Impact of Network Density on Data Aggregation in Wireless Sensor Networks

Impact of Network Density on Data Aggregation in Wireless Sensor Networks. Intanagonwiwat, C., Estrin, D., Govindan, R., & Heidemann, J. Technical Report 01-750, University of Southern California Computer Science Department, November, 2001.

Paper abstract bibtex

In-network data aggregation is essential for wireless sensor networks where resources (e.g., bandwidth, energy) are limited. In a previously proposed data dissemination scheme, data is opportunistically aggregated at the intermediate nodes on a low-latency tree which may not necessarily be energy efficient. A more energy-efficient tree is a greedy tree which can be incrementally constructed by connecting each source to the closest point of the existing tree. In this paper, we propose a greedy approach for constructing a greedy aggregation tree to improve path sharing. We evaluated the performance of this greedy approach by comparing it to the prior opportunistic approach. Our preliminary result suggests that although the greedy aggregation and the opportunistic aggregation are roughly equivalent at low-density networks, the greedy aggregation can achieve signficant energy savings at higher densities. In one experiment we found that the greedy aggregation can achieve up to 45% energy savings over the opportunistic aggregation without an adverse impact on latency or robustness.

@TechReport{Intanagonwiwat01b,
	author = 	"Chalermek Intanagonwiwat and Deborah Estrin
		 and Ramesh Govindan and John Heidemann",
	title = "Impact of Network Density on Data Aggregation in Wireless Sensor Networks",
	institution = 	"University of Southern California Computer Science Department",
	year = 		2001,
	sortdate = "2001-11-01",
	project = "ilense, scadds",
	jsubject = "sensornet_data_dissemination",
	number =	"01-750",
	month =		nov,
	location =	"johnh: folder: xxx",
	location =	"johnh: pafile",
	keywords =	"diffusion, greedy vs. opportunistic aggregation",
	otherurl =	"ftp://ftp.usc.edu/pub/csinfo/tech-reports/papers/01-750.pdf",
	url =		"http://www.isi.edu/%7ejohnh/PAPERS/Intanagonwiwat01b.html",
	pdfurl =		"http://www.isi.edu/%7ejohnh/PAPERS/Intanagonwiwat01b.pdf",
	abstract = "
In-network data aggregation is essential for wireless sensor networks
where resources (e.g., bandwidth, energy) are limited. In a previously
proposed data dissemination scheme, data is opportunistically
aggregated at the intermediate nodes on a low-latency tree which may
not necessarily be energy efficient. A more energy-efficient tree is a
greedy tree which can be incrementally constructed by connecting each
source to the closest point of the existing tree. In this paper, we
propose a greedy approach for constructing a greedy aggregation tree
to improve path sharing. We evaluated the performance of this greedy
approach by comparing it to the prior opportunistic approach. Our
preliminary result suggests that although the greedy aggregation and
the opportunistic aggregation are roughly equivalent at low-density
networks, the greedy aggregation can achieve signficant energy savings
at higher densities. In one experiment we found that the greedy
aggregation can achieve up to 45\% energy savings over the
opportunistic aggregation without an adverse impact on latency or
robustness.
",
}

