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A Toulmin's Framework-Based Method for Design Argumentation of Cyber-Physical Systems
Get PDFThe design of cyber-physical systems (CPS) is a promising domain, where the data market is expected to soon penetrate. When engineers focus on only a particular part of data (whether intentionally or not) for establishing a design hypothesis, the design hypothesis may also be supported by data sets in the market. Therefore, the validity of such a design hypothesis cannot be evaluated by the data itself, and can only be accepted by the robustness of the logic behind the design argumentation. Although the validation of the design logic is significant, cognitive aspects (which people have spontaneously) disturb the design argumentation reasoning. Therefore, a design method that overcomes the cognitive aspects is indispensable for the CPS designers. This work proposes a CPS design method using the interaction between logic and data sets with a logic visualization tool, and applies the proposed method to the design of a diagnosis system for semiconductor manufacture. The capability of the proposed method is also discussed and analyzed in this paper
Accurate Distance Estimation between Things: A Self-correcting Approach
Get PDFThis paper suggests a method to measure the physical distance between an IoT device (a Thing) and a mobile device (also a Thing) using BLE (Bluetooth Low-Energy profile) interfaces with smaller distance errors. BLE is a well-known technology for the low-power connectivity and suitable for IoT devices as well as for the proximity with the range of several meters. Apple has already adopted the technique and enhanced it to provide subdivided proximity range levels. However, as it is also a variation of RSS-based distance estimation, Apple's iBeacon could only provide immediate, near or far status but not a real and accurate distance. To provide more accurate distance using BLE, this paper introduces additional self-correcting beacon to calibrate the reference distance and mitigate errors from environmental factors. By adopting self-correcting beacon for measuring the distance, the average distance error shows less than 10% within the range of 1.5 meters. Some considerations are presented to extend the range to be able to get more accurate distances
An Efficient Approach for Cost Optimization of the Movement of Big Data
Get PDFWith the emergence of cloud computing, Big Data has caught the attention of many researchers in the area of cloud computing. As the Volume, Velocity and Variety (3 Vs) of big data are growing exponentially, dealing with them is a big challenge, especially in the cloud environment. Looking at the current trend of the IT sector, cloud computing is mainly used by the service providers to host their applications. A lot of research has been done to improve the network utilization of WAN (Wide Area Network) and it has achieved considerable success over the traditional LAN (Local Area Network) techniques. While dealing with this issue, the major questions of data movement such as from where to where this big data will be moved and also how the data will be moved, have been overlooked. As various applications generating the big data are hosted in geographically distributed data centers, they individually collect large volume of data in the form of application data as well as the logs. This paper mainly focuses on the challenge of moving big data from one data center to other. We provide an efficient algorithm for the optimization of cost in the movement of the big data from one data center to another for offline environment. This approach uses the graph model for data centers in the cloud and results show that the adopted mechanism provides a better solution to minimize the cost for data movement
Introductory Editorial
Get PDFThe Open Journal of Big Data is a new open access journal published by RonPub, and RonPub is an academic publisher of online, open access, peer-reviewed journals. OJBD addresses aspects of Big Data, including new methodologies, processes, case studies, poofs-of-concept, scientific demonstrations, industrial applications and adoption. This editorial presents the two articles in this first issue. The first paper is on An Efficient Approach for Cost Optimization of the Movement of Big Data, which mainly focuses on the challenge of moving big data from one data center to other.The second paper is on Cognitive Spam Recognition Using Hadoop and Multicast-Update, which describes a method to make machines cognitively label spam using Machine Learning and the Naive Bayesian approach. OJBD has a rising reputation thanks to the support of research communities, which help us set up the First International Conference on Internet of Things and Big Data 2016 (IoTBD 2016), in Rome, Italy, between 23 and 25 April 2016
The Potential of Printed Electronics and Personal Fabrication in Driving the Internet of Things
Get PDFIn the early nineties, Mark Weiser, a chief scientist at the Xerox Palo Alto Research Center (PARC), wrote a series of seminal papers that introduced the concept of Ubiquitous Computing. Within this vision, computers and others digital technologies are integrated seamlessly into everyday objects and activities, hidden from our senses whenever not used or needed. An important facet of this vision is the interconnectivity of the various physical devices, which creates an Internet of Things. With the advent of Printed Electronics, new ways to link the physical and digital worlds became available. Common printing technologies, such as screen, flexography, and inkjet printing, are now starting to be used not only to mass-produce extremely thin, flexible and cost effective electronic circuits, but also to introduce electronic functionality into objects where it was previously unavailable. In turn, the growing accessibility to Personal Fabrication tools is leading to the democratization of the creation of technology by enabling end-users to design and produce their own material goods according to their needs. This paper presents a survey of commonly used technologies and foreseen applications in the field of Printed Electronics and Personal Fabrication, with emphasis on the potential to drive the Internet of Things
Scalable Distributed Computing Hierarchy: Cloud, Fog and Dew Computing
