By Guojun Wang, Yanbo Han, Gregorio Martínez Pérez
This booklet constitutes the refereed lawsuits of the tenth Asia-Pacific companies Computing convention, APSCC 2016, held in Zhangjiajie, China, in November 2016.
The 38 revised complete papers provided during this e-book have been conscientiously reviewed and chosen from 107 submissions. The papers hide quite a lot of themes within the fields of cloud/utility/Web computing/big facts; foundations of providers computing; social/peer-to-peer/mobile/ubiquitous/pervasive computing; service-centric computing types; integration of telecommunication SOA and net providers; enterprise procedure integration and administration; and safety in services.
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Extra resources for Advances in Services Computing: 10th Asia-Pacific Services Computing Conference, APSCC 2016, Zhangjiajie, China, November 16-18, 2016, Proceedings
In: Proceedings of the Eighth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 538–543. ACM (2002) 16. : Divrank: the interplay of prestige and diversity in information networks. In: Proceedings of the 16th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 1009–1018. ACM (2010) 17. : Diversiﬁed ranking on large graphs: an optimization viewpoint. In: Proceedings of the 17th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp.
Cn Abstract. The number of services is proliferating dramatically and the rate of services’ evolution has also been increasingly fluctuating in recent years. The demands of service composition also show the characteristics of individuation and diversiﬁcation at the same time. The traditional methods of service composition are difﬁcult to meet the multiple granularity demands of users. This paper proposes a novel multiple granular service composition model based on services granular space. The model ﬁrstly constructs service granularity by service clustering.
Get ﬁve service compositions for each degree of similarity. Use the average response time and the average number of granular as the ﬁnal result. Take the service response time as the metrics to determine the optimal granular. Fig. 6. Service composition response time changes with the number of service grains Fig. 7. Number of service grains changes with similarity As the number of services is ﬁxed, when we change the parameter of similarity, the number of service grains is varied. The higher the degree of similarity, the smaller the number of atomic services in each service grain contained.
Advances in Services Computing: 10th Asia-Pacific Services Computing Conference, APSCC 2016, Zhangjiajie, China, November 16-18, 2016, Proceedings by Guojun Wang, Yanbo Han, Gregorio Martínez Pérez