PuLSaR: preference-based cloud service selection for cloud service brokers. Issue 1 (August 2015)

• Record Type: Journal Article
• Authors: Patiniotakis, Ioannis; Verginadis, Yiannis; Mentzas, Gregoris
• Is Part Of: Journal of internet services and applications. Volume 6:Issue 1(2015)
• Page Start: 1
• Page End: 14
• Publication Date: 2015-08
• Subjects: Cloud Service Broker -- Optimisation -- Service Ranking -- MCDM; TCP/IP (Computer network protocol) -- Periodicals; Internet -- Periodicals; Internet -- Security measures -- Periodicals; 004.678
• DOI: 10.1186/s13174-015-0042-4
• Languages: English
• ISSNs: 1867-4828

Abstract

Abstract Over the last few years, the vast increase of cloud service offerings that are available from heterogeneous cloud vendors, has made the evaluation and selection of desired cloud services, a cumbersome task for service consumers. In that respect, there is an increasing need for user guidance and intermediation during the service selection process but also during the cloud service consumption that should always refer to the best possible choice based on user preferences. In this paper, we discuss the Preference-based cLoud Service Recommender (PuLSaR) that uses a holistic multi-criteria decision making (MCDM) approach for offering optimisation as a brokerage service. The specification and implementation details of this proposed software mechanism are thoroughly discussed while the background method used is summarised. Both method and brokerage service allow for the multi-objective assessment of cloud services in a unified way, taking into account precise and imprecise metrics and dealing with their fuzziness. We cope with the fuzziness of imprecise metrics in the sense that this approach deals with linguistically expressed preferences and cloud service characteristics that lack a fixed or precise value and entail a level of vagueness which can only be captured using the Zadeh's Fuzzy Set Theory. Furthermore, this paper reports on a number of experiments that were conducted in order to measure PuLSaR's performance and scalability.