Get PDFThe paper considers the conceptual approach for organization of the vertical hierarchical links between the scalable distributed computing paradigms: Cloud Computing, Fog Computing and Dew Computing. In this paper, the Dew Computing is described and recognized as a new structural layer in the existing distributed computing hierarchy. In the existing computing hierarchy, the Dew computing is positioned as the ground level for the Cloud and Fog computing paradigms. Vertical, complementary, hierarchical division from Cloud to Dew Computing satisfies the needs of high- and low-end computing demands in everyday life and work. These new computing paradigms lower the cost and improve the performance, particularly for concepts and applications such as the Internet of Things (IoT) and the Internet of Everything (IoE). In addition, the Dew computing paradigm will require new programming models that will efficiently reduce the complexity and improve the productivity and usability of scalable distributed computing, following the principles of High-Productivity computing
Statistical Machine Learning in Brain State Classification using EEG Data
Get PDFIn this article, we discuss how to use a variety of machine learning methods, e.g. tree bagging, random forest, boost, support vector machine, and Gaussian mixture model, for building classifiers for electroencephalogram (EEG) data, which is collected from different brain states on different subjects. Also, we discuss how training data size influences misclassification rate. Moreover, the number of subjects that contributes to the training data affects misclassification rate. Furthermore, we discuss how sample entropy contributes to building a classifier. Our results show that classification based on sample entropy give the smallest misclassification rate. Moreover, two data sets were collected from one channel and seven channels respectively. The classification results of each data set show that the more channels we use, the less misclassification we have. Our results show that it is promising to build a self-adaptive classification system by using EEG data to distinguish idle from active state
Semantic and Web: The Semantic Part
Get PDFThe Web is everywhere in daily life. Business is not possible any more without the fast communication through the web. The knowledge of the humans is reflected in the information accessible in the web. New challenges occur with the flood of information and electronic possibilities for the human being. The current World Wide Web enables an easy, instant access to a vast amount of online information. However, the content in the Web is typically for human consumption, and is not tailored to be machine-processed. The Semantic Web, which is intended to establish a machine-understandable web, thereby offers a promising and potential solution to mining and analyzing web content. The Semantic Web is currently changing from an emergent trend to a technology used in complex real-world applications. This part of the special issue "Semantic and Web" especially investigates how semantic technologies can help the human being to open the new possibilities of the web. The papers, which contribute more to Web technologies, are published in Open Journal of Web Technologies (OJWT)
Cooperative Hybrid Cloud Intermediaries - Making Cloud Sourcing Feasible for Small and Medium-sized Enterprises
Get PDF"The cloud" is widely advertised as a silver bullet for many IT-related challenges of small and medium-sized enterprises (SMEs). While it can potentially have a number of attractive benefits, many SMEs refrain from using cloud sourcing and cloud services because of high upfront costs for building the appropriate knowledge in the enterprise, for searching and screening of possible cloud service providers, and for mastering the intricate legal issues related to outsourcing sensitive data. This paper presents the concept of hybrid cloud intermediaries, an approach that can address many of the prevailing issues. With the aid of empirical findings from a cross-nation study of cloud adoption in SMEs for context, we describe the concept in detail and show conceivable variants, including a comprehensive cross-perspective consolidated model of cloud intermediary value-creation. Subsequently, we analyze the benefits of such a hybrid cloud intermediary for addressing cloud adoption issues in SMEs, and suggest suitable governance structures based on the cooperative paradigm. The resulting entity - a cooperative hybrid cloud intermediary or, more concisely, co-op cloud - is discussed in detail showing both feasible scenarios and limitations for SMEs that would like to engage in a cloud-sourcing
Modelling the Integrated QoS for Wireless Sensor Networks with Heterogeneous Data Traffic
Get PDFThe future of Internet of Things (IoT) is envisaged to consist of a high amount of wireless resource-constrained devices connected to the Internet. Moreover, a lot of novel real-world services offered by IoT devices are realized by wireless sensor networks (WSNs). Integrating WSN to the Internet has therefore brought forward the requirements of an end-to-end quality of service (QoS) guarantee. In this paper, the QoS requirements for the WSN-Internet integration are investigated by first distinguishing the Internet QoS from the WSN QoS. Next, this study emphasizes on WSN applications that involve traffic with different levels of importance, thus the way realtime traffic and delay-tolerant traffic are handled to guarantee QoS in the network is studied. Additionally, an overview of the integration strategies is given, and the delay-tolerant network (DTN) gateway, being one of the desirable approaches for integrating WSNs to the Internet, is discussed. Next, the implementation of the service model is presented, by considering both traffic prioritization and service differentiation. Based on the simulation results in OPNET Modeler, it is observed that real-time traffic achieve low bound delay while delay-tolerant traffic experience a lower packet dropped, hence indicating that the needs of real-time and delay-tolerant traffic can be better met by treating both packet types differently. Furthermore, a vehicular network is used as an example case to describe the applicability of the framework in a real IoT application environment, followed by a discussion on the future work of this research