On the Use of Queueing Petri Nets for Modeling and Performance Analysis of Distributed Systems

Predictive performance models are used increasingly throughout the phases of the software engineering lifecycle of distributed systems. However, as systems grow in size and complex-ity, building models that accurately capture the different aspects of their behavior becomes a more and more challenging task. The challenge stems from the limited model expressivenes

A Queueing Network Model for Performance Prediction of Apache Cassandra

NoSQL databases such as Apache Cassandra have attracted large interest in recent years thanks to their high availability, scalability, flexibility and low latency. Still there is limited research work on performance engineering methods for NoSQL databases, which yet are needed since these systems are highly distributed and thus can incur significant cost/performance trade-offs. To address this need, we propose a novel queueing network model for the Cassandra NoSQL database aimed at supporting resource provisioning. The model defines explicitly key configuration parameters of Cassandra such as consistency levels and replication factor, allowing engineers to compare alternative system setups. Experimental results based on the YCSB benchmark indicate that, with a small amount of training for the estimation of its input param- eters, the proposed model achieves good predictive accuracy across different loads and consistency levels. The average performance errors of the model compared to the real results are between 6% and 10%. We also demonstrate the applicability of our model to other NoSQL databases and other possible utilisation of it

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

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

Parameter dependencies for reusable performance specifications of software components

To avoid design-related per­for­mance problems, model-driven performance prediction methods analyse the response times, throughputs, and re­source utilizations of software architectures before and during implementation. This thesis proposes new modeling languages and according model transformations, which allow a reusable description of usage profile dependencies to the performance of software components. Predictions based on this new methods can support performance-related design decisions

Performance by Unified Model Analysis (PUMA)

Evaluation of non-functional properties of a design (such as performance, dependability, security, etc.) can be enabled by design annotations specific to the property to be evaluated. Performance properties, for instance, can be annotated on UML designs by using the UML Profile for Schedulability, Performance and Time (SPT) . However the communication between the design description in UML and the tools used for non-functional properties evaluation requires support, particularly for performance where there are many alternative performance analysis tools that might be applied. This paper describes a tool architecture called PUMA, which provides a unified interface between different kinds of design information and different kinds of performance models, for example Markov models, stochastic Petri nets and process algebras, queues and layered queues. The paper concentrates on the creation of performance models. The unified interface of PUMA is centered on an intermediate model called Core Scenario Model (CSM), which is extracted from the annotated design model. Experience shows that CSM is also necessary for cleaning and auditing the design information, and providing default interpretations in case it is incomplete, before creating a performance model

Performance Modeling of Database Systems: a Survey, Journal of Telecommunications and Information Technology, 2018, nr 4

This paper presents a systematic survey of the existing database system performance evaluation models based on the queueing theory. The continuous evolution of the methodologies developed is classified according to the mathematical modeling language used. This survey covers formal models – from queueing systems and queueing networks to queueing Petri nets. Some fundamentals of the queueing system theory are presented and queueing system models are classified according to service time distribution. The paper introduces queueing networks and considers several classification criteria applicable to such models. This survey distinguishes methodologies, which evaluate database performance at the integrated system level. Finally, queueing Petri nets are introduced, which combine modeling power of queueing networks and Petri nets. Two performance models within this formalism are investigated. We find that an insufficient amount of research effort is directed into the area of NoSQL data stores. Vast majority of models developed focus on traditional relational models. These models should be adapted to evaluate performance of non-relational data stores

Modelling parallel database management systems for performance prediction

Abstract unavailable please refer to PD

NetMod: A Design Tool for Large-Scale Heterogeneous Campus Networks

The Network Modeling Tool (NetMod) uses simple analytical models to provide the designers of large interconnected local area networks with an in-depth analysis of the potential performance of these systems. This tool can be used in either a university, industrial, or governmental campus networking environment consisting of thousands of computer sites. NetMod is implemented with a combination of the easy-to-use Macintosh software packages HyperCard and Excel. The objectives of NetMod, the analytical models, and the user interface are described in detail along with its application to an actual campus-wide network.http://deepblue.lib.umich.edu/bitstream/2027.42/107971/1/citi-tr-90-1.pd