Observation-Enhanced QoS Analysis of Component-Based Systems

by   Colin Paterson, et al.

We present a new method for the accurate analysis of the quality-of-service (QoS) properties of component-based systems. Our method takes as input a QoS property of interest and a high-level continuous-time Markov chain (CTMC) model of the analysed system, and refines this CTMC based on observations of the execution times of the system components. The refined CTMC can then be analysed with existing probabilistic model checkers to accurately predict the value of the QoS property. The paper describes the theoretical foundation underlying this model refinement, the tool we developed to automate it, and two case studies that apply our QoS analysis method to a service-based system implemented using public web services and to an IT support system at a large university, respectively. Our experiments show that traditional CTMC-based QoS analysis can produce highly inaccurate results and may lead to invalid engineering and business decisions. In contrast, our new method reduced QoS analysis errors by 84.4-89.6 the IT support system, significantly lowering the risk of such invalid decisions.


page 1

page 2

page 3

page 4


Probabilistic Quality of Service aware Service Selection

In software-as-a-service paradigms software systems are no longer monoli...

CAHPHF: Context-Aware Hierarchical QoS Prediction with Hybrid Filtering

With the proliferation of Internet-of-Things and continuous growth in th...

QoS management mechanisms for Enhanced Living Environments in IoT

The Internet of Things (IoT) paradigm is expected to bring ubiquitous in...

Efficient Parametric Model Checking Using Domain Knowledge

We introduce an efficient parametric model checking (ePMC) method for th...

In Search of Lost QoS

The area of quality of service (QoS) in communications networks has been...

Managing Service Level Agreements in Service Oriented Product Lines

Service Oriented Architecture (SOA) and Software Product Line (SPL) have...

Please sign up or login with your details

Forgot password? Click here to reset