On supporting dynamic web service selection with histogramming

Abstract

To ensure that consumer requests for web services are served successfully and effectively amidst overwhelming options, one must narrow the web service search to only the most qualified, highest-ranked services. However, today, the ranking of services is done only with regards to static attributes or with a snapshot of current values, resulting in low quality search results. To improve user experience, one must consider dynamic quality of service measures and address the practical challenges they incur. In this paper, we propose using histograms and an area-to-right-of-threshold function to handle the fluctuation and absence of attributes values effectively. This permits utilizing well-established techniques for selecting web services, such as skyline and top-k. We also discuss algorithmic considerations to efficiently produce dynamic web service discovery results.