High Precision Clock Bias Prediction Model in Clock Synchronization System

Time synchronization is a fundamental requirement for many services provided by a distributed system. Clock calibration through the time signal is the usual way to realize the synchronization among the clocks used in the distributed system. The interference to time signal transmission or equipment failures may bring about failure to synchronize the time. To solve this problem, a clock bias prediction module is paralleled in the clock calibration system. And for improving the precision of clock bias prediction, the first-order grey model with one variable (GM(1,1)) model is proposed. In the traditional GM(1,1) model, the combination of parameters determined by least squares criterion is not optimal; therefore, the particle swarm optimization (PSO) is used to optimize GM(1,1) model. At the same time, in order to avoid PSO getting stuck at local optimization and improve its efficiency, the mechanisms that double subgroups and nonlinear decreasing inertia weight are proposed. In order to test the precision of the improved model, we design clock calibration experiments, where time signal is transferred via radio and wired channel, respectively. The improved model is built on the basis of clock bias acquired in the experiments. The results show that the improved model is superior to other models both in precision and in stability. The precision of improved model increased by 66.4%~76.7%

A framework for multimodal wireless sensor networks

Wireless Sensor Networks are a widely used solution for monitoring oriented applications (e.g., water quality on watersheds, pollution monitoring in cities). These kinds of applications are characterized by the necessity of two data-reporting modes: time-driven and event-driven. The former is used mainly for continually supervising an area and the latter for event detection and tracking. By switching between both modes, a WSN can improve its energy-efficiency and event reporting latency, compared to single data-reporting schemes. We refer to those WSNs, where both data-reporting modes are required simultaneously, as MultiModal Wireless Sensor Networks (M2WSNs). M2WSNs arise as a solution for the trade-off between energy savings and event reporting latency in those monitoring-oriented applications where regular and emergency reporting are required simultaneously. The multimodality in these M2WSNs allows sensor nodes to perform data-reporting in two possible schemes, time-driven and event-driven, according to the circumstances, providing higher energy savings and better reporting results when compared to traditional schemes. Traditionally, sophisticated power-aware wake-up schemes have been employed to achieve energy efficiency in WSNs, such as low-duty cycling protocols using a single radio architecture. These protocols achieve good results regarding energy savings, but they suffer from idle-listening and overhearing issues, that make them not reliable for most ultra-low-power demanding applications, especially, those deployed in hostile and unattended environments. Currently, Wake-up Radio Receivers based protocols, under a dual-radio architecture and always-on operation, are emerging as a solution to overcome these issues, promising higher energy consumption reduction and reliability in terms of latency and packet-delivery-ratio compared to classic wake-up protocols. By combining different transceivers and reporting protocols regarding energy efficiency and reliability, multimodality in M2WSNs is achieved. This dissertation proposes a conceptual framework for M2WSNs that integrates the goodness of both data-reporting schemes and the Wake-up Radio paradigm--data periodicity, responsiveness, and energy-efficiency--, that might be suitable for monitoring oriented applications with low bandwidth requirements, that operates under normal circumstances and emergencies. The framework follows a layered approach, where each layer aims to fulfill specific tasks based on its information, the functions provided by its adjacent layers, and the information resulted from the cross-layer interactions.Doctor en IngenieríaDoctoradohttps://orcid.org/0000-0003-1346-6451https://scholar.google.com.co/citations?user=0I4kXQUAAAAJ&hl=enhttps://scienti.minciencias.gov.co/cvlac/visualizador/generarCurriculoCv.do?cod_rh=000001365

