Investigating Coverage and Connectivity Trade-offs in Wireless Sensor Networks: The Benefits of MOEAs

Matthias Woehrle, Dimo Brockhoff, Tim Hohm () and Stefan Bleuler
Additional contact information
Tim Hohm: ETH Zurich

A chapter in Multiple Criteria Decision Making for Sustainable Energy and Transportation Systems, 2010, pp 211-221 from Springer

Abstract: Abstract How many wireless sensor nodes should be used and where should they be placed in order to form an optimal wireless sensor network (WSN) deployment? This is a difficult question to answer for a decision maker due to the conflicting objectives of deployment costs and wireless transmission reliability. Here, we address this problem using a multiobjective evolutionary algorithm (MOEA) which allows to identify the trade-offs between low-cost and highly reliable deployments–providing the decision maker with a set of good solutions to choose from. For the MOEA, we use an off-the-shelf selector and propose a problem-specific representation, an initialization scheme, and variation operators. The resulting algorithm is applied to a test deployment scenario to show the usefulness of the approach in terms of decision making.

Keywords: Evolutionary multiobjective optimization; Variable-length representation; Wireless sensor networks (search for similar items in EconPapers)
Date: 2010
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:lnechp:978-3-642-04045-0_18

Ordering information: This item can be ordered from
http://www.springer.com/9783642040450

DOI: 10.1007/978-3-642-04045-0_18

Access Statistics for this chapter

More chapters in Lecture Notes in Economics and Mathematical Systems from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().