Impact of Link Unreliability and Asymmetry on the Quality of Connectivity in Large-scale Sensor Networks
Identifieur interne : 000090 ( Pmc/Curation ); précédent : 000089; suivant : 000091Impact of Link Unreliability and Asymmetry on the Quality of Connectivity in Large-scale Sensor Networks
Auteurs : Yanjun Li ; Ye-Qiong Song ; René Schott ; Zhi Wang ; Youxian SunSource :
- Sensors (Basel, Switzerland) [ 1424-8220 ] ; 2008.
Abstract
Connectivity is a fundamental issue in research on wireless sensor networks. However, unreliable and asymmetric links have a great impact on the global quality of connectivity (QoC). By assuming the deployment of nodes a homogeneous Poisson point process and eliminating the border effect, this paper derives an explicit expression of node non-isolation probability as the upper bound of one-connectivity, based on an analytical link model which incorporates important parameters such as path loss exponent, shadowing variance of channel, modulation, encoding method etc. The derivation has built a bridge over the local link property and the global network connectivity, which makes it clear to see how various parameter impact the QoC. Numerical results obtained further confirm the analysis and can be used as reference for practical design and simulation of wireless ad hoc and sensor networks. Besides, we find giant component size a good relaxed measure of connectivity in some applications that do not require full connectivity.
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DOI: 10.3390/s8106674
PubMed: NONE
PubMed Central: 3707473
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<record><TEI><teiHeader><fileDesc><titleStmt><title xml:lang="en">Impact of Link Unreliability and Asymmetry on the Quality of Connectivity in Large-scale Sensor Networks</title><author><name sortKey="Li, Yanjun" sort="Li, Yanjun" uniqKey="Li Y" first="Yanjun" last="Li">Yanjun Li</name><affiliation><nlm:aff id="af1-sensors-08-06674"> State Key Laboratory of Industrial Control Technology, Zhejiang University, China / 38, Zheda Road 310027, Hangzhou, Zhejiang Province, China; E-Mails:<email>yjli.iipc@gmail.com</email></nlm:aff></affiliation><affiliation><nlm:aff id="af2-sensors-08-06674"> LORIA-Nancy University, Villers-lès-Nancy, France / Campus Scientifique, B.P. 239 - 54506 Vandoeuvre-lès-Nancy, France; E-Mails:<email>song@loria.fr</email>,<email>schott@loria.fr</email></nlm:aff></affiliation></author><author><name sortKey="Song, Ye Qiong" sort="Song, Ye Qiong" uniqKey="Song Y" first="Ye-Qiong" last="Song">Ye-Qiong Song</name><affiliation><nlm:aff id="af2-sensors-08-06674"> LORIA-Nancy University, Villers-lès-Nancy, France / Campus Scientifique, B.P. 239 - 54506 Vandoeuvre-lès-Nancy, France; E-Mails:<email>song@loria.fr</email>,<email>schott@loria.fr</email></nlm:aff></affiliation></author><author><name sortKey="Schott, Rene" sort="Schott, Rene" uniqKey="Schott R" first="René" last="Schott">René Schott</name><affiliation><nlm:aff id="af2-sensors-08-06674"> LORIA-Nancy University, Villers-lès-Nancy, France / Campus Scientifique, B.P. 239 - 54506 Vandoeuvre-lès-Nancy, France; E-Mails:<email>song@loria.fr</email>,<email>schott@loria.fr</email></nlm:aff></affiliation></author><author><name sortKey="Wang, Zhi" sort="Wang, Zhi" uniqKey="Wang Z" first="Zhi" last="Wang">Zhi Wang</name><affiliation><nlm:aff id="af1-sensors-08-06674"> State Key Laboratory of Industrial Control Technology, Zhejiang University, China / 38, Zheda Road 310027, Hangzhou, Zhejiang Province, China; E-Mails:<email>yjli.iipc@gmail.com</email></nlm:aff></affiliation></author><author><name sortKey="Sun, Youxian" sort="Sun, Youxian" uniqKey="Sun Y" first="Youxian" last="Sun">Youxian Sun</name><affiliation><nlm:aff id="af1-sensors-08-06674"> State Key