421,663 research outputs found

    A Review on Software Performance Analysis for Early Detection of Latent Faults in Design Models

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    Organizations and society could face major breakdown if IT strategies do not comply with performance requirements. This is more so in the era of globalization and emergence of technologies caused more issues. Software design models might have latent and potential issues that affect performance of software. Often performance is the neglected area in the industry. Identifying performance issues in the design phase can save time, money and effort. Software engineers need to know the performance requirements so as to ensure quality software to be developed. Software performance engineering a quantitative approach for building software systems that can meet performance requirements. There are many design models based on UML, Petri Nets and Product-Forms. These models can be used to derive performance models that make use of LQN, MSC, QNM and so on. The design models are to be mapped to performance models in order to predict performance of system early and render valuable feedback for improving quality of the system. Due to emerging distributed technologies such as EJB, CORBA, DCOM and SOA applications became very complex with collaboration with other software. The component based software systems, software systems that are embedded, distributed likely need more systematic performance models that can leverage the quality of such systems. Towards this end many techniques came into existence. This paper throws light into software performance analysis and its present state-of-the-art. It reviews different design models and performance models that provide valuable insights to make well informed decisions

    Performance controls for distributed telecommunication services

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    As the Internet and Telecommunications domains merge, open telecommunication service architectures such as TINA, PARLAY and PINT are becoming prevalent. Distributed Computing is a common engineering component in these technologies and promises to bring improvements to the scalability, reliability and flexibility of telecommunications service delivery systems. This distributed approach to service delivery introduces new performance concerns. As service logic is decomposed into software components and distnbuted across network resources, significant additional resource loading is incurred due to inter-node communications. This fact makes the choice of distribution of components in the network and the distribution of load between these components critical design and operational issues which must be resolved to guarantee a high level of service for the customer and a profitable network for the service operator. Previous research in the computer science domain has addressed optimal placement of components from the perspectives of minimising run time, minimising communications costs or balancing of load between network resources. This thesis proposes a more extensive optimisation model, which we argue, is more useful for addressing concerns pertinent to the telecommunications domain. The model focuses on providing optimal throughput and profitability of network resources and on overload protection whilst allowing flexibility in terms of the cost of installation of component copies and differentiation in the treatment of service types, in terms of fairness to the customer and profitability to the operator. Both static (design-time) component distribution and dynamic (run-time) load distribution algorithms are developed using Linear and Mixed Integer Programming techniques. An efficient, but sub-optimal, run-time solution, employing Market-based control, is also proposed. The performance of these algorithms is investigated using a simulation model of a distributed service platform, which is based on TINA service components interacting with the Intelligent Network through gateways. Simulation results are verified using Layered Queuing Network analytic modelling Results show significant performance gains over simpler methods of performance control and demonstrate how trade-offs in network profitability, fairness and network cost are possible

