Confluence

The ARINC-653 standard, dictating the use of time and space partitioning in real-time avionics systems, has been widely embraced by the industry. We present the design of real-time file system (RTFS), a file system that complies with the ARINC-653 standard and the emerging standard for a file system for ARINC-653. RTFS provides realtime accesses to data stored on a variety of mass storage device. In addition to an interface complying with emerging standard, RTFS provides an application interface that complies with a subset of the POSIX standard. RTFS is implemented as a normal ARINC-653 partition. Task partitions communicate their file operation requests to RTFS via queuing ports; such ports are also used to deliver the responses from RTFS to the task partitions. The temporal behavior of RTFS is predictable and the response times for file operations are bounded. The design of RTFS handles a mix of hard and soft real-time file access requests. RTFS implements metadata journaling using on-board non-volatile memory devices to provide fast file updates and fast file system recovery on faults. Finally, RTFS includes facilities to support network-centric operations and a set of design and maintenance tools. This paper overviews the design of RTFS and describes the realization of the many unique features of RTFS.

Organizing documents in the file system is one of the most tedious and thorny tasks for most computer users. Taxonomies based on hand made directory hierarchies still remain the only possible alternative for most small and medium enterprises, public administrations and individual users. However, both the limitations of the hierarchical organization of file systems and the difficulty of maintaining the coherence within the taxonomy have raised the need for more scalable and effective approaches.Desktop searching applications provide proprietary interfaces that enable content-based searching at the cost of having no control on the indexing and ranking of results. Semantic file systems, instead, leave users the freedom to manage the taxonomy according to their specific needs, but lose the standard file system features.In this paper we describe GFS (graph-based file system) a new hybrid file system that extends the standard hierarchical organization of files with semantic features. GFS allows the user to nest semantic spaces inside the directory hierarchy leaving unaltered system folders. Semantic spaces allow customized file tagging and leverage on browsing to guide file searching.Since GFS does not change the low-level interface to interact with file systems, users can continue to use their favorite file managers to interact with it. Moreover, no changes are required to integrate the semantic features in proprietary software.

Fault-tolerance is very important in cluster computing. Many famous cluster-computing systems have implemented fault-tolerance by using checkpoint/restart mechanism. But existent checkpointing algorithms can not restore the states of a file system when roll-backing the running of a program, so there are many restrictions on file accesses in existent fault-tolerance systems. SCR algorithm, an algorithm based on atomic operation and consistent schedule, which can restore the states of file systems, is present in this paper. In SCR algorithm, system calls on file sytems are classified into idempotent operations and non-idempotent operations. A non-idempotent operation modifies a file system's states, and an idempotent operation does not. SCR algorithm dynamically follows the tracks of a program's running, logs each non-idempotent operation used by the program and the information that can restore the operation in disks. When checkpointing roll-backing the program, SCR algorithm will revert the file system states to the last checkpoint time. By using SCR algorithm, users are allowed to use any file operation in their programs.

Accessing large volumes of data presents a significant challenge when finding the best strategies to manage the data efficiently. Deep learning applications require the processing of massive amounts of data, which implies a considerable access Input/Output (I/O) load on computer systems. During training, interaction with the I/O system intensifies as files are continuously accessed to read data sets. This persistent access could overload the file system, which, in turn, adversely impacts application performance and efficient storage system utilization. Several factors influence the I/O of these applications, and one of the most relevant is the variety of file formats in which datasets can be stored. The choice of file format depends on the use case, as each format defines how information is stored. Some file formats have features that promote efficient access to datasets during the training phase, which can improve the performance of deep learning applications. Likewise, it is also important that the format adapts to the context, in this case, to an HPC system with a parallel file system. We will propose an image preprocessing method for cases where performance improves with parallel file access. This method will transform image data sets from their original JPEG format to the more efficient HDF5 format. Thus, our research will focus on the importance of understanding the mode of data access, spatial and temporal patterns, and the level of parallelism in file access to determine whether it is advisable to change the storage format.

PurposeThis aim of this article is to propose a technical solution for digital libraries to establish the information needs ontology based on a comprehensive understanding of personalized user information needs and offer an information push service by really simple syndication (RSS) in a ubiquitous computing environment.Design/methodology/approachFirst, the authors formalize an ontology model applicable to the ubiquitous computing environment to describe user information needs comprehensively. The information needs related to the user's research activities are regarded as the ontology, which is described with web ontology language (OWL), and thus an ontology knowledgebase is established. Second, in light of the user's explicit information needs, the digital library finds the hidden information needs from the ontology knowledgebase, and also extracts the information resources required by the user from the corresponding database and then pushes them to the user by means of RSS. Finally, users can browse through a man‐machine interface to access the information.FindingsAfter these steps, an RSS information push service architecture is established based on the user information needs ontology, providing the users with dynamic, personalized and proactive information services.Originality/valueThe innovation of this research lies in the fact that the architecture that is put forward is helpful to improve the accuracy and integrity of information push service of digital library, and is also beneficial for the research on u‐library.

