Virtual topology control with multistate neural associative memories

Previously, a highly adaptive virtual network topology (VNT) reconfiguration method called Attractor Selection Based (ASB) topology control was presented. ASB has an important drawback: it can only work with binary path tables. We propose a novel VNT controller by adding multistate path capabilities into ASB. However, adding multistate path capabilities reduces topology exploration space. We solve this problem by changing the system dynamics of ASB. With the modification of the system dynamics and the extension from binary to multistate paths, we observed a 60% performance improvement over ASB, and a 21% reduction in processing time in the simulations.