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Paper Abstract and Keywords
Presentation 2015-12-05 14:50
Performance Prediction for GAE Using the UPPAAL
Sachi Nishida, Yoshiyuki Shinkawa (Ryukoku Univ.) SWIM2015-15
Abstract (in Japanese) (See Japanese page) 
(in English) Recently, PaaS type cloud services like Google App Engine (GAE) are becoming a candidate for the system
processing platform of enterprise information systems. PaaS has excellent properties for developing and operating backbone
systems cost-effectively, along with the flexibility of application forms. However we often face with the problems
regarding performance prediction during development, since PaaS system structure is hidden and virtualize and required
performance related information is not opened for general public. In addition, the more relaxed data integrity principle
called BASE makes the data integrity evaluation difficult. This paper proposes a process and relevant techniques to predict
the performance of transaction systems for GAE datastore database, which is one of the NoSQL databases, using
the model checking tool UPPAAL. In order to create the prediction model, we focus on the Application Programming
Interfaces (APIs) instead of system structures, and regard the system as a mechanism to process these APIs. Moreover,
we write Java programs to measure the processing time of each API, and incorporate the statistical properties like mean
and variance into the model.
Keyword (in Japanese) (See Japanese page) 
(in English) Transaction Processing / Cloud Computing / Google App Engine / UPPAAL / Performance Prediction / / /  
Reference Info. IEICE Tech. Rep., vol. 115, no. 353, SWIM2015-15, pp. 19-24, Dec. 2015.
Paper # SWIM2015-15 
Date of Issue 2015-11-28 (SWIM) 
ISSN Print edition: ISSN 0913-5685    Online edition: ISSN 2432-6380
Copyright
and
reproduction		 All rights are reserved and no part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopy, recording, or any information storage and retrieval system, without permission in writing from the publisher. Notwithstanding, instructors are permitted to photocopy isolated articles for noncommercial classroom use without fee. (License No.: 10GA0019/12GB0052/13GB0056/17GB0034/18GB0034)
Download PDF SWIM2015-15

Conference Information
Committee SWIM  
Conference Date 2015-12-05 - 2015-12-05 
Place (in Japanese) (See Japanese page) 
Place (in English) Tokyo polytechnic Univ. 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Model implementation, etc. (Work Shop) 
Paper Information
Registration To SWIM 
Conference Code 2015-12-SWIM 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Performance Prediction for GAE Using the UPPAAL 
Sub Title (in English)  
Keyword(1) Transaction Processing  
Keyword(2) Cloud Computing  
Keyword(3) Google App Engine  
Keyword(4) UPPAAL  
Keyword(5) Performance Prediction  
Keyword(6)  
Keyword(7)  
Keyword(8)  
1st Author's Name Sachi Nishida  
1st Author's Affiliation Ryukoku University (Ryukoku Univ.)
2nd Author's Name Yoshiyuki Shinkawa  
2nd Author's Affiliation Ryukoku University (Ryukoku Univ.)
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Speaker Author-1 
Date Time 2015-12-05 14:50:00 
Presentation Time 25 minutes 
Registration for SWIM 
Paper # SWIM2015-15 
Volume (vol) vol.115 
Number (no) no.353 
Page pp.19-24 
#Pages 6 
Date of Issue 2015-11-28 (SWIM) 

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