Enhanced query processing using weighted predicate tree in edge computing environment

Edge computing is a novel computing paradigm in which the edge nodes of Internet of Things (IoT) are heavily involved in data processing. Resource Description Framework (RDF) plays an important role in Semantic Web due to the explosive growth of data of IoT. RDF is a graph-based data model employed for representing the Uniform Resource Identifiers (URIs), and SPARQL is the standard query language used for processing the query of RDF data. Growth of data throws a big challenge to the data storing and processing. In this paper a new data storing and query processing approach is proposed using weighted predicate tree. The predicate tree is used for effective storing of data and extracting the weights indicating the relation of the data. Computer simulation with SP2 Bench data set and SPARQL query reveals that the proposed approach allows substantially higher performance than three existing representative query processing schemes.

[1]  Claudio Gutiérrez,et al.  The Multiset Semantics of SPARQL Patterns , 2016, SEMWEB.

[2]  Stefan Decker,et al.  TopFed: TCGA tailored federated query processing and linking to LOD , 2014, Journal of Biomedical Semantics.

[3]  Daniel J. Abadi,et al.  Scalable SPARQL querying of large RDF graphs , 2011, Proc. VLDB Endow..

[4]  Martin Theobald,et al.  TriAD: a distributed shared-nothing RDF engine based on asynchronous message passing , 2014, SIGMOD Conference.

[5]  Muhammad Saleem,et al.  HiBISCuS: Hypergraph-Based Source Selection for SPARQL Endpoint Federation , 2014, ESWC.

[6]  Katja Hose,et al.  Partout: a distributed engine for efficient RDF processing , 2012, WWW.

[7]  Katja Hose,et al.  WARP: Workload-aware replication and partitioning for RDF , 2013, 2013 IEEE 29th International Conference on Data Engineering Workshops (ICDEW).

[8]  Xing Zhang,et al.  A Survey on Mobile Edge Networks: Convergence of Computing, Caching and Communications , 2017, IEEE Access.

[9]  Sean Bechhofer.  OWL: Web Ontology Language , 2018, Encyclopedia of Database Systems.

[10]  Feng Xia,et al.  Application optimization in mobile cloud computing: Motivation, taxonomies, and open challenges , 2015, J. Netw. Comput. Appl..

[11]  Qun Li,et al.  A Survey of Fog Computing: Concepts, Applications and Issues , 2015, Mobidata@MobiHoc.

[12]  Biswanath Dutta,et al.  An analytical approach for query optimization based on hypergraph , 2015, 2015 12th International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology (ECTI-CON).

[13]  Georg Lausen,et al.  SP^2Bench: A SPARQL Performance Benchmark , 2008, 2009 IEEE 25th International Conference on Data Engineering.