The emergence of OpenFlow and Software Defined Networks brings new perspectives into how we design the next generation networks, where the number of base stations/access points as well as the devices per subscriber will be dramatically higher. In suc
h dense environments, devices can communicate with each other directly and can attach to multiple base stations (or access points) for simultaneous data communication over multiple paths. This paper explores how networks can maximally enable this multi-path diversity through network programmability. In particular, we propose programmable flow clustering and set policies for inter-group as well as intra-group wireless scheduling. Further, we propose programmable demultiplexing of a single network flow onto multiple paths before the congestion areas and multiplexing them together post congestion areas. We show the benefits of such programmability first for legacy applications that cannot take advantage of multi-homing without such programmability. We then evaluate the benefits for smart applications that take advantage of multi-homing by either opening multiple TCP connections over multiple paths or utilizing a transport protocol such as MP-TCP designed for supporting such environments. More specifically, we built an emulation environment over Mininet for our experiments. Our evaluations using synthetic and trace driven channel models indicate that the proposed programmability in wireless scheduling and flow splitting can increase the throughput substantially for both the legacy applications and the current state of the art.
In this paper, we propose a distributed OpenFlow controller and an associated coordination framework that achieves scalability and reliability even under heavy data center loads. The proposed framework, which is designed to work with all existing Ope
nFlow controllers with minimal or no required changes, provides support for dynamic addition and removal of controllers to the cluster without any interruption to the network operation. We demonstrate performance results of the proposed framework implemented over an experimental testbed that uses controllers running Beacon.
