Nonlinear Autoregressive Recurrent Neural Network Model for Quality of Service Prediction

Due to the advances in computer networks, Internet and multimedia communications, Quality of Service (QoS) monitoring and assessment become an increasingly important. The importance of assessing QoS stems from the fact it may reflect the resources availability of a network that may provide solutions for QoS provision, routing, monitoring, management … etc. In the literature, several monitoring and measurement approached and methods have been developed to quantify and predict the QoS of multimedia applications transmitted over such networks. In this research, a new QoS prediction system will be designed. The proposed system is based on using the Nonlinear Autoregressive with eXogenous input model (NARX) using recurrent neural network. This prediction system uses in addition to the QoS parameters; previous measured QoS values will used as inputs to this model. The expected output of this new model is the forecasted QoS. The proposed model will be trained, tested, validated and then optimized to provide a good estimate of the QoS provided by the given network. Simulation results are expected to show that the proposed model will have high accurate QoS prediction capabilities compared to other QoS assessment systems adopted in the literature.

Big Data Management in Maritime Transport

As maritime transport produces a large amount of data from various sources and in different formats, authors have analysed current applications of Big Data by researching global applications and experiences and by studying journal and conference articles. Big Data innovations in maritime transport (both cargo and passenger) are demonstrated, mainly in the fields of seaport operations, weather routing, monitoring/tracking and security. After the analysis, the authors have concluded that Big Data analyses can provide deep understanding of causalities and correlations in maritime transport, thus improving decision making. However, there exist major challenges of an efficient data collection and processing in maritime transport, such as technology challenges, challenges due to competitive conditions etc. Finally, the authors provide a future perspective of Big Data usage in maritime transport.

Distributed Methods for Multi-Sink Wireless Sensor Networks Formation

Recent application development in the wireless sensor networks (WSNs) area makes arise problems regarding data aggregation and effective methods to collect data. For addressing these problems, effective procedures are required. A multi-sink sensor network application has been characterized by many-to-many communication, where multiple sources report their data to multiple sinks. This chapter presents recent techniques for distributed multi-sink environments. The reviewed proposals are classified according to the purpose of the application, such as routing, monitoring of a specific target, data aggregation applications, and others. Finally, the authors present a discussion on the analyzed works.

Distributed Methods for Multi-Sink Wireless Sensor Networks Formation

Recent application development in the wireless sensor networks (WSNs) area makes arise problems regarding data aggregation and effective methods to collect data. For addressing these problems, effective procedures are required. A multi-sink sensor network application has been characterized by many-to-many communication, where multiple sources report their data to multiple sinks. This article presents recent techniques for distributed multi-sink environments. The reviewed proposals are classified according to the purpose of the application, such as routing, monitoring of a specific target, data aggregation applications, and others. Finally, we present a discussion on the analysed works.

Design on Monitoring System of Fire Disaster Based on Zigbee CC2530

Aiming at the practical problems existing in the fire disaster monitoring, such as harsh site conditions, the detection point difficult to change and expand, low automation level and the monitoring products having higher prices, etc., a fire disaster environment parameters intelligent monitoring system is designed based on the ZigBee CC2530 wireless communication chip. By deploying sensor network nodes in monitoring area, the monitoring information, that is, temperature, humidity, and smoke concentration of the fire site, is aggregated to the central monitoring system in order to achieve a unified data management and network routing monitoring functions. The central monitoring computer stores and displays the data sent by ZigBee network, thus the real-time monitoring of changes in environmental parameters of the fire site is achieved. The monitoring results have shown that this system is stable, high reliable in data transmission and easy to use, and can be used in environmental monitoring occasions inconvenient of direct attachment.

Air Quality Monitoring System Based on ZigBeeCC2530

Aiming at the actual demand of the indoor air quality safety monitoring, an air quality monitoring system was designed based on low-power ZigBee wireless communication technology and micro-controller chip CC2530. By deploying sensor network nodes in monitoring area, the monitoring information, that is, CO, formalin, SO2and benzene, are collected in real time and aggregated to the central monitoring system in order to achieve a unified data management and network routing monitoring functions. The central monitoring computer stores and displays the data sent by ZigBee network, thus achieves real-time monitoring of changes in indoor environmental parameters. The monitoring results have shown that this system is stable, high reliable in data transmission and easy to use, and can be applied to the automatic monitoring of environmental parameters in other areas by slight transformation.