Self-Aware Model-Driven Pervasive Systems

In the Ubiquitous Computing Environment (UCE) context, the successful provision of user-required services necessitates the collaboration of various system components, encompassing hardware parts, software components, and network connections. The utilization of UCE has presented some difficulties to customers seeking services in a diverse environment, including excessive Memory Usage (MU) and prolonged Component Construction Time (CCT). To optimize the user's experience, fuzzy agent employs a non-intrusive approach in online deep-rooted learning to get insights into user behavior. Integrating the advancements mentioned above aims to enhance the connectivity between users and information technology devices by utilizing an invisible network of UCE devices, creating dynamic computational environments that can effectively meet the users' needs. This work presents a unique methodology called Fuzzy Agent Middleware to Enhance User Experiences (FAM-EUI), which aims to improve user experiences in contexts where computer technology is seamlessly incorporated into everyday activities. This research endeavors to tackle the issues associated with imprecise data and enhance user-friendly interactions by integrating fuzzy logic with intelligent agents. The results highlight the potential of FAM in enhancing user interaction within ubiquitous soft computing, leading to improved efficiency and user-centered computing systems. This study provides valuable insights into integrating soft computing and agent-based technologies to enhance ubiquitous computing paradigms.

The main focus of this research will be on pervasive computing. Pervasive computing, (also called ubiquitous computing) is the growing trend towards embedding microprocessors in everyday objects so they can communicate information. Pervasive computing devices are completely connected and constantly available. Throughout this research pervasive computing will be defined, examples will be provided, and we will discuss it’s relevancy as time goes forward. Towards the end of our research we will provide an idea that could ease the human experience with respect to pervasive computing.

Why do people share their context information on Social Network Services? A qualitative study and an experimental study on users' behavior of balancing perceived benefit and risk

The fast development on microelectronics has promoted the increase on the computational power of hardware components. On the other hand, we are facing a significant improvement on energy consumption as well as the reduction of the physical size of such components. These improvements and the emergence of wireless networking technologies are enabling the development of small and powered mobile devices. Due to this scenario, the so-called pervasive computing paradigm, introduced by Mark Weiser in 1991 (Weiser, 1991) is becoming a reality. Such a paradigm envisions a world where environments are inhabited by computing devices, all of them seamlessly integrated into peoples’ lives, and effectively helping to carry on their daily tasks. Among others, one major characteristic of Weiser’s vision is that each device in an environment becomes a potential client or provider of resources. Not surprisingly, pervasive computing environments are becoming dynamic repositories of computational resources, all of them available to mobile users from the palm of their hands. However, devices can unpredictably join and leave such environments. Thus, resources can be dynamically made available or unavailable. Such a scenario has a great impact on the way that resources are found and used. In the case of static environments, such as the Web, it is reasonable to look up and access resources, such as Web pages, knowing the address of their providers beforehand. On the other hand, for dynamic environments, such as the pervasive computing ones, this is not a reasonable approach. This is due to the fact that one cannot guarantee that the provider of a resource will be available at any moment, because it may have left the environment or simply turned off. A better approach would be to discover these resources based on their descriptions, or any other feature that does not require the client to know the specific address of their providers. To this end, some of the current pervasive computing solutions, like Wings (Loureiro, Bublitz, Oliveira, Barbosa, Perkusich, Almeida, & Ferreira, 2006), Green (Sivaharan, Blair, & Coulson, 2005), RUNES (Costa, Coulson, Mascolo, Picco, & Zachariadis, 2005), and Scooby (Robinson, Wakeman, & Owen, 2004), are making use of a novel approach from the branch of distributed applications, the service-oriented computing paradigm (Papazoglou, 2003; Huhns & Singh, 2005). This is due to the fact that such a paradigm provides a crucial element for pervasive computing systems, the ability for dynamically binding to remote resources (Bellur & Narenda, 2005), which enables mobile devices to find needed services on demand. However, pervasive environments may be structured in different ways. They can range from wired networks to completely wireless ones, where communication among the devices is performed in an ad hoc way. Such a characteristic indicates that the way services are provisioned in a pervasive computing environment should fit in its organization, in order to enhance the access to the services available. Considering the above discussion, in this article we provide a review on service provision and its applicability in pervasive computing. More precisely, we will list the existing service provision approaches and discuss the characteristics and problems associated with each one, as well as their usage in pervasive computing environments. We start by providing introductory concepts of service-oriented and pervasive computing, respectively in the service-oriented computing and pervasive computing sections. Next, we present the service provision techniques available and how they can be applied for pervasive computing environments. The main current solutions within this scope will be introduced in the service oriented technologies section. Some of the future trends associated with research for service provision in pervasive computing environments will be presented in the future research trends section. Finally, in the conclusions sect

…On the direct programming of CNC milling equipment

In this paper, we define and implement the protocol to manage networks in USN (ubiquitous sensor network). Although network management system in USN related with this paper is being progressed for the purpose of independent projects, protocol interfaces and message systems have not clearly defined yet such as general-purpose network or extension into heterogeneous kinds, communication support, etc. Therefore, USN network management should be conducted for the management of fault, composition, power, and applications. In this paper, we design the ubiquitous sensor network based on u-learning processing for multiple devices in order to connect other devices for the multimedia services, allowing the characteristics of existing network protocols.

