WNOS: Enabling Principled Software-Defined Wireless Networking

TL;DR

WNOS introduces a novel wireless network operating system that abstracts complex wireless protocols, enabling automated generation of distributed control programs and demonstrating significant utility gains in various interference scenarios.

Contribution

This paper presents the design principles of WNOS, a new SDN approach for wireless networks that automates distributed control program generation from high-level specifications.

Findings

Achieves up to 80.4% utility gain in high interference networks

Automatically generates distributed control algorithms from centralized control programs

Prototype implementation on software-defined radios validates effectiveness

Abstract

This article investigates the basic design principles for a new Wireless Network Operating System (WNOS), a radically different approach to software-defined networking (SDN) for infrastructure-less wireless networks. Departing from well-understood approaches inspired by OpenFlow, WNOS provides the network designer with an abstraction hiding (i) the lower-level details of the wireless protocol stack and (ii) the distributed nature of the network operations. Based on this abstract representation, the WNOS takes network control programs written on a centralized, high-level view of the network and automatically generates distributed cross-layer control programs based on distributed optimization theory that are executed by each individual node on an abstract representation of the radio hardware. We first discuss the main architectural principles of WNOS. Then, we discuss a new approach to automatically generate solution algorithms for each of the resulting subproblems in an automated fashion. Finally, we illustrate a prototype implementation of WNOS on software-defined radio devices and test its effectiveness by considering specific cross-layer control problems. Experimental results indicate that, based on the automatically generated distributed control programs, WNOS achieves 18%, 56% and 80.4% utility gain in networks with low, medium and high levels of interference; maybe more importantly, we illustrate how the global network behavior can be controlled by modifying a few lines of code on a centralized abstraction.