NeTs-NOSS: A Middleware Framework for Rapid Composition and Deployment of Compute-Intensive Networked Embedded Systems

University Of Southern California, Los Angeles CA

Investigators

Abstract

Proposal Number: 0627028 Investigators: Viktor Prasanna (PI), Bhaskar Krishnamachari (Co-PI) Institution: University of Southern California Title: NeTS-NOSS: A Middleware Framework for Rapid Composition and Deployment of Compute-Intensive Networked Embedded Systems Abstract Wireless sensor networks (WSN) have the potential to revolutionize data collection and analysis in physical sciences and other fields by allowing intelligent dense monitoring of the environment. The primary focus of WSN research till now has been the design and implementation of the basic sensor node hardware and low-level protocols such as those for localization, time synchronization, medium access, routing, etc. However, the composition and deployment of a complex networked sensing application is still a daunting task for the non-expert end user. This project involves the design and evaluation of reusable middleware functions that provide easy-to-program abstractions of the underlying hardware and network services, allowing rapid composition and deployment of sensor network applications. The topics addressed by our research include the development and evaluation of suitable topological abstractions, task mapping and migration techniques, communication and computational primitives, and realistic performance models to evaluate designs. We expect the middleware techniques developed in this project to significantly enhance the state of the art in the design of sensor networks for complex applications. The abstractions and tools we develop will help establish a paradigm shift from the current dependence on application-specific customized solutions to a generalized automated approach that facilitates rapid design and ease of deployment for a wide range of applications. The outcomes of the research will be disseminated in a timely basis through publications, presentations, and collaborations to the academic research community as well as to industry. The project will also have a significant educational impact, by supporting graduate student research, and providing material for a course on wireless sensor networks taught at USC.