Adaptive file system consistency for unreliable mobile computing environments

The framework presented in the paper identifies the promises and pitfalls of Artificial Intelligence (AI) and End-User Development (EUD) approaches by focusing on two basic system components: (1) adaptive systems (grounded in AI) that change their behavior automatically driven by context-aware mechanisms including models of their users and specific task contexts, and (2) adaptable systems (grounded in EUD) that can be adjusted, modified, and extended by their users in order to capture unforeseen and important emergent user needs and aspects of problems. Grounded in an analysis of design trade-offs between the two approaches, arguments, and examples for creating a desirable symbiosis between adaptive and adaptable systems are described and design guidelines for future socio-technical environments are explored contributing to the development of theoretical concepts for the future of EUD.

It is widely known that, for most computer applications, their users and contexts of usage are quite heterogeneous and change in time. A variability analysis approach was developed to bridge the gap between requirements engineering and human-computer interaction can help identify these variations and design flexible, adaptable and adaptive solutions that accommodate them at interaction time, i.e., during system usage. The core assumption of the approach is that an in-depth exploration of how user goals can be formulated into diverse user requests expressed in a linguistic structure using cases, designers will be better equipped to create solutions that cope with variations during user-system interaction. This paper shows how a set of adaptation-related questions and related interactive solutions may help to bridge the problem and solution spaces of flexible, adaptable and adaptive systems.

HTTP Video streaming has become a strong candidate for video transmission on the Internet thanks to the abundance of web infrastructure. With the recent standardization of the new MPEG Dynamic Adaptive Streaming over HTTP (DASH), the flexibility and implantation of adaptive video systems has increased due to the fact that DASH can operate on a conventional web infrastructure. In this paper we propose an estimation and adaptation system for DASH. The proposed adaptive algorithm is based on client buffer threshold and smooth throughput measures (based on the throughput of previous segments). Before DASH, the standard of Scalable Video Coding (SVC) also arose from the idea of adaptation. Both systems (adaptive system based on SVC and the proposed system for DASH) are compared in terms of Video Quality (VQ) metrics. The results show that the proposed system reacts properly to changes in the network capacity, while maintaining a minimum level of segments in the buffer. The user-perceived quality is better than in the SVC-based adaptive system although the generated traffic is higher.

Two experiments are presented examining adaptive and adaptable methods for invoking automation. Empirical investigations of adaptive automation have focused on methods used to invoke automation or on automation-related performance implications. However, no research has addressed whether performance benefits associated with brain-based systems exceed those in which users have control over task allocations. Participants performed monitoring and resource management tasks as well as a tracking task that shifted between automatic and manual modes. In the first experiment, participants worked with an adaptive system that used their electroencephalographic signals to switch the tracking task between automatic and manual modes. Participants were also divided between high- and low-reliability conditions for the system-monitoring task as well as high- and low-complacency potential. For the second experiment, participants operated an adaptable system that gave them manual control over task allocations. Results indicated increased situation awareness (SA) of gauge instrument settings for individuals high in complacency potential using the adaptive system. In addition, participants who had control over automation performed more poorly on the resource management task and reported higher levels of workload. A comparison between systems also revealed enhanced SA of gauge instrument settings and decreased workload in the adaptive condition. The present results suggest that brain-based adaptive automation systems may enhance perceptual level SA while reducing mental workload relative to systems requiring user-initiated control. Potential applications include automated systems for which operator monitoring performance and high-workload conditions are of concern.

A system able to adapt to different user characteristics may increase user's learning outcome and advance her/his personal learning experience. This paper reports on research identifying and appraising user personal differences employed in user modelling for adaptive educational systems. A preliminary set of individual characteristics relevant for adaptation is proposed, along with a framework for their categorization. The framework is derived on the basis of empirical studies and survey papers reviewing the usage of these variables in adaptive and adaptable systems. Each variable is addressed from the perspective of its definition, implementation in existing systems and relevance for adaptation. Methods for variable detection and quantification are discussed as well. Suggested framework represents authors' perspective of the state-of-the-art in analyzing user individual differences and adds to the body of knowledge related to the user analysis as an essential part of an adaptive system development process.

Background. This study aimed to compare the cyclic fatigue resistance of ProTaper Next, Hyflex CM, 2Shape, and TF-Adaptive nickel-titanium endodontic file systems with various alloy properties and production methods and investigate the fractured cross-sectional surface of files due to cyclic fatigue by scanning electron microscopy (SEM). Methods. A total of 120 instruments were used (n=30). For standardization, #25/.06 apical diameter and taper angle were selected for each file system. The experiment of files was subjected to a static cyclic fatigue model. The time for files’ failure was recorded with a digital chronometer and multiplied by the rotation speed to calculate the number of cycles. Kolmogorov-Smirnov, one-way ANOVA, and post hoc Bonferroni analysis were used for statistical analysis. Statistical significance was set at P < 0.05. Results. The number of cycles for the failure of files was compared between the groups, and significant differences were found (P < 0.05). The number of cycles for instrument failure was recorded from the highest to the lowest as follows: Hyflex CM, TF-Adaptive, ProTaper Next, and 2Shape. Conclusion. The files were fractured at different average numbers of cycles in an artificial canal in all the groups. The Hyflex CM demonstrated better cyclic fatigue resistance than TF Adaptive, ProTaper Next, and 2Shape file systems. Factors such as production patterns, alloy properties, and the phase in which the files were produced might affect the lifespan of file systems.

