I-Corps: Intelligent Multi-layer Network Optimization

Cornell University, Ithaca NY

Investigators

Abstract

The broader impact/commercial potential of this I-Corps project is to improve long distance data transmission. The global consumer internet traffic experiences annual growth requiring continuous improvement in internet backbone efficiency. A wide range of industries are impacted by such improvements. Some applications, such as smart cities, require considerable improvements in infrastructure network efficiency. For example, in order to accomplish smart cities with the heterogeneous applications on Internet of Things (IoT), improving infrastructure network efficiency is necessary. Furthermore, the fifth generation (5G) wireless network as the next generation mobile system is also reliant on a resilient high speed telecommunication backbone network. On a broad scale, these improvements to networks will increase efficiency of data centers and computing platforms and can improve the energy efficiency of such systems. Dynamic multi-layer network optimization will make networks adaptable to traffic variation and potential failure events, and consequently eliminate the costly and wasteful over provisioning of system resources. This I-Corps project explores the commercialization path for telecommunication networks optimization technology. This method monitors traffic requirements from higher layers and performs multi-layer optimization on the optical and internet protocol layers. It achieves improvements in data transmission speed and network resource usage while guaranteeing network stability. These techniques do not require prior knowledge of the network equipment specifications, are scalable, provide high accuracy and are able to adjust and learn changes on the network. The implementation feasibility has been successfully demonstrated in small-scale prototypes and the performance improvements at scale has been extensively studies by numerical evaluations proving up to 2x improvement in transmission speed and 10 percent reduction in equipment usage.