U-health expert system with statistical neural network

Ubiquitous Health(U-Health) system witch focuses on automated applications that can provide healthcare to human anywhere and anytime using wired and wireless mobile technologies is becoming increasingly important. This system consists of a network system to collect data and a sensor module which measures pulse, blood pressure, diabetes, blood sugar, body fat diet with management and measurement of stress etc, by both wired and wireless and further portable mobile connections. In this paper, we propose an expert system using back-propagation to support the diagnosis of citizens in U-Health system

An Energy-Efficient MAC Protocol Using Dynamic Queue Management for Delay-Tolerant Mobile Sensor Networks

Conventional MAC protocols for wireless sensor network perform poorly when faced with a delay-tolerant mobile network environment. Characterized by a highly dynamic and sparse topology, poor network connectivity as well as data delay-tolerance, delay-tolerant mobile sensor networks exacerbate the severe power constraints and memory limitations of nodes. This paper proposes an energy-efficient MAC protocol using dynamic queue management (EQ-MAC) for power saving and data queue management. Via data transfers initiated by the target sink and the use of a dynamic queue management strategy based on priority, EQ-MAC effectively avoids untargeted transfers, increases the chance of successful data transmission, and makes useful data reach the target terminal in a timely manner. Experimental results show that EQ-MAC has high energy efficiency in comparison with a conventional MAC protocol. It also achieves a 46% decrease in packet drop probability, 79% increase in system throughput, and 25% decrease in mean packet delay

ORIGINAL PAPER mHealthMon: Toward Energy-Efficient and Distributed Mobile Health Monitoring Using Parallel Offloading

Abstract Although mobile health monitoring where mobile sensors continuously gather, process, and update sensor readings (e.g. vital signals) from patient’s sensors is emerging, little effort has been investigated in an energyefficient management of sensor information gathering and processing. Mobile health monitoring with the focus of energy consumption may instead be holistically analyzed and systematically designed as a global solution to optimization subproblems. This paper presents an attempt to decompose the very complex mobile health monitoring system whose layer in the system corresponds to decomposed subproblems, and interfaces between them are quantified as functions of the optimization variables in order to orchestrate the subproblems. We propose a distributed and energy-saving mobile health platform, called mHealthMon where mobile users publish/access sensor data via a cloud computing-based distributed P2P overlay network. The key objective is to satisfy the mobile health monitoring application’s quality of service requirements by modeling each subsystem: mobile clients with medical sensors, wireless network medium, and distributed cloud services. By simulations based on experimental data, we present the proposed system can achieve up to 10.1 times more energy-efficient and 20.2 times faster compared to a standalone mobil

IoB-DTN: a lightweight DTN protocol for mobile IoT Applications to smart bike sharing systems

International audienceInformation and communication are key to the intelligent city of tomorrow. Many technologies have been designed to connect smart devices to the Internet. In particular, public transport systems have been used to collect data from mobile devices. Public bike sharing systems have been introduced as part of the urban transportation system and could be used as the support of a mobile sensor network. In this paper, we introduce the "Internet of Bikes" IoB-DTN protocol which applies De-lay/Disruption Tolerant Network (DTN) paradigm to the Internet of Things (IoT) applications running on urban bike sharing system based sensor network. We evaluate the performance of three variants of IoB-DTN with four buffer management policies. Our results show that limiting the number of packet copies sprayed in the network and prioritizing generated packets against relayed ones, improves on low loss rate and delivery delay in urban bicycle scenario

DATA DRIVEN INTELLIGENT AGENT NETWORKS FOR ADAPTIVE MONITORING AND CONTROL

To analyze the characteristics and predict the dynamic behaviors of complex systems over time, comprehensive research to enable the development of systems that can intelligently adapt to the evolving conditions and infer new knowledge with algorithms that are not predesigned is crucially needed. This dissertation research studies the integration of the techniques and methodologies resulted from the fields of pattern recognition, intelligent agents, artificial immune systems, and distributed computing platforms, to create technologies that can more accurately describe and control the dynamics of real-world complex systems. The need for such technologies is emerging in manufacturing, transportation, hazard mitigation, weather and climate prediction, homeland security, and emergency response. Motivated by the ability of mobile agents to dynamically incorporate additional computational and control algorithms into executing applications, mobile agent technology is employed in this research for the adaptive sensing and monitoring in a wireless sensor network. Mobile agents are software components that can travel from one computing platform to another in a network and carry programs and data states that are needed for performing the assigned tasks. To support the generation, migration, communication, and management of mobile monitoring agents, an embeddable mobile agent system (Mobile-C) is integrated with sensor nodes. Mobile monitoring agents visit distributed sensor nodes, read real-time sensor data, and perform anomaly detection using the equipped pattern recognition algorithms. The optimal control of agents is achieved by mimicking the adaptive immune response and the application of multi-objective optimization algorithms. The mobile agent approach provides potential to reduce the communication load and energy consumption in monitoring networks. The major research work of this dissertation project includes: (1) studying effective feature extraction methods for time series measurement data; (2) investigating the impact of the feature extraction methods and dissimilarity measures on the performance of pattern recognition; (3) researching the effects of environmental factors on the performance of pattern recognition; (4) integrating an embeddable mobile agent system with wireless sensor nodes; (5) optimizing agent generation and distribution using artificial immune system concept and multi-objective algorithms; (6) applying mobile agent technology and pattern recognition algorithms for adaptive structural health monitoring and driving cycle pattern recognition; (7) developing a web-based monitoring network to enable the visualization and analysis of real-time sensor data remotely. Techniques and algorithms developed in this dissertation project will contribute to research advances in networked distributed systems operating under changing environments

Game Theoretical Approach for Joint Relay Selection and Resource Allocation in Mobile Device Networks

With the improvement of hardware, more and more multimedia applications are allowed to run in the mobile device. However, due to the limited radio bandwidth, wireless network performance becomes a critical issue. Common mobile solutions are based on the centralized structure, which require an access point to handle all the communication requirement in the work area. The transmission performance of centralized framework relies on the density of access points. But increasing the number of access points will cost lot of money and the interference between access point will reduce the transmission quality. Thanks to the wireless sensor network implementations, the distributed wireless network solution has been well studied. Now, many mobile network studies introduce the device to device idea which is a distributed structure of mobile network. Unlike wireless sensor networks, mobile networks have more movability and higher transmission speed requirement. In order to be used in mobile networks, a distributed network management algorithm needs to perform faster and more accurate. In this thesis, a new pairing algorithm is proposed to provide a better transmission quality for multimedia data. In the proposed approach, the multimedia data is quantized by distortion reduction. Then, the source-relay pairing solution is optimized by a history tracing system using game theory to improve the expected overall distortion reduction of the entire network. Several parameters are introduced in the proposed solution, so the optimization would fit for different situations. Simulation results show that the proposed algorithm achieves higher overall distortion reduction by avoiding the competition between nodes. Simulation results also show the parameters would affect the system performance, such as optimization speed, system stability and system overall transmit speed