abstract: The adoption of the Service Oriented Architecture (SOA) as the foundation for developing a new generation of software systems - known as Service Based Software Systems (SBS), poses new challenges in system design. While simulation as a methodology serves a principal role in design, there is a growing recognition that simulation of SBS requires modeling capabilities beyond those that are developed for the traditional distributed software systems. In particular, while different component-based modeling approaches may lend themselves to simulating the logical process flows in Service Oriented Computing (SOC) systems, they are inadequate in terms of supporting SOA-compliant modeling. Furthermore, composite services must satisfy multiple QoS attributes under constrained service reconfigurations and hardware resources. A key desired capability, therefore, is to model and simulate not only the services consistent with SOA concepts and principles, but also the hardware and network components on which services must execute on. In this dissertation, SOC-DEVS - a novel co-design modeling methodology that enables simulation of software and hardware aspects of SBS for early architectural design evaluation is developed. A set of abstractions representing important service characteristics and service relationships are modeled. The proposed software/hardware co-design simulation capability is introduced into the DEVS-Suite simulator. Exemplar simulation models of a communication intensive Voice Communication System and a computation intensive Encryption System are developed and then validated using data from an existing real system. The applicability of the SOC-DEVS methodology is demonstrated in a simulation testbed aimed at facilitating the design & development of SBS. Furthermore, the simulation testbed is extended by integrating an existing prototype monitoring and adaptation system with the simulator to support basic experimentation towards design & development of Adaptive SBS. / Dissertation/Thesis / Ph.D. Computer Science 2011

Marine renewable energy promises to provide a significant contribution to the future electricity supply. It is estimated that 17% of today's UK electricity demand could be generated from wave and tidal sources. The ambition to harvest this resource is in the public interest, as it eases the pressures on energy security, holds the potential to reduce carbon emissions and has the prospect to create a new UK industry sector worth £15 billion. From an engineering perspective, marine energy is one of the least developed renewable energy technologies and has to be regarded as unproven. The reliability of components and devices in the harsh marine environment is one of the main engineering challenges. Reliability assessments and the assurance of acceptable reliability levels are dependant on the adequacy of failure information, which is scantily available for marine energy. This thesis shows that large failure rate uncertainties impede the reliability assessment for wave energy converters and how a suite of experimental, numerical and statistical methods can be applied to improve scarcely available reliability information. The analysis of component load conditions identifies fatigue as failure mode of concern and the fatigue life of mooring lines and marine power cables is quantified in a floating wave energy application. A Bayesian statistical approach and dedicated service-simulation component testing is proposed, and implemented to improve the quality of reliability estimates and to provide relevant data and assurance. The methods presented, along with the results, will assist reliability assessment and design during early development stages, and will inform the prediction of maintenance requirements during operation. Reliable marine energy systems will be the technical enabler for the successful transition of prototype devices to a commercially viable marine energy industry.

在服務資源需求量會隨時間而改變的情況下，系統的服務資源供給對致力於提供高服務品質的資源提供者來說是一個重要的議題。在服務資源可以迅速的部署和解除的假設下，像是以雲端運算為基礎之服務，本研究提供了系統性的估算服務資源方法，本方法之結構是以模擬為基礎並結合了非監督式學習、顧客到達率之估計以及統計技術。首先，本研究將每一日之顧客到達率進行分群運算並將具有類似顧客到達模式的日期分為一群，且每一群之包含日期具備可解釋之代表性；下一階段使用兩階段式的忙碌因子模型去建立每一群的顧客到達率模型，並估計該群的多區間普瓦松分布來做為系統模擬隨機過程所需之參數；最後應用了等候模型理論去設計系統模擬方法，模擬出顧客在系統中到達並接受服務的隨機過程，其結果包含觀察出顧客在系統中的等待時間和排隊長度以及所需之服務資源，並提供在不同的服務策略情形下之表現。 本研究使用了一個來自電力公司客服中心之進線量資料進行本方法之實驗，展示出如何使用本方法建立一個能滿足服務水準要求的服務資源配置策略，也和該公司過去之配置策略進行比較，並提出實質上如何提升服務品質的配置策略之建議。

This thesis focuses on design, modeling and simulation of heterogeneous systems with emphasis on discrete-event systems. It proposes service-oriented simulation architecture where modeling and simulation is treated as a service and establishes a DEVS Meta Language that is intended for implementation of simulation models based on the DEVS formalism. Special M\&S techniques are described and integration of existing simulation tools is discussed as well.