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Building Efficient Wireless Sensor Networks with Low-Level Naming

John Heidemann, Fabio Silva, Chalermek Intanagonwiwat, Ramesh Govindan, Deborah Estrin, and Deepak Ganesan
USC/Information Sciences Institute

Abstract

In most distributed systems, naming of nodes for low-level communication leverages topological location (such as node addresses) and is independent of any application. In this paper, we investigate an emerging class of distributed systems where low-level communication does not rely on network topological location. Rather, low-level communication is based on attributes that are external to the network topology and relevant to the application. When combined with dense deployment of nodes, this kind of named data enables in-network processing for data aggregation, collaborative signal processing, and similar problems. These approaches are essential for emerging applications such as sensor networks where resources such as bandwidth and energy are limited. This paper is the first description of the software architecture that supports named data and in-network processing in an operational, multi-application sensor-network. We show that approaches such as in-network aggregation and nested queries can significantly affect network traffic. In one experiment aggregation reduces traffic by up to 42% and nested queries reduce loss rates by 30%. Although aggregation has been previously studied in simulation, this paper demonstrates nested queries as another form of in-network processing, presents the first evaluation of these approaches over an operational testbed.

Availability

This paper is available in several formats: abstract web page with pointers and cites, gzip'ed postscript, PDF, paper copies can be obtained by mail to the authors. Copyright terms for this paper appear below.

Reference

Heidemann01c: John Heidemann, Fabio Silva, Chalermek Intanagonwiwat, Ramesh Govindan, Deborah Estrin, and Deepak Ganesan. Building Efficient Wireless Sensor Networks with Low-Level Naming. In Proceedings of the Symposium on Operating Systems Principles, pp. 146-159. Chateau Lake Louise, Banff, Alberta, Canada, ACM. October, 2001. <http://www.isi.edu/~johnh/PAPERS/Heidemann01c.html>.

@inproceedings{Heidemann01c,
	author = "John Heidemann and Fabio Silva and Chalermek Intanagonwiwat and Ramesh Govindan and Deborah Estrin and Deepak Ganesan",
	title = "Building Efficient Wireless Sensor Networks with Low-Level Naming",
	booktitle = "Proceedings of the  Symposium on Operating Systems Principles",
	year = "2001",
	publisher = "{ACM}",
	address = "Chateau Lake Louise, Banff, Alberta, Canada",
	month = "October",
	pages = "146--159",
	keywords = "sensor networks, apis, in-network processing,
                         possible 551 or 555 paper",
	url = "http://www.isi.edu/~johnh/PAPERS/Heidemann01c.html",
	pdfurl = "http://www.isi.edu/~johnh/PAPERS/Heidemann01c.pdf",
	psurl = "http://www.isi.edu/~johnh/PAPERS/Heidemann01c.ps.gz",
	otherurl = "http://www-cse.ucsd.edu/sosp01/papers/heidemann.pdf",
}

Copyright

This paper is copyright © 2001 by its authors. Permission to make digital or hard copies of part or all of this work for personal use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that new copies bear this notice and the full citation on the first page. Abstracting with credit is permitted.

To copy otherwise, to republish, to post on servers or to redistribute to lists, requires prior specific permission of the authors.