Design patterns in beeping algorithms: Examples, emulation, and analysis
We consider networks of entities which interact using beeps. In the basic model by Cornejo and Kuhn (2010), entities either beep or listen in each round. Those who beep cannot detect simultaneous beeps. Those who listen distinguish only between silence and non-silence. We call this model BL (beep or...
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| Veröffentlicht in: | Information and computation 2019-02, Vol.264 (264), p.32-51 |
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| creator | Casteigts, A. Métivier, Y. Robson, J.M. Zemmari, A. |
| description | We consider networks of entities which interact using beeps. In the basic model by Cornejo and Kuhn (2010), entities either beep or listen in each round. Those who beep cannot detect simultaneous beeps. Those who listen distinguish only between silence and non-silence. We call this model BL (beep or listen). Stronger models enable collision detection when beeping (BcdL), listening (BLcd), or both (BcdLcd).
We identify a set of generic design patterns in beeping algorithms: multi-slot phases; exclusive beeps; adaptive probability; internal or peripheral collision detection (and their emulation). Using them, we formulate concisely a number of algorithms for basic tasks like colouring, degree computation, and MIS. We analyse their complexities, improving known bounds of the MIS algorithm by Jeavons et al. (2016). Finally, inspired by Afek et al. (2013), we show that all Las Vegas algorithms using collision detection are convertible into Monte Carlo algorithms with emulated detection, with a logarithmic slowdown. |
| doi_str_mv | 10.1016/j.ic.2018.10.001 |
| format | Article |
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We identify a set of generic design patterns in beeping algorithms: multi-slot phases; exclusive beeps; adaptive probability; internal or peripheral collision detection (and their emulation). Using them, we formulate concisely a number of algorithms for basic tasks like colouring, degree computation, and MIS. We analyse their complexities, improving known bounds of the MIS algorithm by Jeavons et al. (2016). Finally, inspired by Afek et al. (2013), we show that all Las Vegas algorithms using collision detection are convertible into Monte Carlo algorithms with emulated detection, with a logarithmic slowdown.</description><identifier>ISSN: 0890-5401</identifier><identifier>EISSN: 1090-2651</identifier><identifier>DOI: 10.1016/j.ic.2018.10.001</identifier><language>eng</language><publisher>Elsevier Inc</publisher><subject>2-hop colouring ; Beeping models ; Collision detection ; Colouring ; Computer Science ; Degree computation ; Design patterns ; Distributed, Parallel, and Cluster Computing ; Emulation ; Mathematics ; Networking and Internet Architecture ; Probability</subject><ispartof>Information and computation, 2019-02, Vol.264 (264), p.32-51</ispartof><rights>2018 Elsevier Inc.</rights><rights>Distributed under a Creative Commons Attribution 4.0 International License</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c370t-5f0f49192961b1f552fb3f63305b897dab12bed542e22ea80233e99f4bfe87993</citedby><cites>FETCH-LOGICAL-c370t-5f0f49192961b1f552fb3f63305b897dab12bed542e22ea80233e99f4bfe87993</cites><orcidid>0000-0002-7819-7013</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://dx.doi.org/10.1016/j.ic.2018.10.001$$EHTML$$P50$$Gelsevier$$H</linktohtml><link.rule.ids>230,314,780,784,885,3550,27924,27925,45995</link.rule.ids><backlink>$$Uhttps://hal.science/hal-01883360$$DView record in HAL$$Hfree_for_read</backlink></links><search><creatorcontrib>Casteigts, A.</creatorcontrib><creatorcontrib>Métivier, Y.</creatorcontrib><creatorcontrib>Robson, J.M.</creatorcontrib><creatorcontrib>Zemmari, A.</creatorcontrib><title>Design patterns in beeping algorithms: Examples, emulation, and analysis</title><title>Information and computation</title><description>We consider networks of entities which interact using beeps. In the basic model by Cornejo and Kuhn (2010), entities either beep or listen in each round. Those who beep cannot detect simultaneous beeps. Those who listen distinguish only between silence and non-silence. We call this model BL (beep or listen). Stronger models enable collision detection when beeping (BcdL), listening (BLcd), or both (BcdLcd).