Laboratory of Industrial Control Technology, Zhejiang University, China / 38, Zheda Road 310027, Hangzhou, Zhejiang Province, China; E-Mails:<email>yjli.iipc@gmail.com</email></nlm:aff></affiliation></author></titleStmt><publicationStmt><idno type="wicri:source">PMC</idno><idno type="pmc">3707473</idno><idno type="url">http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3707473</idno><idno type="RBID">PMC:3707473</idno><idno type="doi">10.3390/s8106674</idno><idno type="pmid">NONE</idno><date when="2008">2008</date><idno type="wicri:Area/Pmc/Corpus">000090</idno><idno type="wicri:explorRef" wicri:stream="Pmc" wicri:step="Corpus" wicri:corpus="PMC">000090</idno><idno type="wicri:Area/Pmc/Curation">000090</idno><idno type="wicri:explorRef" wicri:stream="Pmc" wicri:step="Curation">000090</idno></publicationStmt><sourceDesc><biblStruct><analytic><title xml:lang="en" level="a" type="main">Impact of Link Unreliability and Asymmetry on the Quality of Connectivity in Large-scale Sensor Networks</title><author><name sortKey="Li, Yanjun" sort="Li, Yanjun" uniqKey="Li Y" first="Yanjun" last="Li">Yanjun Li</name><affiliation><nlm:aff id="af1-sensors-08-06674"> State Key Laboratory of Industrial Control Technology, Zhejiang University, China / 38, Zheda Road 310027, Hangzhou, Zhejiang Province, China; E-Mails:<email>yjli.iipc@gmail.com</email></nlm:aff></affiliation><affiliation><nlm:aff id="af2-sensors-08-06674"> LORIA-Nancy University, Villers-lès-Nancy, France / Campus Scientifique, B.P. 239 - 54506 Vandoeuvre-lès-Nancy, France; E-Mails:<email>song@loria.fr</email>,<email>schott@loria.fr</email></nlm:aff></affiliation></author><author><name sortKey="Song, Ye Qiong" sort="Song, Ye Qiong" uniqKey="Song Y" first="Ye-Qiong" last="Song">Ye-Qiong Song</name><affiliation><nlm:aff id="af2-sensors-08-06674"> LORIA-Nancy University, Villers-lès-Nancy, France / Campus Scientifique, B.P. 239 - 54506 Vandoeuvre-lès-Nancy, France; E-Mails:<email>song@loria.fr</email>,<email>schott@loria.fr</email></nlm:aff></affiliation></author><author><name sortKey="Schott, Rene" sort="Schott, Rene" uniqKey="Schott R" first="René" last="Schott">René Schott</name><affiliation><nlm:aff id="af2-sensors-08-06674"> LORIA-Nancy University, Villers-lès-Nancy, France / Campus Scientifique, B.P. 239 - 54506 Vandoeuvre-lès-Nancy, France; E-Mails:<email>song@loria.fr</email>,<email>schott@loria.fr</email></nlm:aff></affiliation></author><author><name sortKey="Wang, Zhi" sort="Wang, Zhi" uniqKey="Wang Z" first="Zhi" last="Wang">Zhi Wang</name><affiliation><nlm:aff id="af1-sensors-08-06674"> State Key Laboratory of Industrial Control Technology, Zhejiang University, China / 38, Zheda Road 310027, Hangzhou, Zhejiang Province, China; E-Mails:<email>yjli.iipc@gmail.com</email></nlm:aff></affiliation></author><author><name sortKey="Sun, Youxian" sort="Sun, Youxian" uniqKey="Sun Y" first="Youxian" last="Sun">Youxian Sun</name><affiliation><nlm:aff id="af1-sensors-08-06674"> State Key Laboratory of Industrial Control Technology, Zhejiang University, China / 38, Zheda Road 310027, Hangzhou, Zhejiang Province, China; E-Mails:<email>yjli.iipc@gmail.com</email></nlm:aff></affiliation></author></analytic><series><title level="j">Sensors (Basel, Switzerland)</title><idno type="eISSN">1424-8220</idno><imprint><date when="2008">2008</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en"><p>Connectivity is a fundamental issue in research on wireless sensor networks. However, unreliable and asymmetric links have a great impact on the global quality of connectivity (QoC). By assuming the deployment of nodes a homogeneous Poisson point process and eliminating the border effect, this paper derives an explicit expression of node non-isolation probability as the upper bound of one-connectivity, based on an analytical link model which incorporates important parameters such as path loss exponent, shadowing variance of channel, modulation, encoding method etc. The derivation has built a bridge over the local link property and the global network connectivity, which makes it clear to see how various parameter impact the QoC. Numerical results obtained further confirm the analysis and can be used as reference for practical design and simulation of wireless ad hoc and sensor networks. 