Graph aware caching policy for distributed graph stores

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dc.citation.epage15en_US
dc.citation.spage6en_US
dc.contributor.authorAksu, Hidayeten_US
dc.contributor.authorCanım, M.en_US
dc.contributor.authorChang, Y.-C.en_US
dc.contributor.authorKörpeoğlu, İbrahimen_US
dc.contributor.authorUlusoy, Özgüren_US
dc.coverage.spatialTempe, AZ, USA
dc.date.accessioned2016-02-08T12:24:11Z
dc.date.available2016-02-08T12:24:11Z
dc.date.issued2015-03en_US
dc.departmentDepartment of Computer Engineeringen_US
dc.descriptionConference name: IEEE International Conference on Cloud Engineering, 2015
dc.descriptionDate of Conference: 9-13 March 2015
dc.description.abstractGraph stores are becoming increasingly popular among NOSQL applications seeking flexibility and heterogeneity in managing linked data. Conceptually and in practice, applications ranging from social networks, knowledge representations to Internet of things benefit from graph data stores built on a combination of relational and non-relational technologies aimed at desired performance characteristics. The most common data access pattern in querying graph stores is to traverse from a node to its neighboring nodes. This paper studies the impact of such traversal pattern to common data caching policies in a partitioned data environment where a big graph is distributed across servers in a cluster. We propose and evaluate a new graph aware caching policy designed to keep and evict nodes, edges and their metadata optimized for query traversal pattern. The algorithm distinguishes the topology of the graph as well as the latency of access to the graph nodes and neighbors. We implemented graph aware caching on a distributed data store Apache HBase in the Hadoop family. Performance evaluations showed up to 15x speedup on the benchmark datasets preferring our new graph aware policy over non-aware policies. We also show how to improve the performance of existing caching algorithms for distributed graphs by exploiting the topology information. © 2015 IEEE.en_US
dc.identifier.doi10.1109/IC2E.2015.39en_US
dc.identifier.urihttp://hdl.handle.net/11693/28574
dc.language.isoEnglishen_US
dc.publisherIEEEen_US
dc.relation.isversionofhttp://dx.doi.org/10.1109/IC2E.2015.39en_US
dc.source.titleProceedings - EEE International Conference on Cloud Engineering, IC2E 2015en_US
dc.subjectApache HBaseen_US
dc.subjectBig data analyticsen_US
dc.subjectCacheen_US
dc.subjectDistributed computingen_US
dc.subjectGraph awareen_US
dc.subjectBenchmarkingen_US
dc.subjectBig dataen_US
dc.subjectData handlingen_US
dc.subjectDistributed computer systemsen_US
dc.subjectKnowledge representationen_US
dc.subjectSocial sciences computingen_US
dc.subjectTopologyen_US
dc.subjectData analyticsen_US
dc.subjectDistributed data storesen_US
dc.subjectPerformance characteristicsen_US
dc.subjectTopology informationen_US
dc.subjectTraversal patternsen_US
dc.subjectGraph theoryen_US
dc.titleGraph aware caching policy for distributed graph storesen_US
dc.typeConference Paperen_US

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