SaaS application mashup based on High Speed Message Processing

Abstract

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.