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Load Index Metrics for an Optimized Management of Web Services: A Systematic Evaluation

Load Index Metrics for an Optimized Management of Web Services: A Systematic Evaluation
Load Index Metrics for an Optimized Management of Web Services: A Systematic Evaluation
The lack of precision to predict service performance through load indices may lead to wrong decisions regarding the use of web services, compromising service performance and raising platform cost unnecessarily. This paper presents experimental studies to qualify the behaviour of load indices in the web service context. The experiments consider three services that generate controlled and significant server demands, four levels of workload for each service and six distinct execution scenarios. The evaluation considers three relevant perspectives: the capability for representing recent workloads, the capability for predicting near-future performance and finally stability. Eight different load indices were analysed, including the JMX Average Time index (proposed in this paper) specifically designed to address the limitations of the other indices. A systematic approach is applied to evaluate the different load indices, considering a multiple linear regression model based on the stepwise-AIC method. The results show that the load indices studied represent the workload to some extent; however, in contrast to expectations, most of them do not exhibit a coherent correlation with service performance and this can result in stability problems. The JMX Average Time index is an exception, showing a stable behaviour which is tightly-coupled to the service runtime for all executions. Load indices are used to predict the service runtime and therefore their inappropriate use can lead to decisions that will impact negatively on both service performance and execution cost.
1932-6203
e68819
Souza, Paulo S.L.
976d9a07-c8eb-49a7-93cf-dc8cf8b4cfe0
Santana, Regina H.C.
afe98bd1-acbf-42f9-9e1d-91e3d02b3589
Santana, Marcos J.
3fdd8770-b622-43d8-bd5f-e0406bf4c950
Zaluska, Ed
43f6a989-9542-497e-bc9d-fe20f03cad35
Faical, Bruno S.
ebb89781-cde7-42b2-9f58-632c6ab553d5
Estrella, Julio C.
42542e4e-e820-43bc-bddb-47d7493f938f
Souza, Paulo S.L.
976d9a07-c8eb-49a7-93cf-dc8cf8b4cfe0
Santana, Regina H.C.
afe98bd1-acbf-42f9-9e1d-91e3d02b3589
Santana, Marcos J.
3fdd8770-b622-43d8-bd5f-e0406bf4c950
Zaluska, Ed
43f6a989-9542-497e-bc9d-fe20f03cad35
Faical, Bruno S.
ebb89781-cde7-42b2-9f58-632c6ab553d5
Estrella, Julio C.
42542e4e-e820-43bc-bddb-47d7493f938f

Souza, Paulo S.L., Santana, Regina H.C., Santana, Marcos J., Zaluska, Ed, Faical, Bruno S. and Estrella, Julio C. (2013) Load Index Metrics for an Optimized Management of Web Services: A Systematic Evaluation. PLoS ONE, 8 (7), e68819. (doi:10.1371/journal.pone.0068819).

Record type: Article

Abstract

The lack of precision to predict service performance through load indices may lead to wrong decisions regarding the use of web services, compromising service performance and raising platform cost unnecessarily. This paper presents experimental studies to qualify the behaviour of load indices in the web service context. The experiments consider three services that generate controlled and significant server demands, four levels of workload for each service and six distinct execution scenarios. The evaluation considers three relevant perspectives: the capability for representing recent workloads, the capability for predicting near-future performance and finally stability. Eight different load indices were analysed, including the JMX Average Time index (proposed in this paper) specifically designed to address the limitations of the other indices. A systematic approach is applied to evaluate the different load indices, considering a multiple linear regression model based on the stepwise-AIC method. The results show that the load indices studied represent the workload to some extent; however, in contrast to expectations, most of them do not exhibit a coherent correlation with service performance and this can result in stability problems. The JMX Average Time index is an exception, showing a stable behaviour which is tightly-coupled to the service runtime for all executions. Load indices are used to predict the service runtime and therefore their inappropriate use can lead to decisions that will impact negatively on both service performance and execution cost.

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Published date: 16 July 2013
Organisations: Web & Internet Science

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Local EPrints ID: 356773
URI: http://eprints.soton.ac.uk/id/eprint/356773
ISSN: 1932-6203
PURE UUID: 6beb841a-b75d-4e60-8dab-cdc45ba6c7ee

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Date deposited: 13 Sep 2013 09:08
Last modified: 11 Nov 2019 20:55

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Contributors

Author: Paulo S.L. Souza
Author: Regina H.C. Santana
Author: Marcos J. Santana
Author: Ed Zaluska
Author: Bruno S. Faical
Author: Julio C. Estrella

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