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

The Time of the Infant, Parent-Infant Desynchronization and Attachment Disorganization, or How Long Does it Take for a Preventive Action to be Effective?

The classical version of early development by psychoanalysis has been largely challenged by developmental psychology, and particularly by attachment theory. Psychopathology appears to be much more linked with a sequence of events involving interpersonal relationship disorders rather than with intra psychic conflicts, as hypothesised by drive theory. Establishing synchrony between parent and infant is probably one of the major tasks of the first year of life. Attachment theory appears to be the modern paradigm to understand how the several types of answers from caregivers to stressing situations in the infant give way to different emotional and cognitive regulatory strategies, with impact on the effectiveness of the stress buffer systems. This paper presents what we can figure out about what is time to the infant, the importance of synchronization within infant and caregiver, the key concept of attachment disorganization, the concept of sustained social withdrawal as a defence mechanism and an alarm signal when synchronisation fails, and finally the key issue of conditions for effectiveness of early parent- infant preventive intervention.Parent- infant synchrony, Attachment Disorganization, Parenting, infant social withdrawal behaviour, early prevention and intervention

Preliminary specification and design documentation for software components to achieve catallaxy in computational systems

This Report is about the preliminary specifications and design documentation for software components to achieve Catallaxy in computational systems. -- Die Arbeit beschreibt die Spezifikation und das Design von Softwarekomponenten, um das Konzept der Katallaxie in Grid Systemen umzusetzen. Eine Einführung ordnet das Konzept der Katallaxie in bestehende Grid Taxonomien ein und stellt grundlegende Komponenten vor. Anschließend werden diese Komponenten auf ihre Anwendbarkeit in bestehenden Application Layer Netzwerken untersucht.Grid Computing

Ecological autocatalysis:A central principle in ecosystem organization?

Ecosystems comprise flows of energy and materials, structured by organisms and their interactions. Important generalizations have emerged in recent decades about conversions by organisms of energy (metabolic theory of ecology) and materials (ecological stoichiometry). However, these new insights leave a key question about ecosystems inadequately addressed: are there basic organizational principles that explain how the interaction structure among species in ecosystems arises? Here we integrate recent contributions to the understanding of how ecosystem organization emerges through ecological autocatalysis (EA), in which species mutually benefit through self-reinforcing circular interaction structures. We seek to generalize the concept of EA by integrating principles from community and ecosystem ecology. We discuss evidence suggesting that ecological autocatalysis is facilitated by resource competition and natural selection, both central principles in community ecology. Furthermore, we suggest that pre-emptive resource competition by consumers and plant resource diversity drive the emergence of autocatalytic loops at the ecosystem level. Subsequently, we describe how interactions between such autocatalytic loops can explain pattern and processes observed at the ecosystem scale, and summarize efforts to model different aspect of the phenomenon. We conclude that EA is a central principle that forms the backbone of the organization in systems ecology, analogous to autocatalytic loops in systems chemistry.</p

Intelligent and adaptive tutoring for active learning and training environments

Active learning facilitated through interactive and adaptive learning environments differs substantially from traditional instructor-oriented, classroom-based teaching. We present a Web-based e-learning environment that integrates knowledge learning and skills training. How these tools are used most effectively is still an open question. We propose knowledge-level interaction and adaptive feedback and guidance as central features. We discuss these features and evaluate the effectiveness of this Web-based environment, focusing on different aspects of learning behaviour and tool usage. Motivation, acceptance of the approach, learning organisation and actual tool usage are aspects of behaviour that require different evaluation techniques to be used

Tracing Cold War in Post-Modern Management's Hot Issues

Tracing Cold War in post-modern managerial science and ideology one encounters hot issues linking contemporary liberal dogmas and romanticized view of organizational leadership to the dismantling of a welfare state disguised as a liberation of an individual employee, empowerment of an individual consumer and a progressive, liberal and global development of a market/parliament mix. The concept of totalitarianism covers fearful symmetries between three modes of paying the bills for western modernization; liberal, communist and the emergent "egalibertarian"(1), while the ideologies of organisationalism and globalization testify to a search for a post-Cold War mission statement. Messiness of re-engineering the enlargement of the European Union testifies to the hidden injuries of Cold War, not all of them caused by a class and class struggle.empowerment;liberalism;Cold War;hidden costs of modernization;egaliberty;organizationalism;paradigm;romanticized view of leadership;Managerialist ideology;totalitarianism