Software configuration in a heterogeneous and dynamic environment such as ubiquitous computing is a challenging task. This paper presents the COCA model, which transforms heterogeneous ubiquitous computing resources through a process called classification into a conceptualized representation, which allows high-level manipulation and configuration by ubiquitous computing applications. A multi-modal ubiquitous computing application serves as a sample implementation of the model that uses an automatic software configuration process to dynamically adapt to changes in the environment.KeywordsUbiquitous ComputingAutomatic SoftwareUbiquitous Computing EnvironmentWireless Application ProtocolPublic Switch Telephony NetworkThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Our vision is to create an independent content-distribution system using ubiquitous computing technologies. In this paper, we report on how we implemented mobile computing applications to design and build a content-distribution system using Bluetooth technology in an urban site in order to distribute context-sensitive media. The granularities of our design considerations included the ability to support both annotative and phenomenological locative media projects. GPS surveillance technologies were integrated into our prototype. While we were building the system, we conducted a survey to find out what would induce people to turn their Bluetooth on and what kinds of content they would like to receive. This paper contributes to the field of ubiquitous computing and urban studies through its description of how existing technologies can be combined to provide novel mobile computing applications in the city. In our vision a tram route assumes the guise of a performative terrain where passengers can listen to varied narratives of place.

Computing and communication technology is widely used and integrated in devices, environments, and everyday objects. Even with major advances in technology the vision of ubiquitous computing - from a user perspective - is not yet achieved. In this paper we look at new forms of interaction that will help to interact with the ubiquitous computer. In particular we introduce the concept of embedded interaction, and implicit use. The focus of the research is on embedding information into people's environments. Currently massive amounts of information are available. However, delivering it to the user in a way that is pleasant and not annoying is still a challenge. Observing mobile phone information push services, it appears that endless information is available; however, much of the information is interesting only in a very specific context of use. We investigate how information can be provided to users - exactly when and where it is needed. Our approach is based on a variety of information displays unobtrusively embedded into the user's everyday environment. We place the information displays in context. In contrast to the traditional approach on context-awareness where a context is recognized and then the appropriate information is delivered, we look at providing information already in context. It is up to the user to make use of the provided information or not.

This paper proposes a FAst paRAllel and pipeliNE Q-learning accelerator (FARANE-Q) for a configurable Reinforcement Learning (RL) algorithm implemented in a System on Chip (SoC). The proposed work offers flexibility, configurability, and scalability while maintaining computation speed and accuracy to overcome the challenges of a dynamic environment and increasing complexity. The proposed method includes a Hardware/Software (HW/SW) design methodology for the SoC architecture to achieve flexibility. We also propose joint optimizations on the algorithm, architecture, and implementation to obtain optimum (high efficiency) performance, specifically in energy and area efficiency. Furthermore, we implemented the proposed design in a real-time Zynq Ultra96-V2 FPGA platform to evaluate the functionality with an actual use case of smart navigation. Experimental results confirm that the proposed accelerator FARANE-Q outperforms state-of-the-art works by achieving a throughput of up to 148.55 MSps. It corresponds to the energy efficiency of 1747.64 MSps/W per agent for 32-bit and 2424.33 MSps/W per agent for 16-bit FARANE-Q. Moreover, the proposed 16-bit FARANE-Q outperforms other related works by an improvement of at least <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$1.23\times $ </tex-math></inline-formula> in energy efficiency. The designed system also maintains an error accuracy of less than 0.4% with optimized bit precision for more than eight fraction bits. The proposed FARANE-Q also offers a speed up of processing time up to <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$1795\times $ </tex-math></inline-formula> compared to embedded SW computation executed on ARM Zynq processor and <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$280\times $ </tex-math></inline-formula> of computation of full software executed on i7 processor. Hence, the proposed work has the potential to be used for smart navigation, robotic control, and predictive maintenance.

