Dynamis: Effective Context-Aware Web Service Selection Using Dynamic Attributes

Date

2015

Authors

Pahlevan, Atousa
Duprat, Jean-Luc
Thomo, Alex
Müller, Hausi

Journal Title

Journal ISSN

Volume Title

Publisher

Future Internet

Abstract

Quality web service discovery requires narrowing the search space from an overwhelming set of services down to the most relevant ones, while matching the consumer’s request. Today, the ranking of services only considers static attributes or snapshots of current attribute values, resulting in low-quality search results. To satisfy the user’s need for timely, well-chosen web services, we ought to consider quality of service attributes. The problem is that dynamic attributes can be difficult to measure, frequently fluctuate, are context-sensitive and depend on environmental factors, such as network availability at query time. In this paper, we propose the Dynamis algorithm to address these challenges effectively. Dynamis is based on well-established database techniques, such as skyline and aggregation. We illustrate our approach using observatory telescope web services and experimentally evaluate it using stock market data. In our evaluation, we show significant improvement in service selection over existing techniques.

Description

Keywords

service discovery, service selection, quality of service (QoS), Dynamis, aggregation, skyline, histogram, top k

Citation

Pahlevan, A., Duprat, J., Thomo, A. & Müller, H. (2015). Dynamis: Effective Context-Aware Web Service Selection Using Dynamic Attributes. Future Internet, 7(2), 110-139. https://doi.org/10.3390/fi7020110