Most modern file systems provide journaling method instead of traditional file system check routine for fast recovery and consistency guarantee from unexpected crashes. For clustered file systems with shared storage, to improve the performance of journaling, each node gets its own journal space and each journal can be on its own disk for greater parallelism. After a failure, file system consistency is restored quickly by simply re-applying all updates recorded in the failed node's journal. However, for file system operations involving multiple nodes, this method may not be efficient enough as lock mechanism has to be employed in most cases, which may cause poorer performance and more recovery time. By introducing specific journal storage to record the transactions involving multiple nodes, an enhanced lock-free journaling method is presented in this paper, which can improve the performance of journaling operations involving multiple nodes, and then shortens recovery time from crashes. A Linux-based concept-proofing implementation has been applied in self-developed clustered file system.

The two concepts of universal access and augmented cognition have both contributed significantly to providing the intended users of modern information and communication technology with the necessary resources to achieve enhanced interaction and performance. The two concepts share a number of important features including; the improvement of user performance, the use of concepts from cognitive psychology, a consideration of user modelling, a user sensitive approach, support for customisation, personalisation, adaptation and adaptive systems. They differentially emphasise; short term and long term demands, ambient intelligence, ubiquitous computing, people with disabilities, the Information Society and social skills. Since the present research programme (CIRCUA) is focussed upon the design and evaluation of universally accessible systems within a vocational context, the concepts of universal access and augmented are both very relevant, though both need to draw more upon the concept of social intelligence if they to tackle key issues of the Information Society.

A global and parallel file system for grids

Users rarely consider running network file systems over slow or wide-area networks, as the performance would be unacceptable and the bandwidth consumption too high. Nonetheless, efficient remote file access would often be desirable over such networks---particularly when high latency makes remote login sessions unresponsive. Rather than run interactive programs such as editors remotely, users could run the programs locally and manipulate remote files through the file system. To do so, however, would require a network file system that consumes less bandwidth than most current file systems.This paper presents LBFS, a network file system designed for low-bandwidth networks. LBFS exploits similarities between files or versions of the same file to save bandwidth. It avoids sending data over the network when the same data can already be found in the server's file system or the client's cache. Using this technique in conjunction with conventional compression and caching, LBFS consumes over an order of magnitude less bandwidth than traditional network file systems on common workloads.

Most of today's applications are built on a micro-service architecture, where one large application is divided into several differently functional parts. Each part is packaged in an isolated container with its own file system, process space and IP address. Contemporary container management tools implement only the simplest strategies for placing containers in cluster systems. In this paper, we propose a method for constructing adaptive containerized infrastructures using machine learning methods. The paper also describes the methodology for designing distributed systems with containers of different types: data-intensive and compute-intensive.

Modeling file system organizations in a local area network environment

The user model is considered the core content of any adaptive system. The process that is most challenging in an adaptation system is the modelling of user data. This paper is focused on creating a user model that can be suitably adapted to advertisement applications. To integrate data from different publicly available sources, a social component has been added to the user model, to support advertisements adaptation. In addition, a straightforward and lightweight user model has been targeted, which should be easy to integrate into any existing system. A tool based on this model is introduced and a study that assesses the effectiveness of it via a trial run of a prototype of the tool with different users is described.

The concept of the vector approximation method for CSI-fed induction motors consists of vector control and the shaping of a stator current wave. Vector approximation means that a desirable space current vector is approximated by two realizable current vectors which have only six directions, and by DC link current control. The main purpose of the vector approximation method is not only to decrease torque ripple but also to control instantaneous torque, which is different from the purpose of the general PWM method. Moreover, a parameter adaptation system containing a magnetic saturation table and a model reference adaptive system (MRAS) has been added to the system, and this system works at any constant flux level and the steady state. The simulation and experimental results show the proposed method bring more precise vector approximation and torque control to induction motor drive systems. >

In factories of the future, the worker and his or her well-being is regarded a crucial part of manufacturing situations. Human factors are recognized as vital to achieve sustainable organizational success. Advances in the area of wearable sensors proclaim that sensing human properties within manufacturing settings is technically feasible. Thereby, sensing human properties, such as the level of comfort or stress, may be used to adapt system behaviour in manufacturing situations. This chapter revisits related work from adaptive systems design addressing triggers for adaptations and impacted dimensions. The related work can be considered as design space for developers of S-BPM-based adaptive processes. In line with the related work, a laboratory setting at the Johannes Kepler University Linz has been designed and utilized for testing sensor-based process behaviour and control. Essential findings are described with respect to system architectures and S-BPM process design. The chapter concludes with relating modelling adaptive to human-aware S-BPM processes on a concept layer, and future work.