Model checking for cloud autoscaling using WATERS

This thesis investigates the use of formal methods to verify cloud system designs against Service Level Agreements (SLAs), towards providing guarantees under uncertainty. We used WATERS (the Waikato Analysis Toolkit for Events in Reactive Systems), which is a model-checking tool based on discrete event systems. We created models for one aspect of cloud computing, horizontal autoscaling, and used this to verify cloud system designs against an SLA that specifies the maximum request response time. To evaluate the accuracy of the WATERS models, the cloud system designs are simulated on a private Kubernetes cluster, using JMeter to drive the workload. The results from Kubernetes are compared to the verification results from WATERS. A key research goal was to have these match as closely as possible, and to explain the discrepancies between the two. This process is followed for two applications: a default installation of NGINX, a web server with a fast but variable response time, and a hand-written Node.js program enforcing a fixed response time. The results suggest that WATERS can be used to predict potential SLA violations. Lessons learned include that the state space must be constrained to avoid excessive checking times, and we provide a method for doing so. An advantage of our model checking-based technique is that it verifies against all possible patterns of arriving requests (up to a given maximum), which would be impractical to test with a load testing tool such as JMeter. A key difference from existing work is our use non-probabilistic finite state machines, as opposed to probabilistic models which are prevalent in existing research. In addition, we have attempted to model the detail of the autoscaling process (a “white-box” approach), whereas much existing research attempts to find patterns between autoscaling parameters and SLA violation, effectively viewing autoscaling as a black-box process. Future work includes refining the WATERS models to more closely match Kubernetes, and modelling other SLO types. Other methods may also be used to limit the compilation and verification time for the models. This includes attempting different algorithms and perhaps editing the models to reduce the state space

A Novel Method for Adaptive Control of Manufacturing Equipment in Cloud Environments

The ability to adaptively control manufacturing equipment, both in local and distributed environments, is becoming increasingly more important for many manufacturing companies. One important reason for this is that manufacturing companies are facing increasing levels of changes, variations and uncertainty, caused by both internal and external factors, which can negatively impact their performance. Frequently changing consumer requirements and market demands usually lead to variations in manufacturing quantities, product design and shorter product life-cycles. Variations in manufacturing capability and functionality, such as equipment breakdowns, missing/worn/broken tools and delays, also contribute to a high level of uncertainty. The result is unpredictable manufacturing system performance, with an increased number of unforeseen events occurring in these systems. Events which are difficult for traditional planning and control systems to satisfactorily manage. For manufacturing scenarios such as these, the use of real-time manufacturing information and intelligence is necessary to enable manufacturing activities to be performed according to actual manufacturing conditions and requirements, and not according to a pre-determined process plan. Therefore, there is a need for an event-driven control approach to facilitate adaptive decision-making and dynamic control capabilities. Another reason driving the move for adaptive control of manufacturing equipment is the trend of increasing globalization, which forces manufacturing industry to focus on more cost-effective manufacturing systems and collaboration within global supply chains and manufacturing networks. Cloud Manufacturing is evolving as a new manufacturing paradigm to match this trend, enabling the mutually advantageous sharing of resources, knowledge and information between distributed companies and manufacturing units. One of the crucial objectives for Cloud Manufacturing is the coordinated planning, control and execution of discrete manufacturing operations in collaborative and networked environments. Therefore, there is also a need that such an event-driven control approach supports the control of distributed manufacturing equipment. The aim of this research study is to define and verify a novel and comprehensive method for adaptive control of manufacturing equipment in cloud environments. The presented research follows the Design Science Research methodology. From a review of research literature, problems regarding adaptive manufacturing equipment control have been identified. A control approach, building on a structure of event-driven Manufacturing Feature Function Blocks, supported by an Information Framework, has been formulated. The Function Block structure is constructed to generate real-time control instructions, triggered by events from the manufacturing environment. The Information Framework uses the concept of Ontologies and The Semantic Web to enable description and matching of manufacturing resource capabilities and manufacturing task requests in distributed environments, e.g. within Cloud Manufacturing. The suggested control approach has been designed and instantiated, implemented as prototype systems for both local and distributed manufacturing scenarios, in both real and virtual applications. In these systems, event-driven Assembly Feature Function Blocks for adaptive control of robotic assembly tasks have been used to demonstrate the applicability of the control approach. The utility and performance of these prototype systems have been tested, verified and evaluated for different assembly scenarios. The proposed control approach has many promising characteristics for use within both local and distributed environments, such as cloud environments. The biggest advantage compared to traditional control is that the required control is created at run-time according to actual manufacturing conditions. The biggest obstacle for being applicable to its full extent is manufacturing equipment controlled by proprietary control systems, with native control languages. To take the full advantage of the IEC Function Block control approach, controllers which can interface, interpret and execute these Function Blocks directly, are necessary

