Quality of Service Centric Web Service Composition: Assessing Composition Impact Scale towards Fault Proneness

Quality of Service Centric Web Service Composition: Assessing Composition Impact Scale towards Fault Proneness

Sujatha Varadi

Contact

G Appa Rao

Contact

1 GITAM University

GJCST Volume 14 Issue C9

Article Fingerprint

ReserarchID

CSTSDE4899L

Quality of Service Centric Web Service Composition: Assessing Composition Impact Scale towards Fault Proneness Banner

Service composition in service oriented architecture is an important activity. In regard to achieve the quality of service and secured activities from the web service compositions, they need to be verified about their impact towards fault proneness before deploying that service composition. Henceforth, here in this paper, we devised a novel statistical approach to assess the service composition impact scale towards fault proneness. The devised model explores the higher and lower ranges of the service composition impact scale, which is from the knowledge of earlier compositions that are notified as fault prone.

11 Cites in Articles

References

M Papazoglou,D Georgakopoulos (2003). Introduction.
R Aggarwal (2004). Constraint-driven Web Service Composition in METEOR-S.
Alexander Lazovik,Marco Aiello,Mike Papazoglou (2003). Planning and Monitoring the Execution of Web Service Requests.
E Sirin,J Hendler,B Parsia (2003). Semi-automatic Composition of Web Services Using Semantic Descriptions.
B Srivastava,J Koehler (2003). Web Service Composition -Current Solutions and Open Problems.
Octavio Martín-Díaz,Antonio Ruiz-Cortés,Amador Durán,Carlos Müller (2005). An Approach to Temporal-Aware Procurement of Web Services.
Tao Yu,Kwei-Jay Lin (2005). Service Selection Algorithms for Composing Complex Services with Multiple QoS Constraints.
L Zeng,B Benatallah (2004). QoS-aware Middleware for Web Services Composition.
J Cardoso,A Sheth,J Miller,J Arnold,K Kochut (2004). Quality of service for workflows and web service processes.
D Ardagna,B Pernici (2005). Global and local QoS constraints guarantee in Web service selection.
Girish Chafle,Sunil Chandra,Pankaj Kankar,Vijay Mann (2005). Handling Faults in Decentralized Orchestration of Composite Web Services.

Download References

Funding

No external funding was declared for this work.

Conflict of Interest

The authors declare no conflict of interest.

Ethical Approval

No ethics committee approval was required for this article type.

Data Availability

Not applicable for this article.

Sujatha Varadi. 2015. \u201cQuality of Service Centric Web Service Composition: Assessing Composition Impact Scale towards Fault Proneness\u201d. Global Journal of Computer Science and Technology - C: Software & Data Engineering GJCST-C Volume 14 (GJCST Volume 14 Issue C9): .

More Citation Formats

Select Citation Style:

Download Citation

Download Article

GJCST Volume 14 Issue C9
Pg. 13- 17

Explore Journals Explore Volume Read This Issue

Journal Specifications

Crossref Journal DOI 10.17406/gjcst

Print ISSN 0975-4350

e-ISSN 0975-4172

Keywords

composition support service composition impact scale service descriptor impact scale web service composition fault pronen web service compositions

Classification

Not Found

Submission ReceivedDecember 14, 2013
RevisedDecember 14, 2013
Peer Review Double Blind
Handling Editor
Accepted January 4, 2014
Published January 15, 2014

Version of record

v1.2

Issue date

January 21, 2015

Language

English

Experiance in AR

The methods for personal identification and authentication are no exception.

Read in 3D

The methods for personal identification and authentication are no exception.

Article Matrices

Total Score: 102

Country: India

Subject: Global Journal of Computer Science and Technology - C: Software & Data Engineering

Authors: Sujatha Varadi, G Appa Rao (PhD/Dr. count: 0)

View Count (all-time): 213

Total Views (Real + Logic): 8410

Total Downloads (simulated): 2228

Publish Date: 2015 01, Wed

Monthly Totals (Real + Logic):

Month 1: 64 views
Month 2: 46 views
Month 3: 23 views
Month 4: 35 views
Month 5: 62 views
Month 6: 25 views
Month 7: 47 views
Month 8: 44 views
Month 9: 54 views
Month 10: 31 views
Month 11: 22 views
Month 12: 14 views
Month 13: 20 views
Month 14: 36 views
Month 15: 33 views
Month 16: 36 views
Month 17: 19 views
Month 18: 26 views
Month 19: 17 views
Month 20: 36 views
Month 21: 16 views
Month 22: 44 views
Month 23: 30 views
Month 24: 34 views
Month 25: 50 views
Month 26: 30 views
Month 27: 29 views
Month 28: 32 views
Month 29: 24 views
Month 30: 33 views
Month 31: 24 views
Month 32: 26 views
Month 33: 18 views
Month 34: 29 views
Month 35: 18 views
Month 36: 10 views
Month 37: 40 views
Month 38: 35 views
Month 39: 16 views
Month 40: 17 views
Month 41: 23 views
Month 42: 30 views
Month 43: 40 views
Month 44: 37 views
Month 45: 38 views
Month 46: 32 views
Month 47: 42 views
Month 48: 30 views
Month 49: 34 views
Month 50: 21 views
Month 51: 22 views
Month 52: 23 views
Month 53: 41 views
Month 54: 27 views
Month 55: 30 views
Month 56: 28 views
Month 57: 35 views
Month 58: 23 views
Month 59: 30 views
Month 60: 38 views
Month 61: 13 views
Month 62: 34 views
Month 63: 38 views
Month 64: 21 views
Month 65: 16 views
Month 66: 42 views
Month 67: 42 views
Month 68: 34 views
Month 69: 25 views
Month 70: 11 views
Month 71: 24 views
Month 72: 42 views
Month 73: 45 views
Month 74: 28 views
Month 75: 39 views
Month 76: 28 views
Month 77: 30 views
Month 78: 16 views
Month 79: 35 views
Month 80: 16 views
Month 81: 29 views
Month 82: 26 views
Month 83: 15 views
Month 84: 25 views
Month 85: 31 views
Month 86: 38 views
Month 87: 26 views
Month 88: 30 views
Month 89: 34 views
Month 90: 36 views
Month 91: 29 views
Month 92: 35 views
Month 93: 28 views
Month 94: 17 views
Month 95: 44 views
Month 96: 14 views
Month 97: 42 views
Month 98: 22 views
Month 99: 14 views
Month 100: 29 views
Month 101: 18 views
Month 102: 19 views
Month 103: 24 views
Month 104: 15 views
Month 105: 37 views
Month 106: 19 views
Month 107: 30 views
Month 108: 24 views
Month 109: 20 views
Month 110: 37 views
Month 111: 31 views
Month 112: 29 views
Month 113: 37 views
Month 114: 34 views
Month 115: 26 views
Month 116: 26 views
Month 117: 19 views
Month 118: 34 views
Month 119: 34 views
Month 120: 14 views
Month 121: 21 views
Month 122: 43 views
Month 123: 32 views
Month 124: 33 views
Month 125: 37 views
Month 126: 37 views
Month 127: 31 views
Month 128: 25 views
Month 129: 40 views
Month 130: 20 views
Month 131: 34 views
Month 132: 27 views
Month 133: 34 views
Month 134: 42 views
Month 135: 47 views

Total Views: 8410

Total Downloads: 2228

2026 Trends

Research Identity (RIN)

Published Article

Our website is actively being updated, and changes may occur frequently. Please clear your browser cache if needed. For feedback or error reporting, please email [email protected]

This Page is Under Development

We are currently updating this article page for a better experience.