Cultural ecosystem services, a complex interplay between humans and landscapes, significantly influence identity, well-being, and social connections. These services, provided through natural and cultural landscapes, can be better understood through spatial data. Using geotagged photos from Flickr, this study delves into user behavior and preferences in Denizli, Türkiye. The aim is to enrich sustainable landscape management by mapping temporal and spatial changes in visitor patterns. The spatial distribution patterns revealed that user activities are predominantly scattered around the city center, historical sites, cultural hubs, and facilities-equipped recreational places. The findings unveiled a concentration in the northwest region in terms of cultural heritage, aesthetic, and recreational values. The period when visitors shared the most photos was between July and October. The study's originality lies in its unique approach to mapping visitor-preferred hotspots and landscape values at the provincial scale, identifying previously unmentioned locations such as Maymun Mountain and the Dodurgalar district. The research underscores the importance of integrating natural and cultural landscape values into urban management and ensuring coordinated efforts to maintain the uniqueness of cities. The practical implications of this study are significant, as they provide valuable insights for urban planners and policymakers interested in sustainable landscape management. Despite the methodological constraints of geotagged social media data, it remains a more time and cost-effective tool. It provides abundant and up-to-date information on user preferences and movements, enabling analysis of spatial and temporal patterns.

Chapter 6 - Mac OS X Systems and Artifacts

Poe in Cyberspace: The “Mobile-Friendly” Sites

Smart environments possess devices that collaborate to help the user non-intrusively. One possible aid smart environment offer is to anticipate user's tasks and perform them on his/her behalf or facilitate the action completion. In this paper, we propose a framework that predicts user's actions by learning his/her behavior when interacting with the smart environment. We prepare the datasets and train a predictor that is responsible to decide whether a target transducer value should be changed or not. Our solution achieves a significant improvement for all target transducers studied and most combinations of parameters yields better results than the base case.

Many people use multiple online and social computing platforms, and choose to share varying amounts of personal information about themselves depending on the context and type of site. For example, people may be willing to share personally-identifiable details (including their real name and date of birth) on a site like Facebook, but may withhold their identity on a dating site that may be widely viewed by strangers. We study the extent to which subtle correlations in a user's activity patterns across different sites may be used to infer that two accounts correspond to the same person. We study a variety of features, including similarity of temporal access patterns, textual content, geo-tags, and social connections, finding that even very weak signals yield surprisingly accurate de-anonymization results.

Presenting scenarios, or user tasks, in the form of storyboards is a common technique in the field of HCI. A storyboarding approach, called SVSb ('simple and visual storyboards'), is proposed. The aim is to create storyboards that are simple and easy to construct and modify, but still communicative and descriptive enough. The storyboards include elements such as context, user, user goals, plans, evaluation, user actions and system events. The rationale of SVSb and experiences on using the approach in a case project are described.

We demonstrate that high-level file system events exhibit self-similar behaviour, but only for short-term time scales of approximately under a day. We do so through the analysis of four sets of traces that span time scales of milliseconds through months, and that differ in the trace collection method, the filesystems being traced, and the chronological times of the tracing. Two sets of detailed, short-term file system trace data are analyzed; both are shown to have self-similar like behaviour, with consistent Hurst parameters (a measure of self-similarity) for all file system traffic as well as individual classes of file system events. Long-term file system trace data is then analyzed, and we discover that the traces' high variability and self-similar behaviour does not persist across time scales of days, weeks, and months. Using the short-term trace data, we show that sources of file system traffic exhibit ON/OFF source behaviour, which is characterized by highly variably lengthed bursts of activity, followed by similarly variably lengthed periods of inactivity. This ON/OFF behaviour is used to motivate a simple technique for synthesizing a stream of events that exhibit the same self-similar short-term behaviour as was observed in the file system traces.

Recent research has demonstrated the potential benefits of building storage arrays that understand the file systems above them. Such disk systems use knowledge of file system structures and operations to improve performance, availability, and even security in ways that are precluded in a traditional storage system architecture.In this paper, we study the applicability of semantically smart disk technology underneath database management systems. For three case studies, we analyze the differences when building database-aware storage. We find that semantically-smart disk systems can be successfully applied underneath a database, but that new techniques, such as log snooping and explicit access statistics, are needed.

To help designers and authors understand users' intentions and work practices for synchronous business communications in a systematic way, we used ethnographic and task-analytic techniques to collect, analyze and classify evidence of the activities of potential users as they conducted their work lives. The interactions we observed among our users took place through a variety of modalities. We found eight categories of tasks for the collaborative or interactive work in which our subjects engaged. Based on these data, we were able to classify roles of potential users of synchronous business communications software into a set of archetypes that characterize their use: Thinkers, Producers, Authors, Networkers and Diplomats. Issues raised by our work include questions about the nature of user archetypes, user tasks, and their modalities.

The ever-increasing gap in performance between CPU/memory technologies and the I/O subsystem (disks, I/O buses) in modern workstations has exacerbated the I/O bottlenecks inherent in applications that access large disk resident data sets. A common technique to alleviate the I/O bottlenecks on clusters of workstations, is the use of parallel file systems. One such parallel file system is the parallel virtual file system (PVFS), which is a freely available tool to achieve high-performance I/O on Linux-based clusters. Here, we describe the performance and scalability of the UNIX I/O interface to PVFS. To illustrate the performance, we present experimental results using Bonnie++, a commonly used file system benchmark to test file system throughput; a synthetic parallel I/O application for calculating aggregate read and write bandwidths; and a synthetic benchmark which calculates the time taken to untar the Linux kernel source tree to measure performance of a large number of small file operations. We obtained aggregate read and write bandwidths as high as 550 MB/s with a Myrinet-based network and 160MB/s with fast Ethernet.