Pregled bibliografske jedinice broj: 660831
Prediction of Atomic Web Services Reliability for QoS-aware Recommendation
Prediction of Atomic Web Services Reliability for QoS-aware Recommendation // IEEE Transaction on Services Computing, 8 (2015), 3; 425-438 doi:10.1109/TSC.2014.2346492 (međunarodna recenzija, članak, znanstveni)
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Naslov
Prediction of Atomic Web Services Reliability for QoS-aware Recommendation
Autori
Šilić, Marin ; Delač, Goran ; Srbljić, Siniša
Izvornik
IEEE Transaction on Services Computing (1939-1374) 8
(2015), 3;
425-438
Vrsta, podvrsta i kategorija rada
Radovi u časopisima, članak, znanstveni
Ključne riječi
K-means clustering; Prediction; QoS; Recommendation; Reliability; Web Services
Sažetak
While constructing QoS-aware composite work- flows based on service oriented systems, it is necessary to assess nonfunctional properties of potential service selection candidates. In this paper, we present CLUS, a model for reliability prediction of atomic web services that estimates the reliability for an ongoing service invocation based on the data assembled from previous invocations. With the aim to improve the accuracy of the current state-of- the-art prediction models, we incorporate user–, service– and environment– specific parameters of the invocation context. To reduce the scalability issues present in the state-of- the-art approaches, we aggregate the past invocation data using K-means clustering algorithm. In order to evaluate different quality aspects of our model, we conducted experiments on services deployed in different regions of the Amazon cloud. The evaluation results confirm that our model produces more scalable and accurate predictions when compared to the current state-of- the-art approaches.
Izvorni jezik
Engleski
Znanstvena područja
Računarstvo
POVEZANOST RADA
Projekti:
036-0362980-1921 - Računalne okoline za sveprisutne raspodijeljene sustave (Srbljić, Siniša, MZO ) ( CroRIS)
Ustanove:
Fakultet elektrotehnike i računarstva, Zagreb
Citiraj ovu publikaciju:
Časopis indeksira:
- Current Contents Connect (CCC)
- Web of Science Core Collection (WoSCC)
- Science Citation Index Expanded (SCI-EXP)
- SCI-EXP, SSCI i/ili A&HCI
- Scopus