The Environmental Health of the Autistic Student in the Public School Classroom

Professionals have found autism to be an enigmatic condition. While necessary biomedical research continues, a gap exists in the inclusion of parental opinions, knowledge, and experiences in educational planning for their autistic children. The purpose of this mixed methods study was to identify the factors that the parents felt contributed to the academic success of their autistic child in the public school classroom environment and ways in which their ideas might contribute to overall educational planning and classroom design in structure, curriculum development, and intervention strategies which might lead to reduced stress. Parental input was explored through semistructured personal interviews with 8 parents and the administration of a 32-question survey questionnaire to 109 parents of autistic children. A content analysis was done on the qualitative data, and an analysis of quantitative data reported the frequency and percentages of the participant responses. Findings from the data revealed multiple areas in need of improved educational services that include the classroom organization, educator training and knowledge about the autistic condition, educator support, effective communication, and behavioral management of the symptoms of autism. The social change impact from the study\u27s findings have the potential to inform educational planning, foster collaboration, increase educator participation in autism training methods, secure necessary funding for evidence based autism educational programs, promote further research, and provide awareness of existing empirically based approaches designed to meet the needs of a vulnerable population

Visoko-pouzdan prenos podataka kod bežičnih senzorskih mreža sa malom potrošnjom energije primenom 2D-SEC-DED tehnike kodiranja

This dissertation deals with the challenges of energy efficiency in systems with limited resources of homogeneous and heterogeneous wireless sensory networks for data collection applications in real environmentals. This research covers several fields from physical layer optimization up to network layer solutions. The problem which has to be solved is viewed from three different perspectives: the energy profile of the nodes with a special emphasis on the activity of the sensing block, the network protocol with a special focus on finding an adequate coding technique that need to reduce or eliminate the request for retransmission and evaluating the range of transmission for the proposed encoding technique. If energy efficiency in wireless sensor networks is formulated as a load balancing problem then the power management unit can significantly contribute to reduction in power consumption. Power management is implemented by switching on/off individual subblocks of the sensor node independently of the hardware platform. By reducing energy consumption both an extension of the lifetime of the sensor node and sensor network, is achieved. The obtained energy profiles reveal significant differences in energy consumption of wireless sensor nodes depending in terms of external sensors number, resolution of the analog-to-digital converter, network traffic dynamics, topology of the network, applied coding techniques, operating modes and activities during the lifetime of the sensor node and other factors. In this sense, the application of combination of power aware techniques, such as the duty-cycling at system-level, and power gating at the level of sensor elements, i.e. sensors, is proposed. An evaluation of the approach shows that energy consumption reduction three orders of magnitude on average can be achieved, when these two techniques are incorporated into the sensor node. On the other hand, in the wireless sensor networks, the choice of coding scheme, i.e. channel coding depends on the application and characteristics-, model-, type-errors appearing in the wireless channel. For example, one encoding technique is preferred for use when burst errors patterns are dominant, while another coding technique is more acceptable in situations where noise causes random errors that are either single or double in nature. Bearing this in mind, along with the analysis of channel characteristics, in this dissertation, we propose a new massage coding technique by which on extend traditional protocols with aim to improve energy efficiency, while maintaining high reliability in data transmission and low latency of message transfer. Namely, channel evaluation in wireless sensor networks used in industry shows that most of the errors are of single or double nature, and burst type errors are present, but rarely. In this context, in this dissertation, an effective technique for correcting errors at a destination (FEC) based on Hamming's coding scheme of relatively low complexity, called Two Dimensional-Single Error Correction- Double Error Detection (2D-SEC-DED) was developed. The proposed encoding technique is intendet to minimize packet retransmissions, thus saving energy. Evaluation of the proposed encoding scheme shows that the code is able to correct all single errors and 99.99% of double/multiple errors. The analysis was carried out through the implementation, in MATLAB, of two versions of Rendezvous Protocol for Long Life (RPLL), called Modified RPLL (M-RPLL) and Ordinary RPLL (O-RPLL), respectively. The energy gain achieved in this way is used to improve the performance of wireless transmission, such as increasing of the transmission range. As illustration, for indoor environment characterized by the path loss exponent 4 at the target BER of 5 10 4 , the proposed encoding scheme is able to improve the transmission distance by about 18 m , or the received signal strength (RSSI) by about 8.5 dBm compared to wireless sensor networks with encoding schemes without possibility to correct errors