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<front><journal-meta><journal-id journal-id-type="nlm-ta">Sensors (Basel)</journal-id><journal-id journal-id-type="iso-abbrev">Sensors (Basel)</journal-id><journal-title-group><journal-title>Sensors (Basel, Switzerland)</journal-title></journal-title-group><issn pub-type="epub">1424-8220</issn><publisher><publisher-name>Molecular Diversity Preservation International (MDPI)</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="pmc">3707473</article-id><article-id pub-id-type="doi">10.3390/s8106674</article-id><article-id pub-id-type="publisher-id">sensors-08-06674</article-id><article-categories><subj-group subj-group-type="heading"><subject>Article</subject></subj-group></article-categories><title-group><article-title>Impact of Link Unreliability and Asymmetry on the Quality of Connectivity in Large-scale Sensor Networks</article-title></title-group><contrib-group><contrib contrib-type="author"><name><surname>Li</surname><given-names>Yanjun</given-names></name><xref ref-type="aff" rid="af1-sensors-08-06674"><sup>1</sup></xref><xref ref-type="aff" rid="af2-sensors-08-06674"><sup>2</sup></xref></contrib><contrib contrib-type="author"><name><surname>Song</surname><given-names>Ye-Qiong</given-names></name><xref ref-type="aff" rid="af2-sensors-08-06674"><sup>2</sup></xref></contrib><contrib contrib-type="author"><name><surname>Schott</surname><given-names>René</given-names></name><xref ref-type="aff" rid="af2-sensors-08-06674"><sup>2</sup></xref></contrib><contrib contrib-type="author"><name><surname>Wang</surname><given-names>Zhi</given-names></name><xref ref-type="aff" rid="af1-sensors-08-06674"><sup>1</sup></xref><xref rid="c1-sensors-08-06674" ref-type="corresp"><sup>*</sup></xref></contrib><contrib contrib-type="author"><name><surname>Sun</surname><given-names>Youxian</given-names></name><xref ref-type="aff" rid="af1-sensors-08-06674"><sup>1</sup></xref></contrib></contrib-group><aff id="af1-sensors-08-06674"><label>1</label> State Key Laboratory of Industrial Control Technology, Zhejiang University, China / 38, Zheda Road 310027, Hangzhou, Zhejiang Province, China; E-Mails:<email>yjli.iipc@gmail.com</email></aff><aff id="af2-sensors-08-06674"><label>2</label> LORIA-Nancy University, Villers-lès-Nancy, France / Campus Scientifique, B.P. 239 - 54506 Vandoeuvre-lès-Nancy, France; E-Mails:<email>song@loria.fr</email>,<email>schott@loria.fr</email></aff><author-notes><corresp id="c1-sensors-08-06674"><label>*</label> Author to whom correspondence should be addressed; E-Mail: <email>wangzhi@iipc.zju.edu.cn</email>; Tel.: +86-571-85698532; Fax: +86-571-87951879</corresp></author-notes><pub-date pub-type="collection"><month>10</month><year>2008</year></pub-date><pub-date pub-type="epub"><day>24</day><month>10</month><year>2008</year></pub-date><volume>8</volume><issue>10</issue><fpage>6674</fpage><lpage>6691</lpage><history><date date-type="received"><day>01</day><month>7</month><year>2008</year></date><date date-type="rev-recd"><day>12</day><month>10</month><year>2008</year></date><date date-type="accepted"><day>22</day><month>10</month><year>2008</year></date></history><permissions><copyright-statement>© 2008 by the authors; licensee Molecular Diversity Preservation International, Basel, Switzerland.