A Framework for Measuring Performance in Service-Oriented Architecture

Quafafou, Mohamed; Jarir, Zahi; Erradi, Mohammed

doi:10.1109/nwesp.2007.24

Cited by 12 publications

(8 citation statements)

References 14 publications

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“…There are many considerations to measure service response time [4] as Figure 2 o The potential problems of XML which is the standard message format increases the time needed to process a request. o The time needed to discover the services through the directory either in design time or run time.…”

Section: Service-oriented Architecture Performance Metrics 41 Servicmentioning

confidence: 99%

“…o Adaptation of service composition by adding new service or adapting existing services. o Think time is an elapsed time between the end of a response time generated by a service and the beginning of an end user's request [4].…”

Section: Service-oriented Architecture Performance Metrics 41 Servicmentioning

confidence: 99%

“…There are two metrics for throughput; throughput of a service and throughput of a business process [4] as Figure 3 stated.…”

Section: Throughputmentioning

confidence: 99%

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Performance Prediction of Service-Oriented Architecture - A survey

Moniem¹,

Ammar²

2014

IJCATR

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Performance prediction and evaluation for SOA based applications assist software consumers to estimate their applications based on service specifications created by service developers. Incorporating traditional performance models such as Stochastic Petri Nets, Queuing Networks, and Simulation present drawbacks of SOA based applications due to special characteristics of SOA such as lose coupling, self-contained and interoperability. Although, researchers have suggested many methods in this area during last decade, none of them has obtained popular industrial use. Based on this, we have conducted a comprehensive survey on these methods to estimate their applicability. This survey classified these approaches according to their performance metrics analyzed, performance models used, and applicable project stage. Our survey helps SOA architects to select the appropriate approach based on target performance metric and researchers to identify the SOA state-of-art performance prediction.

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Section: Service-oriented Architecture Performance Metrics 41 Servicmentioning

confidence: 99%

Section: Service-oriented Architecture Performance Metrics 41 Servicmentioning

confidence: 99%

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Performance Prediction of Service-Oriented Architecture - A survey

Moniem¹,

Ammar²

2014

IJCATR

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“…Most of the reviewed work deals with aspects and metrics to support the first four phases based on design-time data: Metrics to measure busi-ness alignment of SOA implementations [1,30], procedures to model [6,16] and implement SOA [3], including the prediction of development effort and implementation complexity early in the design phase [37]. Metrics to measure granularity, complexity and reuse [15,35,36], performance [5,13] and QoS [28,31] of SOAbased services also rely on design-time data. Most work on operation and optimization has been done on how to handle service level agreements primarily based on design-time data: how to formally describe them [19,34,39,40], technically implement, test and enforce them [4,10,15,17,18,23,25,26,32,33,42,44,45] or how to monitor them [2,20,21].…”

Section: Related Workmentioning

confidence: 99%

FIT for SOA? Introducing the F.I.T.-Metric to Optimize the Availability of Service Oriented Architectures

Frischbier

Buchmann

Putz

2012

Complex Systems Design &Amp; Management

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The paradigm of service-oriented architectures (SOA) is by now accepted for application integration and in widespread use. As an underlying key-technology of cloud computing and because of unresolved issues during operation and maintenance it remains a hot topic. SOA encapsulates business functionality in services, combining aspects from both the business and infrastructure level. The reuse of services results in hidden chains of dependencies that affect governance and optimization of service-based systems. To guarantee the cost-effective availability of the whole service-based application landscape, the real criticality of each dependency has to be determined for IT Service Management (ITSM) to act accordingly. We propose the FIT-metric as a tool to characterize the stability of existing service configurations based on three components: functionality, integration and traffic. In this paper we describe the design of FIT and apply it to configurations taken from a production-strength SOA-landscape. A prototype of FIT is currently being implemented at Deutsche Post MAIL.

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“…al. discuss metrics for modelling web service performance [11]. Head presents a benchmark for SOAP communication in grid web services [10].…”

Section: Related Workmentioning

confidence: 99%

An Extensible Monitoring Framework for Measuring and Evaluating Tool Performance in a Service-Oriented Architecture

Becker

Kulovits

Kraxner

et al. 2009

Lecture Notes in Computer Science

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Abstract. The lack of QoS attributes and their values is still one of the fundamental drawbacks of web service technology. Most approaches for modelling and monitoring QoS and web service performance focus either on client-side measurement and feedback of QoS attributes, or on ranking and discovery, developing extensions of the standard web service discovery models. However, in many cases, provider-side measurement can be of great additional value to aid the evaluation and selection of services and underlying implementations.We present a generic architecture and reference implementation for non-invasive provider-side instrumentation of data-processing tools exposed as QoS-aware web services, where real-time quality information is obtained through an extensible monitoring framework. In this architecture, dynamically configurable execution engines measure QoS attributes and instrument the corresponding web services on the provider side. We demonstrate the application of this framework to the task of performance monitoring of a variety of applications on different platforms, thus enriching the services with real-time QoS information, which is accumulated in an experience base.

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A Framework for Measuring Performance in Service-Oriented Architecture

Cited by 12 publications

References 14 publications

Performance Prediction of Service-Oriented Architecture - A survey

Performance Prediction of Service-Oriented Architecture - A survey

FIT for SOA? Introducing the F.I.T.-Metric to Optimize the Availability of Service Oriented Architectures

An Extensible Monitoring Framework for Measuring and Evaluating Tool Performance in a Service-Oriented Architecture

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