard and does not have a $|D_{max}|^{1-\epsilon}$-competitive algorithm for any $\epsilon >0$, where $|D_{max}|$ is the largest group size at any time. We design a $|D_{max}|$-competitive algorithm equipped with the notion of the budget, the deposit, and Reference Tree to achieve the tightest bound. The simulations and implementation on real SDNs with YouTube traffic manifest that the total cost can be reduced by at least 25% compared with SPT and ST, and the computation time is small for massive SDN.Comment: Full version (accepted by INFOCOM 2018