We identify a set of generic design patterns in beeping algorithms: multi-slot phases; exclusive beeps; adaptive probability; internal or peripheral collision detection (and their emulation). Using them, we formulate concisely a number of algorithms for basic tasks like colouring, degree computation, and MIS. We analyse their complexities, improving known bounds of the MIS algorithm by Jeavons et al. (2016). Finally, inspired by Afek et al. (2013), we show that all Las Vegas algorithms using collision detection are convertible into Monte Carlo algorithms with emulated detection, with a logarithmic slowdown.</description><subject>2-hop colouring</subject><subject>Beeping models</subject><subject>Collision detection</subject><subject>Colouring</subject><subject>Computer Science</subject><subject>Degree computation</subject><subject>Design patterns</subject><subject>Distributed, Parallel, and Cluster Computing</subject><subject>Emulation</subject><subject>Mathematics</subject><subject>Networking and Internet Architecture</subject><subject>Probability</subject><issn>0890-5401</issn><issn>1090-2651</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2019</creationdate><recordtype>article</recordtype><recordid>eNp1kM1LAzEQxYMoWKt3j3sVuusk2Ww3vZVarVDwoueQ3Z20KftFshb73zdLxZuHYWYe7w3Mj5BHCgkFmj0fElsmDGge1gSAXpEJBQkxywS9JhPIwyxSoLfkzvtDMFCRZhOyeUFvd23U62FA1_rItlGB2Nt2F-l61zk77Bu_iNY_uulr9LMIm-9aD7ZrZ5Fuq1C6Pnnr78mN0bXHh98-JV-v68_VJt5-vL2vltu45HMYYmHApJJKJjNaUCMEMwU3GecgilzOK11QVmAlUoaMoc6BcY5SmrQwmM-l5FPydLm717XqnW20O6lOW7VZbtWoBQQ55xkcafDCxVu6znuH5i9AQY3U1EHZUo3URiVACZHFJYLhh6NFp3xpsS2xsg7LQVWd_T98BnLdcuA</recordid><startdate>20190201</startdate><enddate>20190201</enddate><creator>Casteigts, A.</creator><creator>Métivier, Y.</creator><creator>Robson, J.M.</creator><creator>Zemmari, A.</creator><general>Elsevier Inc</general><general>Elsevier</general><scope>AAYXX</scope><scope>CITATION</scope><scope>1XC</scope><scope>VOOES</scope><orcidid>https://orcid.org/0000-0002-7819-7013</orcidid></search><sort><creationdate>20190201</creationdate><title>Design patterns in beeping algorithms: Examples, emulation, and analysis</title><author>Casteigts, A. ; Métivier, Y. ; Robson, J.M. ; Zemmari, A.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c370t-5f0f49192961b1f552fb3f63305b897dab12bed542e22ea80233e99f4bfe87993</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2019</creationdate><topic>2-hop colouring</topic><topic>Beeping models</topic><topic>Collision detection</topic><topic>Colouring</topic><topic>Computer Science</topic><topic>Degree computation</topic><topic>Design patterns</topic><topic>Distributed, Parallel, and Cluster Computing</topic><topic>Emulation</topic><topic>Mathematics</topic><topic>Networking and Internet Architecture</topic><topic>Probability</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Casteigts, A.</creatorcontrib><creatorcontrib>Métivier, Y.</creatorcontrib><creatorcontrib>Robson, J.M.</creatorcontrib><creatorcontrib>Zemmari, A.</creatorcontrib><collection>CrossRef</collection><collection>Hyper Article en Ligne (HAL)</collection><collection>Hyper Article en Ligne (HAL) (Open Access)</collection><jtitle>Information and computation</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Casteigts, A.</au><au>Métivier, Y.</au><au>Robson, J.M.</au><au>Zemmari, A.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Design patterns in beeping algorithms: Examples, emulation, and analysis</atitle><jtitle>Information and computation</jtitle><date>2019-02-01</date><risdate>2019</risdate><volume>264</volume><issue>264</issue><spage>32</spage><epage>51</epage><pages>32-51</pages><issn>0890-5401</issn><eissn>1090-2651</eissn><abstract>We consider networks of entities which interact using beeps. In the basic model by Cornejo and Kuhn (2010), entities either beep or listen in each round. Those who beep cannot detect simultaneous beeps. Those who listen distinguish only between silence and non-silence. We call this model BL (beep or listen). Stronger models enable collision detection when beeping (BcdL), listening (BLcd), or both (BcdLcd).
We identify a set of generic design patterns in beeping algorithms: multi-slot phases; exclusive beeps; adaptive probability; internal or peripheral collision detection (and their emulation). Using them, we formulate concisely a number of algorithms for basic tasks like colouring, degree computation, and MIS. We analyse their complexities, improving known bounds of the MIS algorithm by Jeavons et al. (2016). Finally, inspired by Afek et al. (2013), we show that all Las Vegas algorithms using collision detection are convertible into Monte Carlo algorithms with emulated detection, with a logarithmic slowdown.</abstract><pub>Elsevier Inc</pub><doi>10.1016/j.ic.2018.10.001</doi><tpages>20</tpages><orcidid>https://orcid.org/0000-0002-7819-7013</orcidid><oa>free_for_read</oa></addata></record> |
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| source | Access via ScienceDirect (Elsevier); EZB-FREE-00999 freely available EZB journals |
| subjects | 2-hop colouring Beeping models Collision detection Colouring Computer Science Degree computation Design patterns Distributed, Parallel, and Cluster Computing Emulation Mathematics Networking and Internet Architecture Probability |
| title | Design patterns in beeping algorithms: Examples, emulation, and analysis |
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