A new approach to performance optimization of mashups via data flow refactoring
Proceedings of the Second Asia-Pacific Symposium on Internetware
An optimization strategy for mashups performance based on relational algebra
APWeb'12 Proceedings of the 14th Asia-Pacific international conference on Web Technologies and Applications
Towards an SLA-Driven cache adjustment approach for applications on PaaS
Proceedings of the 5th Asia-Pacific Symposium on Internetware
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The recent surge of popularity has established Mashups as an important category of Web 2.0 applications. Mashups are essentially Web services that are often created by end-users. They aggregate and manipulate data from sources around the World Wide Web. Surprisingly, there are very few studies on the scalability and performance of mashups. In this paper, we study caching as a vehicle for enhancing the scalability and the efficiency of mashups. Although caching has long been used to improve the performance of Web services, mashups pose some unique challenges that necessitate a more dynamic approach to caching. Towards this end, we present MACE - a cache specifically designed for mashups. In designing the MACE framework this paper makes three technical contributions. First, we present a model for representing mashups and analyzing their performance. Second, we propose an indexing scheme that enables efficient reuse of cached data for newly created mashups. Finally, this paper also describes a novel caching policy that analyzes the costs and benefits of caching data at various stages of different mashups and selectively stores data that is most effective in improving system scalability. We report experiments studying the performance of the MACE system.