Committee V.1: Accidental Limit States

Concern for accidental scenarios for ships and offshore structures and for their structural components leading to limit states. Types of accidental scenarios shall include collision, grounding, dropped objects, explosion, and fire. Attention shall be given to hazard identification, accidental loads and nonlinear structural consequences including strength reduction, affecting the probability of failure and related risks. Uncertainties in the use of accidental scenarios for design and analysis shall be highlighted. Consideration shall be given to the practical application of methods and to the development of ISSC guidance for quantitative assessment and management of accidental risks

Not just the right for a wheelchair but the right wheelchair: a multi-site study of the wheelchair public service provision in Belo Horizonte city, Brazil

For decades the care of disabled population in Brazil has been neglected by the government and was provided largely by the charitable institutions. It was as only recently, as in the year 2011 that Brazilian government created the national plan for the rights of the disabled people. The plan articulates policies regarding social inclusion, access to education, accessibility and health care. The last section of the plan includes the provision of wheelchairs free of cost to the Brazilians citizens, who are in need of a wheelchair. It is common knowledge that a wrong wheelchair specification can lead to physical damage for the user and the carer; the abandonment of device, and wastage of time and resources involved in the wheelchair provision. The World Health Organization has propounded several good practices and training material with reference to wheelchair services towards enabling of right wheelchair fit to the user characteristics. Though, there is no evidence that the service provided in Brazil adheres to these guidelines or any other wheelchair service good practice. This research reviews the wheelchair service provision in Belo Horizonte city, Brazil with the aim to understand the functionality of these services in order to provide context-specific interventions and recommendations to improve the design of current services. Herein, three main studies were conducted using a mix of methods: A first exploratory study was conducted to assess the Belo Horizonte assistive technology services and identify a research focus. A second study was conducted to develop an in-depth insight on the understanding of the wheelchair service provided and to collect the necessary information towards creating a context-based and collaborative designed intervention. A third study was conducted to evaluate and improve the proposed interventions. A total of sixty-six interviews were conducted (n=66) with service stakeholders and two hundred and fifty user care observed (n=250) from which ninety-five (n=95) tested the proposed interventions

Investigating the Effect of Drilling Parameters and Mud Rheology for the Flow of Yield Power Law Fluid through Annulus

Fluid flow in the annulus has been the center of numerous studies, whether from the oil industry or academia. This study deals with numerical simulations using computational fluid dynamics technique to investigate the parameters that affect the pressure gradient in the annulus for the flow of Yield Power Law fluids. The study analyses the effect of cutting concentration through volume fraction, flow rate, inclination, eccentricity and rheological properties of drilling fluid on the pressure losses though the annulus. Previous work in the field of study has provided models which aided the industry to better predict hole cleaning efficiency and pressure losses. The benefits of better pressure loss predictions are well documented with potential millions in saving from drilling optimization with the use of modeling. Some of the more advanced studies have included the kinetic theory of granular flow for example to great effect to model hydrodynamics

Volcanic Activity: Processing of Observation and Remote Sensing Data (VAPOR)

The World Bank makes a very clear distinction between disasters and natural phenomena. Natural phenomena are events like volcanic eruptions. A disaster only occurs when the ability of the community to cope with natural phenomenon has been surpassed, causing widespread human, material, economic or environmental losses. By these definitions, volcanic eruptions do not have to lead to disasters. On November 13, 1985, the second most deadly eruption of the twentieth century occurred in Colombia. Within a few hours of the eruption of the Nevado del Ruiz volcano, 23,000 people were dead because no infrastructure existed to respond to such an emergency. Six years later, the 1991 eruption of Mount Pinatubo in the Philippines was the largest volcanic eruption in the 21st century to affect a heavily populated area. Because the volcano was monitored, early warning of the eruption was provided and thousands of lives were saved. Despite these improvements, some communities still face danger from volcanic events and volcano-monitoring systems still require further development. There remain clear gaps in monitoring technologies, in data sharing, and in early warning and hazard tracking systems. A global volcano-monitoring framework such as the VIDA framework can contribute to filling these gaps. VIDA stands for “VAPOR Integrated Data-sharing and Analysis” and is also the Catalan and Spanish word for ‘life’. The ultimate goal for this project is to help save the lives of people threatened by volcanic hazards, while protecting infrastructure and contributing to decision support mechanisms in disaster risk management scenarios