Sensor grid middleware metamodeling and analysis

Sensor grid is a platform that combines wireless sensor networks and grid computing with the aim of exploiting the complementary advantages of the two systems. Proper integration of these distinct systems into effective, logically single platform is challenging. This paper presents an approach for practical sensor grid implementation and management. The proposed approach uses a metamodeling technique and performance analysis and tuning as well as a middleware infrastructure that enable practical sensor grid implementation and management. The paper presents our implementation and analysis of the sensor grid. © 2014 Srimathi Chandrasekaran et al

Emerging sensor-cloud technology for pervasive services and applications

This is an Editorial article for the Special Issue on "Emerging Sensor-Cloud Technology for Pervasive Services and Applications" of the International Journal of Distributed Sensor Networks

The integration, analysis and visualization of sensor data from dispersed wireless sensor network systems using the SWE framework

Wireless Sensor Networks (WSNs) have been used in numerous applications to remotely gather real-time data on important environmental parameters. There are several projects where WSNs are deployed in different locations and operate independently. Each deployment has its own models, encodings, and services for sensor data, and are integrated with different types of visualization/analysis tools based on in-dividual project requirements. This makes it difucult to reuse these services for other WSN applications. A user/system is impeded by having to learn the models, encodings, and ser-vices of each system, and also must integrate/interoperate data from different data sources. Sensor Web Enablement (SWE) provides a set of standards (web service interfaces and data encoding/model specifications) to make sensor data publicly available on the web. This paper describes how the SWE framework can be extended to integrate disparate WSN sys-tems and to support standardized access to sensor data. The proposed system also introduces a web-based data visualiza-tion and statistical analysis service for data stored in the Sen-sor Observation Service (SOS) by integrating open source technologies. A performance analysis is presented to show that the additional features have minimal impact on the sys-tem. Also some lessons learned through implementing SWE are discussed

Proposal of a health care network based on big data analytics for PDs

Health care networks for Parkinson's disease (PD) already exist and have been already proposed in the literature, but most of them are not able to analyse the vast volume of data generated from medical examinations and collected and organised in a pre-defined manner. In this work, the authors propose a novel health care network based on big data analytics for PD. The main goal of the proposed architecture is to support clinicians in the objective assessment of the typical PD motor issues and alterations. The proposed health care network has the ability to retrieve a vast volume of acquired heterogeneous data from a Data warehouse and train an ensemble SVM to classify and rate the motor severity of a PD patient. Once the network is trained, it will be able to analyse the data collected during motor examinations of a PD patient and generate a diagnostic report on the basis of the previously acquired knowledge. Such a diagnostic report represents a tool both to monitor the follow up of the disease for each patient and give robust advice about the severity of the disease to clinicians

Towards a cyber physical system for personalised and automatic OSA treatment

Obstructive sleep apnea (OSA) is a breathing disorder that takes place in the course of the sleep and is produced by a complete or a partial obstruction of the upper airway that manifests itself as frequent breathing stops and starts during the sleep. The real-time evaluation of whether or not a patient is undergoing OSA episode is a very important task in medicine in many scenarios, as for example for making instantaneous pressure adjustments that should take place when Automatic Positive Airway Pressure (APAP) devices are used during the treatment of OSA. In this paper the design of a possible Cyber Physical System (CPS) suited to real-time monitoring of OSA is described, and its software architecture and possible hardware sensing components are detailed. It should be emphasized here that this paper does not deal with a full CPS, rather with a software part of it under a set of assumptions on the environment. The paper also reports some preliminary experiments about the cognitive and learning capabilities of the designed CPS involving its use on a publicly available sleep apnea database

Model Driven Mutation Applied to Adaptative Systems Testing

Dynamically Adaptive Systems modify their behav- ior and structure in response to changes in their surrounding environment and according to an adaptation logic. Critical sys- tems increasingly incorporate dynamic adaptation capabilities; examples include disaster relief and space exploration systems. In this paper, we focus on mutation testing of the adaptation logic. We propose a fault model for adaptation logics that classifies faults into environmental completeness and adaptation correct- ness. Since there are several adaptation logic languages relying on the same underlying concepts, the fault model is expressed independently from specific adaptation languages. Taking benefit from model-driven engineering technology, we express these common concepts in a metamodel and define the operational semantics of mutation operators at this level. Mutation is applied on model elements and model transformations are used to propagate these changes to a given adaptation policy in the chosen formalism. Preliminary results on an adaptive web server highlight the difficulty of killing mutants for adaptive systems, and thus the difficulty of generating efficient tests.Comment: IEEE International Conference on Software Testing, Verification and Validation, Mutation Analysis Workshop (Mutation 2011), Berlin : Allemagne (2011

Digital-Twins towards Cyber-Physical Systems: A Brief Survey

Cyber-Physical Systems (CPS) are integrations of computation and physical processes. Physical processes are monitored and controlled by embedded computers and networks, which frequently have feedback loops where physical processes affect computations and vice versa. To ease the analysis of a system, the costly physical plants can be replaced by the high-fidelity virtual models that provide a framework for Digital-Twins (DT). This paper aims to briefly review the state-of-the-art and recent developments in DT and CPS. Three main components in CPS, including communication, control, and computation, are reviewed. Besides, the main tools and methodologies required for implementing practical DT are discussed by following the main applications of DT in the fourth industrial revolution through aspects of smart manufacturing, sixth wireless generation (6G), health, production, energy, and so on. Finally, the main limitations and ideas for future remarks are talked about followed by a short guideline for real-world application of DT towards CPS

The Integration, Analysis and Visualization of Sensor Data from Dispersed Wireless Sensor Network Systems Using the SWE Framework, Journal of Telecommunications and Information Technology, 2001, nr 4

Wireless Sensor Networks (WSNs) have been used in numerous applications to remotely gather real-time data on important environmental parameters. There are several projects where WSNs are deployed in different locations and operate independently. Each deployment has its own models, encodings, and services for sensor data, and are integrated with different types of visualization/analysis tools based on individual project requirements. This makes it difficult to reuse these services for other WSN applications. A user/system is impeded by having to learn the models, encodings, and services of each system, and also must integrate/interoperate data from different data sources. Sensor Web Enablement (SWE) provides a set of standards (web service interfaces and data encoding/model specifications) to make sensor data publicly available on the web. This paper describes how the SWE framework can be extended to integrate disparate WSN systems and to support standardized access to sensor data. The proposed system also introduces a web-based data visualization and statistical analysis service for data stored in the Sensor Observation Service (SOS) by integrating open source technologies. A performance analysis is presented to show that the additional features have minimal impact on the system. Also some lessons learned through implementing SWE are discussed