Abstract
Cyber-physical systems, encompass the real physical space and virtual cyber space for providing advanced service for humans, which together, are also namely Internet of Things. The complex and large scale relationships among nodes contain the potential information of user, which is required and essential for providing high quality personalized service. Graph is used to represent, make fusion and process the relationships data, which has been used in many domains with traditional small data sets. K-hop reachability query answering in graphs is seeing a growing number of applications, such as ranked keyword search in databases, social networking, ontology reasoning and bioinformatics. Currently, techniques for efficient evaluation of such queries are based on vertex-cover technology. These methods suffer from a lack of scalability; that is, they cannot be applied to very large graphs. To solve these problems, we propose the compound-index method, namely BFSI-B, which uses the special index to decrease the k-hop reachability query time and improve pruning efficiency. The theoretical analysis and experiment results demonstrate that our method has a smaller index size and a faster query time than the k-reach method, in both dense graphs and very large graphs.
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