    From the Queue to the Quality of Service Policy: A Middleware Implementation

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    The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-642-02481-8_61Quality of service policies in communications is one of the current trends in distributed systems based on middleware technology. To implement the QoS policies it is necessary to define some common parameters. The aim of the QoS policies is to optimize the user defined QoS parameters. This article describes how to obtain the common QoS parameters using message queues for the communications and control components of communication. The paper introduces the Queue-based Quality of Service Cycle concept for each middleware component. The QoS parameters are obtained directly from the queue parameters, and Quality of Service Policies controls directly the message queues to obtain the user-defined parameters values.The middleware architecture described in this article is a part of the coordinated project SIDIRELI: Distributed Systems with Limited Resources. Control Kernel and Coordination. Education and Science Department, Spanish Government. CICYT: MICINN: DPI2008-06737-C02-01/02.Poza-Lujan, J.; Posadas-Yagüe, J.; Simó Ten, JE. (2009). From the Queue to the Quality of Service Policy: A Middleware Implementation. En Distributed Computing, Artificial Intelligence, Bioinformatics, Soft Computing, and Ambient Assisted Living. Springer Verlag (Germany). 432-437. doi:10.1007/978-3-642-02481-8_61S432437Aurrecoechea, C., Campbell, A.T., Hauw, L.: A Survey of QoS Architectures. Multimedia Systems Journal, Special Issue on QoS Architecture 6(3), 138–151 (1998)OMG. Data Distribution Service for Real-Time Systems, v1.1. Document formal/2005-12-04 (December 2005)Botts, M., Percivall, G., Reed, C., Davidson, J.: OGC®. Sensor Web Enablement: Overview And High Level Architecture, OpenGIS Consortium Inc (2006)Poza, J.L., Posadas, J.I., Simó, J.E.: QoS-based middleware architecture for distributed control systems. In: International Symposium on Distributed Computing and Artificial Intelligence, Salamanca (2008)Vogel, A., Kerherve, B., von Bochmann, G., Gecsei, J.: Distributed Multi-media and QoS: A Survey 2(2), 10–19 (1995)Crawley, E., Nair, R., Rajagopalan, B.: RFC 2386: A Framework for QoS-based Routing in the Internet, pp. 1–37, XP002219363 (August 1998)ITU-T Recommendation E.800 (0894). Terms and Definitions Related to Quality of Service and Network Performance Including Dependability (1994)Stuck, B.W., Arthurs, E.: A Computer & Communications Network Performance Analysis Primer. Prentice Hall, Englewood Cliffs (1984)Jain, R.: The art of Computer Systems Performance Analysis. John Wiley & Sons Inc., New york (1991)Coulouris, G., Dollimore, J., Kindberg, T.: Distributed Systems. Concepts and Design, 3rd edn. Addison Wesley, Madrid (2001)Jung, J.-l.: Quality of Service in Telecommunications Part II: Translation of QoS Pa-rameters into ATM Performance Parameters in B-ISDN. IEEE Comm. Mag., pp. 112–117 (August 1996)Wohlstadter, E., Tai, S., Mikalsen, T., Rouvellou, I., Devanbu, P.: GlueQoS: Middleware to Sweeten Quality-of-Service Policy Interactions. In: ICSE, 26th International Conference on Software Engineering (ICSE 2004) (2004

    Performance Testing of Distributed Component Architectures

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    Performance characteristics, such as response time, throughput andscalability, are key quality attributes of distributed applications. Current practice,however, rarely applies systematic techniques to evaluate performance characteristics.We argue that evaluation of performance is particularly crucial in early developmentstages, when important architectural choices are made. At first glance, thiscontradicts the use of testing techniques, which are usually applied towards the endof a project. In this chapter, we assume that many distributed systems are builtwith middleware technologies, such as the Java 2 Enterprise Edition (J2EE) or theCommon Object Request Broker Architecture (CORBA). These provide servicesand facilities whose implementations are available when architectures are defined.We also note that it is the middleware functionality, such as transaction and persistenceservices, remote communication primitives and threading policy primitives,that dominates distributed system performance. Drawing on these observations, thischapter presents a novel approach to performance testing of distributed applications.We propose to derive application-specific test cases from architecture designs so thatthe performance of a distributed application can be tested based on the middlewaresoftware at early stages of a development process. We report empirical results thatsupport the viability of the approach

    Quality-aware model-driven service engineering

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    Service engineering and service-oriented architecture as an integration and platform technology is a recent approach to software systems integration. Quality aspects ranging from interoperability to maintainability to performance are of central importance for the integration of heterogeneous, distributed service-based systems. Architecture models can substantially influence quality attributes of the implemented software systems. Besides the benefits of explicit architectures on maintainability and reuse, architectural constraints such as styles, reference architectures and architectural patterns can influence observable software properties such as performance. Empirical performance evaluation is a process of measuring and evaluating the performance of implemented software. We present an approach for addressing the quality of services and service-based systems at the model-level in the context of model-driven service engineering. The focus on architecture-level models is a consequence of the black-box character of services
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