NeTS: Small: Collaborative Research: Lightweight Adaptive Algorithms for Network Optimization at Scale towards Emerging Services

University Of Minnesota-Twin Cities, Minneapolis MN

Investigators

Abstract

The past decade has witnessed enormous transformations of information technologies. The era of cloud computing transformed how information is delivered. With more and more devices becoming ``smarter'' and ``plugged'' into the Internet (through embedded microprocessors and communication chipsets), we are entering into a new era of ``Internet of Things'' (IoT) and cyber-physical systems where the cyber world and physical world are increasingly integrated through a variety of sensors and actuators that are planted into the physical world but controlled through the cyber world. Both today's cloud services and emerging IoT applications alter the point-to-point communication paradigm of the existing IP Internet architecture, and require increasingly demanding quality-of-service (QoS) requirements. These requirements call for scalable and intelligent network algorithms for controlling and coordinating various network components and managing and optimizing resource allocations, with capabilities 1) to meet ever stringent availability, reliability and QoS requirements demanded by emerging services; 2) to cope with the enormous complexity of networked systems; 3) to effectively exploit the rich diversity and redundancy inherent in such complex systems as well as the new capabilities offered by new networking architectures and technologies. This project puts forth a three-plane view of networking as a conceptual framework to structure network functions and guide us in the network algorithmic designs for timely, resilient and resource-efficient information delivery: 1) an information plane capturing application semantics and requirements; 2) a (logically) centralized control plane; and 3) a distributed (programmable) communication (data) plane. This project postulates two design principles and challenges in network algorithms: a) the need for co-design of centralized and distributed network algorithms that can take advantage of a centralized control plane with a global view of the network state, while also enabling the distributed (programmable) network elements to make fast and intelligent decisions to adapt to the changes in the network conditions (e.g., failures); and b) the need for just-in-time (near) optimality as a key metric to gauge and guide the design of network algorithms for timely, resilient and resource-efficient information delivery. The goal of the proposed project is to develop scalable, lightweight, and adaptive algorithms for scalable and intelligent network control and optimization. The research on new network algorithms will contribute to the development of new networking technologies. The project will actively involve undergraduate students - especially female students and underrepresented minorities in the research project, e.g., via NSF REU grants as well as senior design courses and the Undergraduate Research Opportunity Programs at the PIs' institutions. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.