QoS and energy management with Petri nets: A self-adaptive framework

Energy use is becoming a key design consideration in computing infrastructures and services. In this paper we focus on service-based applications and we propose an adaptation framework that can be used to reduce power consumption according to the observed workload. The adaptation guarantees a trade-off between energy consumption and system performance. The approach is based on the principle of proportional energy consumption obtained by scaling down energy for unused resources, considering both the number of servers switched on and their operating frequencies. Stochastic Petri nets are proposed for the modeling of the framework concerns, their analyses give results about the trade-offs. The application of the approach to a simple case study shows its usefulness and practical applicability. Finally, different types of workloads are analyzed with validation purposes.     

Transformation challenges: from software models to performance models

A software model can be analysed for non-functional requirements by extending it with suitable annotations and transforming it into analysis models for the corresponding non-functional properties. For quantitative performance evaluation, suitable annotations are standardized in the “UML Profile for Modeling and Analysis of Real-Time Embedded systems” (MARTE) and its predecessor, the “UML Profile for Schedulability, Performance and Time”. A range of different performance model types (such as queueing networks, Petri nets, stochastic process algebra) may be used for analysis. In this work, an intermediate “Core Scenario Model” (CSM) is used in the transformation from the source software model to the target performance model. CSM focuses on how the system behaviour uses the system resources. The semantic gap between the software model and the performance model must be bridged by (1) information supplied in the performance annotations, (2) in interpretation of the global behaviour expressed in the CSM and (3) in the process of constructing the performance model. Flexibility is required for specifying sets of alternative cases, for choosing where this bridging information is supplied, and for overriding values. It is also essential to be able to trace the source of values used in a particular performance estimate. The performance model in turn can be used to verify responsiveness and scalability of a software system, to discover architectural limitations at an early stage of development, and to develop efficient performance tests. This paper describes how the semantic gap between software models in UML+MARTE and performance models (based on queueing or Petri nets) can be bridged using transformations based on CSMs, and how the transformation challenges are addressed.     

Dependability analysis of DES based on MARTE and UML state machines models

UML (Unified Modeling Language) is a standard design notation which offers the state machines diagram to specify reactive software systems. The “Modeling and Analysis of Real-Time and Embedded systems” profile (MARTE) enables UML with capabilities for performance analysis. MARTE has been specialized in a “Dependability Analysis and Modeling” profile (DAM), then providing UML with dependability assets. In this work, we propose an approach for the automatic transformation of UML-DAM models into Deterministic and Stochastic Petri nets and the subsequent dependability analysis.     

A systematic approach for performance assessment using process mining

Software performance engineering is a mature field that offers methods to assess system performance. Process mining is a promising research field applied to gain insight on system processes. The interplay of these two fields opens promising applications in the industry. In this work, we report our experience applying a methodology, based on process mining techniques, for the performance assessment of a commercial data-intensive software application. The methodology has successfully assessed the scalability of future versions of this system. Moreover, it has identified bottlenecks components and replication needs for fulfilling business rules. The system, an integrated port operations management system, has been developed by Prodevelop, a medium-sized software enterprise with high expertise in geospatial technologies. The performance assessment has been carried out by a team composed by practitioners and researchers. Finally, the paper offers a deep discussion on the lessons learned during the experience, that will be useful for practitioners to adopt the methodology and for researcher to find new routes.     

Analysing Internet Software Retrieval Systems: Modeling and Performance Comparison

Nowadays, there exist web sites that allow users to retrieve and install software in an easy way. The performance of these sites may be poor if they are used in wireless networks; the reason is the inadequate use of the net resources that they need. If these kinds of systems are designed using mobile agent technology the previous problem might be avoided. In this paper, we present a comparison between the performance of a software retrieval system especially designed to be used in a wireless network and the performance of a software retrieval system similar to the well-known Tucows.com web site. In order to compare performance, we make use of a software performance process enriched with formal techniques. The process has as important features that it uses UML as a design notation and it uses stochastic Petri nets as formal model. Petri nets provide a formal semantics for the system and a performance model.     

QoS assessment via stochastic analysis

Using a stochastic modeling approach based on the Unified Modeling Language and enriched with annotations that conform to the UML profile for schedulability performance, and time, the authors propose a method for assessing quality of service (QoS) in fault-tolerant (FT) distributed systems. From the UML system specification, they produce a generalized stochastic Petri net (GSPN) performance model for assessing an FT application's QoS via stochastic analysis. The ArgoSPE tool provides support for the proposed technique, helping to automatically produce the GSPN model.     

A dependability profile within MARTE

The importance of assessing software non-functional properties (NFP) beside the functional ones is well accepted in the software engineering community. In particular, dependability is a NFP that should be assessed early in the software life-cycle by evaluating the system behaviour under different fault assumptions. Dependability-specific modeling and analysis techniques include for example Failure Mode and Effect Analysis for qualitative evaluation, stochastic Petri nets for quantitative evaluation, and fault trees for both forms of evaluation. Unified Modeling Language (UML) may be specialized for different domains by using the profile mechanism. For example, the MARTE profile extends UML with concepts for modeling and quantitative analysis of real-time and embedded systems (more specifically, for schedulability and performance analysis). This paper proposes to add to MARTE a profile for dependability analysis and modeling (DAM). A case study of an intrusion-tolerant message service will offer insight on how the MARTE-DAM profile can be used to derive a stochastic Petri net model for performance and dependability assessment.