</copyright-statement><copyright-year>2008</copyright-year><license><license-p><pmc-comment>CREATIVE COMMONS</pmc-comment>This article is an open-access article distributed under the terms and conditions of the Creative Commons Attribution license (<ext-link ext-link-type="uri" xlink:href="http://creativecommons.org/licenses/by/3.0/">http://creativecommons.org/licenses/by/3.0/</ext-link>).</license-p></license></permissions><abstract><p>Connectivity is a fundamental issue in research on wireless sensor networks. However, unreliable and asymmetric links have a great impact on the global quality of connectivity (QoC). By assuming the deployment of nodes a homogeneous Poisson point process and eliminating the border effect, this paper derives an explicit expression of node non-isolation probability as the upper bound of one-connectivity, based on an analytical link model which incorporates important parameters such as path loss exponent, shadowing variance of channel, modulation, encoding method etc. The derivation has built a bridge over the local link property and the global network connectivity, which makes it clear to see how various parameter impact the QoC. Numerical results obtained further confirm the analysis and can be used as reference for practical design and simulation of wireless ad hoc and sensor networks. Besides, we find giant component size a good relaxed measure of connectivity in some applications that do not require full connectivity.</p></abstract><kwd-group><kwd><bold>S</bold>ensor networks</kwd><kwd>connectivity</kwd><kwd>link model</kwd><kwd>node isolation probability</kwd><kwd>giant component</kwd><kwd>critical node density</kwd></kwd-group></article-meta></front><floats-group><fig id="f1-sensors-08-06674" position="float"><label>Figure 1.</label><caption><p>Different kinds link models. <bold>(a)</bold> Boolean disk model. <bold>(b)</bold> Shadowing model. <bold>(c)</bold> Probabilistic model.</p></caption><graphic xlink:href="sensors-08-06674f1"></graphic></fig><fig id="f2-sensors-08-06674" position="float"><label>Figure 2.</label><caption><p>Analytical PRR to distance, obtained from <xref rid="FD19" ref-type="disp-formula">(19)</xref> and <xref rid="FD17" ref-type="disp-formula">(17)</xref>, <italic>P<sub>t</sub></italic>=-5 dB, <italic>η</italic>=3, <italic>σ</italic>=3.3, <italic>f</italic>=50 Byte, <italic>h</italic>=2 Byte.</p></caption><graphic xlink:href="sensors-08-06674f2"></graphic></fig><fig id="f3-sensors-08-06674" position="float"><label>Figure 3.</label><caption><p>Contour plot for different link models. (a) Boolean disk model<bold>. (b)</bold> Log-normal shadowing based probabilistic model.</p></caption><graphic xlink:href="sensors-08-06674f3"></graphic></fig><fig id="f4-sensors-08-06674" position="float"><label>Figure 4.</label><caption><p>The procedure of linear approximation for Ψ(<italic>γ</italic>) and <italic>f</italic>(<italic>γ</italic>|<italic>s</italic>).</p></caption><graphic xlink:href="sensors-08-06674f4"></graphic></fig><fig id="f5-sensors-08-06674" position="float"><label>Figure 5.</label><caption><p>Simulated results for different settings. <bold>(a)</bold> Benchmark. <bold>(b)</bold> Change path loss exponent <italic>η</italic>. <bold>(c)</bold> Changing shadowing variance <italic>σ</italic>. <bold>(d)</bold> Change encoding method <italic>E</italic>. <bold>(e)</bold> Change transmission power <italic>P<sub>t</sub></italic>. <bold>(f)</bold> Change frame size <italic>f</italic>. <bold>(g)</bold> Changing area size ‖<italic>A</italic>‖.</p></caption><graphic xlink:href="sensors-08-06674f5a"></graphic><graphic xlink:href="sensors-08-06674f5b"></graphic></fig><table-wrap id="t1-sensors-08-06674" position="float"><label>Table 1.