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composit:wsc09 [2014/11/10 10:54] – [Table] pablo.rodriguez.mier | composit:wsc09 [2014/11/20 17:19] (actual) – [Evaluation] pablo.rodriguez.mier | ||
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===== Purpose of this web document ===== | ===== Purpose of this web document ===== | ||
The purpose of this document is to extend the results obtained using the Web Service Challenge 2008 datasets | The purpose of this document is to extend the results obtained using the Web Service Challenge 2008 datasets | ||
- | with the most recent version of this challenge (Web Service Challenge 2009-2010). The main reason behind including | + | with the most recent version of this challenge (Web Service Challenge 2009-2010). The main reason behind |
- | datasets | + | is that the WSC' |
for filtering services by their QoS. Moreover, this difference makes our results not comparable with the other approaches since we are providing semantic compositions | for filtering services by their QoS. Moreover, this difference makes our results not comparable with the other approaches since we are providing semantic compositions | ||
- | just optimising the composition length and the number of services ignoring QoS. | + | just optimising the composition length and the number of services ignoring QoS. We are currently working towards extending the proposed framework with QoS. Meanwhile, we think these results can be also interesting to compare the scalability of different |
- | + | ||
- | We are currently working towards extending the proposed framework with QoS. Meanwhile, we think these results can be also interesting to compare the scalability of different | + | |
composition frameworks. | composition frameworks. | ||
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===== Evaluation ===== | ===== Evaluation ===== | ||
+ | We tested different configurations to study their individual performance and the overall impact on composition response times. In particular, we used the following configurations: | ||
+ | |||
+ | |||
+ | - **SPARQL D/M**: pure //SPARQL// Discovery / Matchmaking where all interactions with the Service and Knowledge Base managers are directly implemented as //SPARQL// queries. This is the typical approach of discovery engines and was the original implementation of iServe. | ||
+ | - **Index. D/ | ||
+ | - **Full Indexed D/M**: both service discovery and concept matchmaking relied on local indexes pre-populated at load time (and updated with writes). In this configuration, | ||
+ | |||
+ | The forward graph generation time + optimizations (**G. time**) and the total number of SPARQL queries generated (**# | ||
+ | " | ||
+ | |||
+ | |||
+ | |||
+ | ^ Dataset | ||
+ | | ::: | ::: ^ 1) SPARQL D/M | ||
+ | | ::: | ::: ^ G. time (s) ^ # | ||
+ | | WSC' | ||
+ | | WSC' | ||
+ | | WSC' | ||
+ | | WSC' | ||
+ | | WSC' | ||
+ | |||
+ | All datasets were solved with optimal values for composition length and number of services, showing a similar scalability as observed in the WSC'08 datasets (see graph below). | ||
+ | |||
+ | {{: | ||
- | ^ Dataset | ||
- | | ::: | ::: ^ 1) SPARQL D/M | ||
- | | ::: | ::: ^ G. time (s) ^ # | ||
- | | WSC' | ||