WNOS: An Optimization-based Wireless Network Operating System

TL;DR

WNOS introduces an abstraction-based wireless network operating system that automates the generation of distributed control programs from high-level network control specifications, improving network utility and manageability.

Contribution

This paper presents a novel SDN approach for wireless networks that automates control program generation using distributed optimization, unlike traditional protocol-specific methods.

Findings

Achieves up to 80.4% utility gain in high interference scenarios

Automatically generates distributed control programs from high-level specifications

Demonstrates effective control of global network behavior with minimal code changes

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 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.