</label><caption><p>Critical density for giant component, one-connectivity and non-isolation under different settings, comparison of analytical and simulation results.</p></caption><table frame="hsides" rules="groups"><thead><tr><th align="center" valign="middle" rowspan="1" colspan="1"><bold>Settings</bold></th><th align="center" valign="middle" rowspan="1" colspan="1"><bold><italic>ρ</italic>(<italic>P</italic>(<italic>G</italic>)=90±.05%) (m<sup>-2</sup>) simulation</bold></th><th align="center" valign="middle" rowspan="1" colspan="1"><bold><italic>ρ</italic>(<italic>P</italic>(<italic>C</italic>)=90±.05%) (m<sup>-2</sup>) simulation</bold></th><th align="center" valign="middle" rowspan="1" colspan="1"><bold><italic>ρ</italic>(<italic>P</italic>(<italic>Ī</italic>)=90±.05%) (m<sup>-2</sup>) simulation</bold></th><th align="center" valign="middle" rowspan="1" colspan="1"><bold><italic>ρ</italic>(<italic>P</italic>(<italic>Ī</italic>)=90±.05%) (m<sup>-2</sup>) analysis</bold></th></tr></thead><tbody><tr><td align="center" valign="top" rowspan="1" colspan="1">(a)</td><td align="center" valign="top" rowspan="1" colspan="1">7.00 · 10<sup>-3</sup></td><td align="center" valign="top" rowspan="1" colspan="1">1.25 · 10<sup>-2</sup></td><td align="center" valign="top" rowspan="1" colspan="1">1.22 · 10<sup>-3</sup></td><td align="center" valign="top" rowspan="1" colspan="1">1.25 · 10<sup>-3</sup></td></tr><tr><td align="center" valign="top" rowspan="1" colspan="1">(b)</td><td align="center" valign="top" rowspan="1" colspan="1">1.15 · 10<sup>-3</sup></td><td align="center" valign="top" rowspan="1" colspan="1">2.27 · 10<sup>-2</sup></td><td align="center" valign="top" rowspan="1" colspan="1">2.21 · 10<sup>-3</sup></td><td align="center" valign="top" rowspan="1" colspan="1">2.15 · 10<sup>-3</sup></td></tr><tr><td align="center" valign="top" rowspan="1" colspan="1">(c)</td><td align="center" valign="top" rowspan="1" colspan="1">4.50 · 10<sup>-3</sup></td><td align="center" valign="top" rowspan="1" colspan="1">1.07 · 10<sup>-2</sup></td><td align="center" valign="top" rowspan="1" colspan="1">1.07 · 10<sup>-3</sup></td><td align="center" valign="top" rowspan="1" colspan="1">6.00 · 10<sup>-3</sup></td></tr><tr><td align="center" valign="top" rowspan="1" colspan="1">(d)</td><td align="center" valign="top" rowspan="1" colspan="1">4.80 · 10<sup>-3</sup></td><td align="center" valign="top" rowspan="1" colspan="1">8.75 · 10<sup>-3</sup></td><td align="center" valign="top" rowspan="1" colspan="1">8.50 · 10<sup>-3</sup></td><td align="center" valign="top" rowspan="1" colspan="1">8.00 · 10<sup>-3</sup></td></tr><tr><td align="center" valign="top" rowspan="1" colspan="1">(e)</td><td align="center" valign="top" rowspan="1" colspan="1">5.00 · 10<sup>-3</sup></td><td align="center" valign="top" rowspan="1" colspan="1">9.00 · 10<sup>-3</sup></td><td align="center" valign="top" rowspan="1" colspan="1">8.70 · 10<sup>-3</sup></td><td align="center" valign="top" rowspan="1" colspan="1">8.70 · 10<sup>-3</sup></td></tr><tr><td align="center" valign="top" rowspan="1" colspan="1">(f)</td><td align="center" valign="top" rowspan="1" colspan="1">7.50 · 10<sup>-3</sup></td><td align="center" valign="top" rowspan="1" colspan="1">1.33 · 10<sup>-2</sup></td><td align="center" valign="top" rowspan="1" colspan="1">1.30 · 10<sup>-3</sup></td><td align="center" valign="top" rowspan="1" colspan="1">1.32 · 10<sup>-3</sup></td></tr><tr><td align="center" valign="top" rowspan="1" colspan="1">(g)</td><td align="center" valign="top" rowspan="1" colspan="1">7.00 · 10<sup>-3</sup></td><td align="center" valign="top" rowspan="1" colspan="1">1.40 · 10<sup>-2</sup></td><td align="center" valign="top" rowspan="1" colspan="1">1.35 · 10<sup>-3</sup></td><td align="center" 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