The Internet of Things designates a vision of an informationalized world, in which everyday objects are modified through computer technology such as RFID, sensors and sensor systems, tracking systems, or small computer units, giving them additional information or functions and integrating them with their environment. This paper explores the phenomenon of Internet of Things by applying some of the key concepts found in the philosophical works of Martin Heidegger and conducts a critical analysis using Martin Heidegger’s reflections on “world” and “technology” from Sein und Zeit (Being and Time) of 1957, and from the paper “Die Frage nach der Technik” (“The Question Concerning Technology”). The concept of “Ge-stell” introduced by Martin Heidegger to the philosophy of technology describes the situation of mankind and technology in a world shaped by modern technology. Both, mankind and technology, are tied to one dimension and share the same world. The world has been shaped and redesigned by technology, and the individual is completely tied into the technologized world. The basis for all Internet of Things concepts and installations is the expression of real-world things and processes as mathematical quantities and concepts, and the connecting of individual values and concepts with each other. The basis for all information technology is the reduction of reality to figures and calculable structures. Mathematics is the foundation of computer science, and thus the foundation of ubiquitous computing.

Information filtering is a crucial task in a world where data is generated steadily and at a high rate, helping users in distinguishing relevant from irrelevant content. This requires efficient processing of continuous streams of textual data. Event processing allows for real time processing of data streams. But up to now event processing has mainly been investigated in the context of business transaction-oriented domains like logistics or finance, but not explicitly in terms of text stream processing and information filtering. The growth of applications that analyze social media streams lets such an approach appear reasonable. Therefore we propose a common vocabulary represented by a text domain event model as well as a reference architecture for text stream processing and information filtering, in order to facilitate the implementation and the assessment of event processing applications for text streams. In addition we describe results from actual use cases that employ this architecture.

The use of satellite as backhaul in 5G networks is currently the most mature approach for satellite/5G integration, extending the coverage of 5G to underserved areas, beyond the reach of terrestrial backhaul infrastructures. This paper presents an actual implementation and over-the-air tests of a 5G Stand-Alone network, where a satellite link is used to interconnect the 5G Core with the RAN. Furthermore, local breakout is adopted to enable edge computing at the satellite edge; this is achieved by virtualizing and off-loading the 5GC User Plane Function to the edge. The performance of each configuration is evaluated with generic traffic, using the Open5GENESIS experiment automation suite, as well as in the context of an actual use case (5G smart agriculture).

The amount of data in the maritime domain is rapidly increasing due to the increase in devices that can collect marine information, such as sensors, buoys, ships, and satellites. Maritime data is growing at an unprecedented rate, with terabytes of marine data being collected every month and petabytes of data already being made public. Heterogeneous marine data collected through various devices can be used in various fields such as environmental protection, defect prediction, transportation route optimization, and energy efficiency. However, it is difficult to manage vessel related data due to high heterogeneity of such marine big data. Additionally, due to the high heterogeneity of these data sources and some of the challenges associated with big data, such applications are still underdeveloped and fragmented. In this paper, we propose the Vessel Data Lakehouse architecture consisting of the Vessel Data Lake layer that can handle marine big data, the Vessel Data Warehouse layer that supports marine big data processing and AI, and the Vessel Application Services layer that supports marine application services. Our proposed a Vessel Data Lakehouse that can efficiently manage heterogeneous vessel related data. It can be integrated and managed at low cost by structuring various types of heterogeneous data using an open source-based big data framework. In addition, various types of vessel big data stored in the Data Lakehouse can be directly utilized in various types of vessel analysis services. In this paper, we present an actual use case of a vessel analysis service in a Vessel Data Lakehouse by using AIS data in Busan area.

In June 2020, ETH Zurich’s Research Collection celebrated its third anniversary. The Research Collection serves as an institutional repository for ETH Zurich that can host both publications and research data and is operated by the E-Publishing team at the ETH Library. Publishing research data and advising customers on research-data-specific questions in the publishing workflow has emerged as a new field of activity for the team. With over 800 research data items published over the last few years, we have now gained a good understanding of the actual use cases for publishing data in an institutional repository at a large university for science and technology. We regularly talk to researchers about the incentives and requirements for publishing their data and monitor what kind of data they deposit. In this paper, we share and discuss our insights. We present statistics on the types of deposited datasets and explain how “FAIR” they are in terms of accessibility, licences and metadata. We also discuss our workflows for checking datasets for formal quality criteria and compliance with institutional policies and how to bridge publishing and preservation requirements in a research data repository. Finally, we give an overview of two ongoing development projects. The first one aims to enable ETH researchers to deposit datasets directly from the data management tool openBIS, while the second one will deliver a solution for publishing large datasets via the Research Collection.