Downloads: 0

{"_id":"MMzFB6iTJ6HL4HMDG","bibbaseid":"intanagonwiwat-estrin-govindan-heidemann-impactofnetworkdensityondataaggregationinwirelesssensornetworks-2001","author_short":["Intanagonwiwat, C.","Estrin, D.","Govindan, R.","Heidemann, J."],"bibdata":{"bibtype":"techreport","type":"techreport","author":[{"firstnames":["Chalermek"],"propositions":[],"lastnames":["Intanagonwiwat"],"suffixes":[]},{"firstnames":["Deborah"],"propositions":[],"lastnames":["Estrin"],"suffixes":[]},{"firstnames":["Ramesh"],"propositions":[],"lastnames":["Govindan"],"suffixes":[]},{"firstnames":["John"],"propositions":[],"lastnames":["Heidemann"],"suffixes":[]}],"title":"Impact of Network Density on Data Aggregation in Wireless Sensor Networks","institution":"University of Southern California Computer Science Department","year":"2001","sortdate":"2001-11-01","project":"ilense, scadds","jsubject":"sensornet_data_dissemination","number":"01-750","month":"November","location":"johnh: pafile","keywords":"diffusion, greedy vs. opportunistic aggregation","otherurl":"ftp://ftp.usc.edu/pub/csinfo/tech-reports/papers/01-750.pdf","url":"http://www.isi.edu/%7ejohnh/PAPERS/Intanagonwiwat01b.html","pdfurl":"http://www.isi.edu/%7ejohnh/PAPERS/Intanagonwiwat01b.pdf","abstract":"In-network data aggregation is essential for wireless sensor networks where resources (e.g., bandwidth, energy) are limited. In a previously proposed data dissemination scheme, data is opportunistically aggregated at the intermediate nodes on a low-latency tree which may not necessarily be energy efficient. A more energy-efficient tree is a greedy tree which can be incrementally constructed by connecting each source to the closest point of the existing tree. In this paper, we propose a greedy approach for constructing a greedy aggregation tree to improve path sharing. We evaluated the performance of this greedy approach by comparing it to the prior opportunistic approach. Our preliminary result suggests that although the greedy aggregation and the opportunistic aggregation are roughly equivalent at low-density networks, the greedy aggregation can achieve signficant energy savings at higher densities. In one experiment we found that the greedy aggregation can achieve up to 45% energy savings over the opportunistic aggregation without an adverse impact on latency or robustness. ","bibtex":"@TechReport{Intanagonwiwat01b,\n\tauthor = \t\"Chalermek Intanagonwiwat and Deborah Estrin\n\t\t and Ramesh Govindan and John Heidemann\",\n\ttitle = \"Impact of Network Density on Data Aggregation in Wireless Sensor Networks\",\n\tinstitution = \t\"University of Southern California Computer Science Department\",\n\tyear = \t\t2001,\n\tsortdate = \"2001-11-01\",\n\tproject = \"ilense, scadds\",\n\tjsubject = \"sensornet_data_dissemination\",\n\tnumber =\t\"01-750\",\n\tmonth =\t\tnov,\n\tlocation =\t\"johnh: folder: xxx\",\n\tlocation =\t\"johnh: pafile\",\n\tkeywords =\t\"diffusion, greedy vs. opportunistic aggregation\",\n\totherurl =\t\"ftp://ftp.usc.edu/pub/csinfo/tech-reports/papers/01-750.pdf\",\n\turl =\t\t\"http://www.isi.edu/%7ejohnh/PAPERS/Intanagonwiwat01b.html\",\n\tpdfurl =\t\t\"http://www.isi.edu/%7ejohnh/PAPERS/Intanagonwiwat01b.pdf\",\n\tabstract = \"\nIn-network data aggregation is essential for wireless sensor networks\nwhere resources (e.g., bandwidth, energy) are limited. In a previously\nproposed data dissemination scheme, data is opportunistically\naggregated at the intermediate nodes on a low-latency tree which may\nnot necessarily be energy efficient. A more energy-efficient tree is a\ngreedy tree which can be incrementally constructed by connecting each\nsource to the closest point of the existing tree. In this paper, we\npropose a greedy approach for constructing a greedy aggregation tree\nto improve path sharing. We evaluated the performance of this greedy\napproach by comparing it to the prior opportunistic approach. Our\npreliminary result suggests that although the greedy aggregation and\nthe opportunistic aggregation are roughly equivalent at low-density\nnetworks, the greedy aggregation can achieve signficant energy savings\nat higher densities. In one experiment we found that the greedy\naggregation can achieve up to 45\\% energy savings over the\nopportunistic aggregation without an adverse impact on latency or\nrobustness.\n\",\n}\n\n","author_short":["Intanagonwiwat, C.","Estrin, D.","Govindan, R.","Heidemann, J."],"bibbaseid":"intanagonwiwat-estrin-govindan-heidemann-impactofnetworkdensityondataaggregationinwirelesssensornetworks-2001","role":"author","urls":{"Paper":"http://www.isi.edu/%7ejohnh/PAPERS/Intanagonwiwat01b.html"},"keyword":["diffusion","greedy vs. opportunistic aggregation"],"metadata":{"authorlinks":{}}},"bibtype":"techreport","biburl":"https://bibbase.org/f/dHevizJoWEhWowz8q/johnh-2023-2.bib","dataSources":["YLyu3mj3xsBeoqiHK","fLZcDgNSoSuatv6aX","fxEParwu2ZfurScPY","7nuQvtHTqKrLmgu99"],"keywords":["diffusion","greedy vs. opportunistic aggregation"],"search_terms":["impact","network","density","data","aggregation","wireless","sensor","networks","intanagonwiwat","estrin","govindan","heidemann"],"title":"Impact of Network Density on Data Aggregation in Wireless Sensor Networks","year":2001}