Cloud service localisation

The essence of cloud computing is the provision of software and hardware services to a range of users in dierent locations. The aim of cloud service localisation is to facilitate the internationalisation and localisation of cloud services by allowing their adaption to dierent locales. We address the lingual localisation by providing service-level language translation techniques to adopt services to dierent languages and regulatory localisation by providing standards-based mappings to achieve regulatory compliance with regionally varying laws, standards and regulations. The aim is to support and enforce the explicit modelling of aspects particularly relevant to localisation and runtime support consisting of tools and middleware services to automating the deployment based on models of locales, driven by the two localisation dimensions. We focus here on an ontology-based conceptual information model that integrates locale specication in a coherent way

Fuzzy Self-Learning Controllers for Elasticity Management in Dynamic Cloud Architectures

Cloud controllers support the operation and quality management of dynamic cloud architectures by automatically scaling the compute resources to meet performance guarantees and minimize resource costs. Existing cloud controllers often resort to scaling strategies that are codified as a set of architecture adaptation rules. However, for a cloud provider, deployed application architectures are black-boxes, making it difficult at design time to define optimal or pre-emptive adaptation rules. Thus, the burden of taking adaptation decisions often is delegated to the cloud application. We propose the dynamic learning of adaptation rules for deployed application architectures in the cloud. We introduce FQL4KE, a self-learning fuzzy controller that learns and modifies fuzzy rules at runtime. The benefit is that we do not have to rely solely on precise design-time knowledge, which may be difficult to acquire. FQL4KE empowers users to configure cloud controllers by simply adjusting weights representing priorities for architecture quality instead of defining complex rules. FQL4KE has been experimentally validated using the cloud application framework ElasticBench in Azure and OpenStack. The experimental results demonstrate that FQL4KE outperforms both a fuzzy controller without learning and the native Azure auto-scalin

How multilevel societal learning processes facilitate transformative change: A comparative case study analysis on flood management

Sustainable resources management requires a major transformation of existing resource governance and management systems. These have evolved over a long time under an unsustainable management paradigm, e.g., the transformation from the traditionally prevailing technocratic flood protection toward the holistic integrated flood management approach. We analyzed such transformative changes using three case studies in Europe with a long history of severe flooding: the Hungarian Tisza and the German and Dutch Rhine. A framework based on societal learning and on an evolutionary understanding of societal change was applied to identify drivers and barriers for change. Results confirmed the importance of informal learning and actor networks and their connection to formal policy processes. Enhancing a society's capacity to adapt is a long-term process that evolves over decades, and in this case, was punctuated by disastrous flood events that promoted windows of opportunity for change

A prescriptive approach to qualify and quantify customer value for value-based requirements engineering

Recently, customer-based product development is becoming a popular paradigm. Customer expectations and needs can be identified and transformed into requirements for product design with the help of various methods and tools. However, in many cases, these models fail to focus on the perceived value that is crucial when customers make the decision of purchasing a product. In this paper, a prescriptive approach to support value-based requirements engineering (RE) is proposed, describing the foundations, procedures and initial applications in the context of RE for commercial aircraft. An integrated set of techniques, such as means-ends analysis, part-whole analysis and multi-attribute utility theory is introduced in order to understand customer values in depth and width. Technically, this enables identifying the implicit value, structuring logically collected statements of customer expectations and performing value modelling and simulation. Additionally, it helps to put in place a system to measure customer satisfaction that is derived from the proposed approach. The approach offers significant potential to develop effective value creation strategies for the development of new product

Measurement of the strong coupling alpha_S from the three-jet rate in e+e- - annihilation using JADE data

We present a measurement of the strong coupling alpha_S using the three-jet rate measured with the Durham algorithm in e+e- -annihilation using data of the JADE experiment at centre-of-mass energies between 14 and 44 GeV. Recent theoretical improvements provide predictions of the three-jet rate in e+e- -annihilation at next-to-next-to-leading order. In this paper a measurement of the three-jet rate is used to determine the strong coupling alpha_s from a comparison to next-to-next-to-leading order predictions matched with next-to-leading logarithmic approximations and yields a value for the strong coupling alpha_S(MZ) = 0.1199+- 0.0010 (stat.) +- 0.0021 (exp.) +- 0.0054 (had.) +- 0.0007 (theo.) consistent with the world average.Comment: 27 pages, 8 figure

Managing change toward adaptive water management through social learning

The management of water resources is currently undergoing a paradigm shift toward a more integrated and participatory management style. This paper highlights the need to fully take into account the complexity of the systems to be managed and to give more attention to uncertainties. Achieving this requires adaptive management approaches that can more generally be defined as systematic strategies for improving management policies and practices by learning from the outcomes of previous management actions. This paper describes how the principles of adaptive water management might improve the conceptual and methodological base for sustainable and integrated water management in an uncertain and complex world. Critical debate is structured around four questions: (1) What types of uncertainty need to be taken into account in water management? (2) How does adaptive management account for uncertainty? (3) What are the characteristics of adaptive management regimes? (4) What is the role of social learning in managing change? Major transformation processes are needed because, in many cases, the structural requirements, e.g., adaptive institutions and a flexible technical infrastructure, for adaptive management are not available. In conclusion, we itemize a number of research needs and summarize practical recommendations based on the current state of knowledge

Welfare Workers' Responses to Domestic Violence Cases: The Effects of Training and Worker Characteristics

Copyright 2006 Alliance for Children and FamiliesThis study evaluated a one-day domestic violence training for Temporary Assistance for Needy Families (TANF) workers and analyzed the relationship between worker characteristics and the use of work exemptions. In a post-only evaluation, trained workers reported a greater tendency than untrained workers to refer clients to couples counseling, make a safety plan, and file a report to child protection services. In a pre/post evaluation, workers reported after training that they would be less likely to refer clients to couples counseling, and more likely to ask about the emotional and physical impact of abuse, make a safety plan, and ask about access to weapons. Workers most likely to offer a waiver from work requirements reported a higher likelihood of making referrals for a variety o f services