• Title/Summary/Keyword: SaaS Aggregation

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SaaS application mashup based on High Speed Message Processing

  • Chen, Zhiguo;Kim, Myoungjin;Cui, Yun
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.16 no.5
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    • pp.1446-1465
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    • 2022
  • Diversified SaaS applications allow users more choices to use, according to their own preferences. However, the diversification of SaaS applications also makes it impossible for users to choose the best one. Furthermore, users can't take advantage of the functionality between SaaS applications. In this paper, we propose a platform that provides an SaaS mashup service, by extracting interoperable service functions from SaaS-based applications that independent vendors deploy and supporting a customized service recommendation function through log data binding in the cloud environment. The proposed SaaS mashup service platform consists of a SaaS aggregation framework and a log data binding framework. Each framework was concreted by using Apache Kafka and rule matrix-based recommendation techniques. We present the theoretical basis of implementing the high-performance message-processing function using Kafka. The SaaS mashup service platform, which provides a new type of mashup service by linking SaaS functions based on the above technology described, allows users to combine the required service functions freely and access the results of a rich service-utilization experience, using the SaaS mashup function. The platform developed through SaaS mashup service technology research will enable various flexible SaaS services, expected to contribute to the development of the smart-contents industry and the open market.

User Targerting SaaS Application Mash-Up Service Framework using Complex-Context and Rule-Martix (복합 콘텍스트 및 Rule-Matrix를 활용한 사용자 맞춤형 SaaS 어플리케이션 연동 서비스 프레임워크)

  • Jung, Jong Jin;Cui, Yun;Kwon, Kyung Min;Lee, Han Ku
    • Journal of Korea Multimedia Society
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    • v.20 no.7
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    • pp.1054-1064
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    • 2017
  • With the development of cloud computing, internet technology and Internet of Things(IoT), most of applications are being smarter and changing from native application to SaaS (Software as a Service) application. New versatile SaaS applications are being released through various app portals (e.g. appstore, googleplay, T-Store, and so on). However, a user has a difficulty in searching, choosing an suitable application to him. It is also hard for him to know what functions of each SaaS application are useful. He wants to be recommended something inter-operated SaaS service according to his personality and his situation. Therefore, this paper presents a way of making mash-up of SaaS applications in order to provide the most convenient inter-operated SaaS service to user. This paper also presents SaaS Application Mash-up Framework (SAMF), complex context and rule matrix. The proposed SAMF is a main system that totally manage SaaS application mash-up service. Complex context and rule matrix are key components in order to recommend what SaaS applications are needed and how those SaaS applications are inter-operated. The SAMF collects complex contexts (User Description, Status Description, SaaS Service Description) in order to choose which SaaS applications are useful, analyze what functions to use, how to mash-up.