Detecting graphs with induced cycles in limited-bandwidth communication networks

dc.contributor.authorZapp, Timothy
dc.contributor.examiningcommitteeLi, Ben (Computer Science)
dc.contributor.examiningcommitteeKamali, Shahin (York University)
dc.contributor.supervisorMiller, Avery
dc.date.accessioned2023-09-06T16:50:04Z
dc.date.available2023-09-06T16:50:04Z
dc.date.issued2023-08-23
dc.date.submitted2023-08-23T23:20:35Zen_US
dc.degree.disciplineComputer Scienceen_US
dc.degree.levelMaster of Science (M.Sc.)
dc.description.abstractThe subgraph detection problem is a fundamental problem in distributed algorithms that asks the nodes of a communication network G to determine if that communication network contains a specific graph P as a subgraph. Recent work in this area has largely been focused on the case where the nodes have limited bandwidth and thus cannot communicate arbitrarily, which is part of a larger movement in distributed algorithms to reduce the amount of communication that our algorithms require. We show that, if P is a graph containing an induced cycle of length at least 4, then detecting a rainbow copy of P (in terms of vertex colourings or edge colourings) takes at least Ω(n/ log n) in the CONGEST model. Motivated by this result, we go on to show that, if P is a necklace graph containing an odd cycle of length at least 5, then detecting a copy of P takes at least Ω(n/ log n) rounds in the CONGEST model. Finally, we discuss techniques for proving similar results when P is a necklace graph containing all even cycles or a 3-cycle, and highlight the difficulties in doing so.
dc.description.noteOctober 2023
dc.identifier.urihttp://hdl.handle.net/1993/37579
dc.language.isoeng
dc.rightsopen accessen_US
dc.subjectCONGEST
dc.subjectSubgraph detection
dc.subjectDistributed computing
dc.subjectInduced subgraphs
dc.subjectLimited-bandwidth communication networks
dc.subjectLower bounds
dc.titleDetecting graphs with induced cycles in limited-bandwidth communication networks
dc.typemaster thesisen_US
local.subject.manitobano
oaire.awardTitleUniversity of Manitoba Graduate Fellowship
project.funder.identifierhttp://doi.org/10.13039/100010318
project.funder.nameUniversity of Manitoba
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