ParallelSubgraphListinginaLarge-ScaleGraph
Subgraphlistingisafundamentaloperationtomanygraphandnetworkanalyses.Theproblemitselfiscomputationallyex pensiveandiswell-studiedincentralizedprocessingalgorithms.However,thecentralizedsolutionscannotscalewelltolarg egraphs.Recently, severalparallelapproachesareintroducedtohandlethelarge graphs.Unfortunately, theseparallelappr oachesstillrelyontheexpensivejoinoperations,thuscannotachievehighperformance.Inthispaper, wedesign anovelparallelsubgraphlisting framework,namedPSgL.ThePSgLiterativelyenumeratessu bgraphinstancesandsolvesthesubgraphlistinginadivide-and-conquerfashion.Theframeworkcompletelyreliesonthegr aphtraversal,andavoidstheexplicitjoinoperation.Moreover,inordertoimproveitsperformance,weproposeseveralsoluti onstobalancetheworkloadandreducethesizeofintermediateresults.Specially,weprovetheproblemofpartialsubgraphins tancedistributionforworkloadbalanceisNP-hard,andcarefullydesignasetofheuristicstrategies.Tofurthermeducetheenor mousintermediateresults,weintroducethreeindependentmechanisms,whichareautomorphismbreakingofthepatterngr aph,initialpatternvertexselectionbasedonacostmodel,andapruningmethodbasedonalight-weightindex.WehaveimplementedtheprototypeofPSgL,andruncomprehensive experimentsof various graphlisting operations on diverselargegraphs.TheexperimentsclearlydemonstratethatPSgLisrobustandcanachieveperformancegainovert hestate-of-the-artsolutionsupto90%.
Graph GraphAlgorithm SubgraphListing GraphEnumeration
YingxiaSHAO BinCUI LeiCHEN LinMA JunjieYAO NingXU
国际会议
昆明
英文
275-292
2014-05-01(万方平台首次上网日期,不代表论文的发表时间)