Openflow-Based Load Balancing Gone Wild (MSE thesis)
Today’s data centers host online services on multiple servers, with a front-end load balancer directing each client request to a particular replica. Dedicated load balancers are expensive and quickly become a single point of failure and congestion. The OpenFlow standard enables an alternative approach where the commodity network switches divide traffic over the server replicas, based on packet-handling rules installed by a separate controller. However, the simple approach of installing a separate rule for each client connection (or “microflow”) leads to a huge number of rules in the switches and a heavy load on the controller. We argue that the controller should exploit switch support for wildcard rules for a more scalable solution that directs large aggregates of client traffic to server replicas. We present algorithms that compute concise wildcard rules that achieve a target distribution of the traffic, and automatically adjust to changes in load-balancing policies without disrupting existing connections. We implement these algorithms on top of the NOX OpenFlow controller, evaluate their effectiveness, and propose several avenues for further research.