SBIR Phase II: High Frequency Network Traffic Optimization

Waltz Networks, Inc., Ithaca NY

Investigators

Abstract

The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase II project is that it will dramatically increase the efficiency of communications networks. Commercially, the ability to dynamically, adaptively and optimally route traffic on data networks will lead to network cost savings ranging from 60% - 70% for network service providers. Critically, the project leverages the recent industry shift towards software-defined networking (SDN) that is projected to become a $45 billion market by 2020. The excitement behind SDN is driven primarily by the promised performance benefits of better traffic control. By bringing to market its provably optimal, dynamic and adaptive traffic control algorithms, the company will be uniquely positioned to capitalize on this market opportunity. The immediate resulting social impact will be that end users will have access to faster, cheaper and more robust data networks. In the longer term, efficient software control of networks will enable rapid innovation in networking leading to new network applications that have not even been envisioned yet. The project also enhances technological and scientific understanding by commercially verifying the company's solution to a longstanding open problem in networking - namely, whether an easy to deploy, dynamic, adaptive and optimal routing algorithm can be found. This Small Business Innovation Research (SBIR) Phase II project focuses on delivering commercial, smart, traffic control algorithms that can unlock the full capacity of modern communications networks. Today, due to unprecedented traffic growth, network operators face major challenges in the form of efficient resource utilization. The problem is that the inherent randomness of data traffic has led to network designers over-provisioning networks to the point where they run at 30% - 40% utilization on average. The company's competitive advantage is a new algorithm that allows it to optimally manage traffic variations by adjusting network routes in real time while retaining the scalability and simplicity of today's protocols. The goal in this project is to build on the beta tests from Phase I by developing an enterprise-grade, cloud-based network control application that is ready for general market launch. To this end, the company will start with small commercial deployments at selected test partners. Feedback from these deployments will be used to iron out any issues before general market launch. By the end of the project, the company anticipates generating significant revenue from initial customers as it continues to innovate and maintain its current lead in developing SDN control plane software.