Design guidance using simulation-based Bayesian Belief Networks

In our work, the task of complex computer-based system design optimization involves exploration of a number of possible candidate designs matching the optimisation criteria. However, the process by which the possible candidate designs are generated and rated is fundamental to an optimal outcome. It is dependent upon the set of system characteristics deemed relevant by the designer given the systems requirements. We propose a method which is aimed at providing the designer with guidance based upon description of the possible causal relationships between various system characteristics and qualities. This guidance information is obtained by employing principles of multiparadigm simulation to generate a set of data which is then processed by an algorithm to generate a Bayesian Belief Network representation of causalities present in the source system. Furthermore, we address the issues and tools associated with application of the proposed method by presenting a detailed simulation and network generation effort undertaken as part of a significant industrial case study. © 2008 IEEE

Architectural optimisation guidance of complex-based systems

University of Technology, Sydney. Faculty of Engineering and Information Technology.NO FULL TEXT AVAILABLE. Access is restricted indefinitely. The hardcopy may be available for consultation at the UTS Library.NO FULL TEXT AVAILABLE. Access is restricted indefinitely. ----- Recent years have seen an increase in the number of application domains taking advantage of computer-based systems. With the ubiquity of use for these types of systems came an associated increase in their complexity, both in terms of compositional features and interactions with the operational environment. As a result, in many situations the non-functional qualities of systems play a major role in the success of the endeavours these systems are built to support. Consequently, the system designers need to engage in optimisation, which involves exploration of options for creation of candidate designs that better match the goals and constraints imposed by the system environment. To be successful, the designer must have a good understanding of factors and criteria that influence the system qualities and be able to manage the trade-offs and entanglements which may arise when multiple non-functional qualities are linked to a single architectural feature or design decision. The research presented in this thesis draws upon existing research to formulate a framework capable of supporting this type of optimisation and then extends it by proposing a mechanism for guiding the designer in this activity. To this end, the method aims to produce a description of the possible causal relationships between the compositional characteristics of a given system and the levels of qualities it attains. The mechanism relies on principles of multi-paradigm simulation to generate a set of data which is then processed by an algorithm to extract a Bayesian Belief Network representation of causalities present in the source system. It is recognised that the advantages associated with obtaining causal information using the proposed guidance method could be undone if the process of its application in realistic settings is too complicated and time consuming. With this in mind, a design study was conducted to assess the practicality of applying the steps necessary to obtain guidance information in the context of a real design problem. The results of this investigation has shown that the method can produce a depiction of causalities useful in identification of design change options most likely to advance the non-functional qualities of the system

Practical application of formal methods for specification and analysis of software architecture

With the ever-growing pace of technological advancement, computer software is required to become increasingly complex to meet the demands of today's leading edge technologies, and their applications. However, fulfilling this requirement creates new, previously unknown, problems pertaining to non-functional properties of software. Specifically, as the software complexity escalates, it becomes increasingly difficult to scale the software in order to cope with the sometimes overwhelming demand created by system growth. It is therefore essential to have processes for addressing the issues associated with scalability that arise due to the complexity in software systems. In this paper we describe an approach aimed at fulfilling the need for such processes. A combination of Object-Z and temporal logic is used to create an architectural description open to further analysis. We also demonstrate thepracticality of this methodology within the context of the Coordinated Adaptive Traffic System (CATS). © 2005 IEEE

Application of Bayesian networks to architectural optimisation

The field of optimisation covers a great multitude of principles, methods and frameworks aimed at maximisation of an objective under constraints. However, the classical optimisation can not be easily applied in the context of computer-based systems architecture as there is not enough knowledge concerning the dependencies between non-functional qualities of the system. Out approach is based on the simulation optimisation methodology where the system simulation is first created to assess the current state of the design with respect to the objectives. The results of the simulation are used to construct a Bayesian Belief Network which effectively becomes a base for an objective function and serves as the main source of the decision support pertaining to the guidance of the optimisation process. The potential effects of each proposed change or combination of changes is then examined by updating and re-evaluating the system simulation. © 2007 IEEE

An autonomic open marketplace for inter-cloud service management

The rise of utility in cloud computing and telecommunications has introduced greater complexity in the provisioning and performance management of remote services. We propose extended management strategies for this complexity. Our overall aim is for the management to accept responsibility for the complex service in an open marketplace. Responsibility is, firstly, defined by aiming to cover the totality of modern complex services, managing both the connectivity and virtual infrastructure. Secondly, responsibility is further defined as managing risk and resilience in the provisioning and operation of the complex service. With these aims, we are working towards a bundled service provider agent architecture, which can negotiate on the open service market. This approach aims to also optimise the utilisation of the providers infrastructure while reducing the risk of failure to users through total service management. We present the specification, design and simulation of the bundled service agents in a marketplace environment. © 2011 IEEE

CARMA: Complete autonomous responsible management agents for telecommunications and inter-cloud services

The continuing rise in telecommunication and cloud services usage is matched by an increased complexity in maintaining adequate performance management. To combat this complexity, researchers and telecommunication companies are exploring a variety of management strategies to leverage their individual infrastructures to provide better performance and increased utilisation. We extend these strategies by addressing the complexities that arise through the interaction of multiple telecommunication and cloud providers when providing a modern complex service. Our overall aim is for the management to accept responsibility for the complex service in an open marketplace. Responsibility is, firstly, defined by aiming to cover the totality of modern complex services, managing both the connectivity and virtual infrastructure. Secondly, responsibility is defined as managing risk and resilience in the provisioning and operation of the complex service. With these aims, we are working towards a bundled service provider agent architecture, which can negotiate on the open service market. This approach aims to also optimise the utilisation of the providers infrastructure while reducing the risk of failure to users through total service management. We present the specification, design and simulation of the Complete Autonomous Responsible Management Agents (CARMA) in a marketplace environment. © 2012 IEEE

Heuristic-based architecture generation for complex computer system optimisation

Having come of age in the last decade, the use of architecture to describe complex systems, especially in software, is now maturing. With our current ability to describe, represent, analyse and evaluate architectures comes the next logical step in our application of architecture to system design and optimisation. Driven by the increasing scale and complexity of modern systems, the designers have been forced to find new ways of managing the difficult and complex task of balancing the quality trade-offs inherent in all architectures. Architecture-based optimisation has the potential to not only provide designers with a practical method for approaching this task, but also to provide a generic mechanism for increasing the overall quality of system design. In this paper we explore the issues that surround the development of architectural optimisation and present, an example of heuristic-based optimisation of a system with respect to concrete goals. © 2005 IEEE

An autonomic open marketplace for service management and resilience

Expansion in telecommunications services, such as triple play and unified communications, introduces complexity that adversely affects service and network provisioning, especially in terms of provisioning times and the risk of delivery (failure) of new services. We envision a marketplace in which all manner of complex services will be provisioned, and their performance managed, especially against poor performance. The first phase of our work is a focus on the architecture, negotiation and management, which will lead to effective specification of network management requirements. We are working towards a bundled service agent architecture, which can negotiate on an open single service market, and which will eventually help to optimise the utilisation of the providers networks while reducing the risk of failure to users. Our work to date has been on the specification, behaviour, service definition and simulation of service agents for bundled service delivery. © 2011 IFIP