Title :
CB-Cloudle and cloud crawlers
Author :
Shengjie Gong ; Kwang Mong Sim
Author_Institution :
Sch. of Comput., Univ. of Kent, Chatham, UK
Abstract :
Cloud services emerge as one of the most important parts for a company. Amazon, Rackspace, Google, Microsoft, to name a few, all fight to gain a foothold as cloud services providers. CB-Cloudle, a search engine aiming to discover the available options of cloud services and to suggest the most appropriate alternatives, is presented here to meet with the end users´ needs. In this work, this software platform CB-Cloudle specialised in searching for cloud services, and an automated cloud services crawler is also implemented. A k-means clustering algorithm with centroids was utilised to improve the search effectiveness and efficiency. This k-means clustering algorithm was introduced to discover the groups of similar cloud service entries, using a new similarity matrix to calculate the distance between cloud service entries.
Keywords :
Web sites; cloud computing; pattern clustering; search engines; Amazon; CB-Cloudle; CB-cloudle; Google; Microsoft; Rackspace; automated cloud services crawler; cloud crawlers; cloud service entry; cloud services providers; k-means clustering algorithm; search effectiveness; search efficiency; search engine; similarity matrix; software platform; Algorithm design and analysis; Cloud computing; Clustering algorithms; Crawlers; Databases; Pricing; Search engines; centroids; cloud services; crawler; k-means; search engine;
Conference_Titel :
Software Engineering and Service Science (ICSESS), 2014 5th IEEE International Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-4799-3278-8
DOI :
10.1109/ICSESS.2014.6933503