Evolution in agriculture: the application of evolutionary approaches to the management of biotic interactions in agro-ecosystems

Anthropogenic impacts increasingly drive ecological and evolutionary processes at many spatio-temporal scales, demanding greater capacity to predict and manage their consequences. This is particularly true for agro-ecosystems, which not only comprise a significant proportion of land use, but which also involve conflicting imperatives to expand or intensify production while simultaneously reducing environmental impacts. These imperatives reinforce the likelihood of further major changes in agriculture over the next 30–40 years. Key transformations include genetic technologies as well as changes in land use. The use of evolutionary principles is not new in agriculture (e.g. crop breeding, domestication of animals, management of selection for pest resistance), but given land-use trends and other transformative processes in production landscapes, ecological and evolutionary research in agro-ecosystems must consider such issues in a broader systems context. Here, we focus on biotic interactions involving pests and pathogens as exemplars of situations where integration of agronomic, ecological and evolutionary perspectives has practical value. Although their presence in agro-ecosystems may be new, many traits involved in these associations evolved in natural settings. We advocate the use of predictive frameworks based on evolutionary models as pre-emptive management tools and identify some specific research opportunities to facilitate this. We conclude with a brief discussion of multidisciplinary approaches in applied evolutionary problems

Self-Learning Cloud Controllers: Fuzzy Q-Learning for Knowledge Evolution

Cloud controllers aim at responding to application demands by automatically scaling the compute resources at runtime to meet performance guarantees and minimize resource costs. Existing cloud controllers often resort to scaling strategies that are codified as a set of adaptation rules. However, for a cloud provider, applications running on top of the cloud infrastructure are more or less 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. Yet, in most cases, application developers in turn have limited knowledge of the cloud infrastructure. In this paper, we propose learning adaptation rules during runtime. To this end, we introduce FQL4KE, a self-learning fuzzy cloud controller. In particular, FQL4KE learns and modifies fuzzy rules at runtime. The benefit is that for designing cloud controllers, we do not have to rely solely on precise design-time knowledge, which may be difficult to acquire. FQL4KE empowers users to specify cloud controllers by simply adjusting weights representing priorities in system goals instead of specifying complex adaptation rules. The applicability of FQL4KE has been experimentally assessed as part of the cloud application framework ElasticBench. The experimental results indicate that FQL4KE outperforms our previously developed fuzzy controller without learning mechanisms and the native Azure auto-scaling

Feral Children: Settler Colonialism, Progress, and the Figure of the Child

Settler colonialism is structured in part according to the principle of civilizational progress yet the roots of this doctrine are not well understood. Disparate ideas of progress and practices related to colonial dispossession and domination can be traced back to the Enlightenment, and as far back as ancient Greece, but there remain unexplored logics and continuities. I argue that civilizational progress and settler colonialism are structured according to the opposition between politics governed by reason or faith and the figure of the child as sinful or bestial. Thus, it is not contingent, but rather necessary that justificatory frameworks of European empire and colonialism depict Indigenous peoples as children. To illustrate how the theoretical link between Indigenous peoples and children emerges not as a simple analogy, but rather, as the source of the premodern/modern and savage/civilized binaries, I trace the various historical iterations of the political/childhood opposition through the classical, medieval, enlightenment, and modern eras. I show how the model of civilizational progress from a premodern and savage state of childhood continues to serve as the model for settler colonial exclusion and domination of Indigenous peoples

Learning Rapidly about the Relevance of Visual Cues Requires Conscious Awareness

Humans have been shown capable of performing many cognitive tasks using information of which they are not consciously aware. This raises questions about what role consciousness actually plays in cognition. Here, we explored whether participants can learn cue-target contingencies in an attentional learning task when the cues were presented below the level of conscious awareness, and how this differs from learning about conscious cues. Participants’ manual (Experiment 1) and saccadic (Experiment 2) response speeds were influenced by both conscious and unconscious cues. However, participants were only able to adapt to reversals of the cue-target contingencies (Experiment 1) or changes in the reliability of the cues (Experiment 2) when consciously aware of the cues. Therefore, although visual cues can be processed unconsciously, learning about cues over a few trials requires conscious awareness of them. Finally, we discuss implications for cognitive theories of consciousness