Dynamically Creating Custom SDN High-Speed Network Paths for Big Data Science Flows

Existing campus network infrastructure is not designed to effectively handle the transmission of big data sets. Performance degradation in these networks is often caused by middleboxes -- appliances that enforce campus-wide policies by deeply inspecting all traffic going through the network (including big data transmissions). We are developing a Software-Defined Networking (SDN) solution for our campus network that grants privilege to science flows by dynamically calculating routes that bypass certain middleboxes to avoid the bottlenecks they create. Using the global network information provided by an SDN controller, we are developing graph databases approaches to compute custom paths that not only bypass middleboxes to achieve certain requirements (e.g., latency, bandwidth, hop-count) but also insert rules that modify packets hop-by-hop to create the illusion of standard routing/forward despite the fact that packets are being rerouted. In some cases, additional functionality needs to be added to the path using network function virtualization (NFV) techniques (e.g., NAT). To ensure that path computations are run on an up-to-date snapshot of the topology, we introduce a versioning mechanism that allows for lazy topology updates that occur only when "important" network changes take place and are requested by big data flows.