Wireless Sensor nodes fall somewhere in between the single application devices that do not need an operating system, and the more capable, general purpose devices with the resources to run a traditional embedded operating system. Sensor node operating system such as TinyOS, Contiki, MantisOS and SOS which is discussed in this paper exhibit characteristics of both traditional embedded systems and general-purpose operating systems providing a limited number of common services for application developers linking software and hardware. These common services typically include platform support, hardware management of sensors, radios, and I/O buses and application construction etc. They also provide services needed by applications which include task coordination, power management, adaptation to resource constraints, and networking. The evaluation was concentrated on TinyOS including an analysis on version 1.x and 2.x resource management and flexibility and its operation with the other wireless sensor node operating systems.

Wireless sensor networks (WSNs) are increasingly being used for monitoring physical environments in lieu of tethered monitoring systems. Being power efficient and wirelessly accessible, WSNs find applications in a variety of domains like health, structural and climate monitoring systems. Despite such diverse use cases, more than often, WSNs are used by researchers with basic or no prior programming experience. Consequently, more time is spent learning to program the sensors than collecting and analysing domain-specific data. To cater to this generic user base, a multi-platform user-friendly programming framework for WSNs has been developed. This framework provides: 1) a visual network comparison tool that analyzes packet traces of two networks to generate a juxtaposed visual comparison of contrasting network characteristics, 2) a scripting language based on the TinyOS sensor network platform that aims at reducing code size and improving programming efficacy, and 3) a visual programming tool with basic sensor drag-and-drop modules for generating simple WSN programs. These tools were also developed to serve as a gentle introduction to the WSN programming environment for middle and high school students. In the absence of resources (sensors), the framework also allows programmers to verify program functionality by remotely simulating and verifying program behaviour in the OMNeT simulation environment.

Made available in DSpace on 2014-06-12T16:01:12Z (GMT). No. of bitstreams: 2 arquivo7175_1.pdf: 951409 bytes, checksum: c76423488bb414047eb8d697e9c1af4d (MD5) license.txt: 1748 bytes, checksum: 8a4605be74aa9ea9d79846c1fba20a33 (MD5) Previous issue date: 2005 / Os avanços tecnológicos nas áreas de micro-eletrônica, informática e telecomunicações vêm abrindo novas possibilidades para o monitoramento remoto de sinais vitais de pacientes, o que pode reduzir custos hospitalares de internação por períodos prolongados, permitir o diagnóstico por especialistas de centros médicos mais avançados, além de proporcionar um incremento na qualidade de vida dos pacientes. Diversos projetos acadêmicos e comerciais buscam desenvolver dispositivos de monitoramento remoto baseados em microcontroladores. Tais dispositivos são programados para executar funções relacionadas à aquisição de sinais, tratamento, armazenamento e transmissão de dados. No entanto, a crescente necessidade por mais funcionalidades, adequação a novos padrões de comunicação, diversidade de plataformas de hardware e aumento da produtividade do desenvolvimento permanecem como desafios no contexto de escassez de recursos computacionais desse tipo de dispositivo. Este trabalho propõe um framework para o desenvolvimento de aplicações de monitoramento de sinais vitais, o TinyMonitor, baseado no sistema operacional TinyOS. Aproveitando as características de programação modularizada do TinyOS, o TinyMonitor define um modelo de componentes que contempla as principais funcionalidades dessa classe de aplicações, permitindo que sejam agregadas novos tipos de captura e processamento de sinais, dispositivos de armazenamento e suporte a diferentes meios de transmissão de dados através da fácil extensão, substituição e reuso de módulos. O modelo de componentes proposto foi implementado como parte de um estudo de caso para o desenvolvimento de uma aplicação de monitoramento de sinais eletrocardiográficos. Posteriormente, essa implementação inicial foi estendida para acrescentar o processamento da freqüência cardíaca. A validação desse estudo de caso se deu por meio de simulações na ferramenta Tossim

In the wireless sensor network, the WLAN interference, multi-path fading andattenuation are the main reason for packets’ corruption. Forward errorcorrection is one of the methods for error mitigation. Many coding methods aredesigned to improve the reliability of wireless channel. However, none of thesecoding methods could handle the burst errors that widely exist in wirelesschannel and are mainly responsible for packet corruption. Interleaving isintroduced to robust these coding methods and make those corrupted packetsavailable to be corrected by spreading the burst errors. The Reed-Solomon(15,7) block code is used as the forwarding error correction in theseexperiments. In this paper, seven different symbol interleaving will be firstlysimulated in the Matlab platform under four different channels to evaluate theirpacket error rate performances. Then, two of the seven interleaving with betterperformance and the simplest interleaving algorithm, general block interleavingwill be implemented in the TinyOS platform, and they will be compared witheach other from packet error rate, interleaving time and memory consumptionaspects. Experiments show that, for theoretical channel, interleaving plays animportant role to enhance the capability to correct the corrupted packets exceptfor Rayleigh channel, in which the impact of interleaving is generally slight.Meanwhile for the channel under IEEE 802.11b/g interference, interleavingenhance more than 10% PER in the receiver. However for MFA channel, theenhancement is slight, only 1.85%. Convolutional interleaving has the best PERperformance in AWGN channel and the channel with deterministic SER, whilematrix interleaving has the lowest PER in WLAN affected channel. In thelatency and memory consumption aspect, For the same packet length, generalblock interleaving has the shortest interleaving time while matrix interleavinghas the longest. In the same interleaving algorithm, the execution time becomeslonger with growth of packet size. Within the same interleaving method, thelonger the packet size is, the more memory that would be consumed. Under thesame interleaving length, general block interleaving consumes least memoryand convolutional interleaving has the largest memory consumption.

This work studies the problem of indoor navigation, using wireless sensor networks. The knowledge of multiagent systems is being used in the process of solving this problem. Platform WSageNt, running on the operating system TinyOS, is being used for the execution of the agents. Agents themselves on the WSageNt platform are created in the language ALLL, which is described in the process. With use of those technologies, a solution is proposed as an extension to the WSageNt plaform and three agents, which fulfill the desired functionality. Then the implementation of this solution is described, followed by its testing, stating advantages and disadvantages of the created system.

This thesis deals with the issues 6LoWPAN protokolu and implementation of IPv6 on the specied platform. Introduction thesis deals with the explanation of wireless sensor networks. Next it was descibed 6LoWPAN protocol, which maps IPv6 on standard IEEE 802.15.4. The thesis further concentrates to exploration of possible operation systems, that are designed for sensor networks and then followed by comparison of their characteristics and advantages. The fth chapter is focused on he implementation of the operating system to the sensor node Iris, introduction Iris and with the structure of the operating system Contiki OS. At the end of thesis is description of the implementation of this system in the sensor node Iris.

The work deals with processing of radio received signal strength in IEEE 802.15.4 which communicates in 2.4 GHz ISM band. The signal is processed by the three approximation methods. They are tested for their effectiveness for measuring in different radio environments. Furthermore, the work deals with calculation of the most efficient coefficients for distance calculating by radio transmission fucntions. It defines the issues of such solutions on practical examples. The work also deals with the experimental algorithm for implementing dynamic calibration of the coefficients. It describes the design, processing and verification of this system in practice.

This master's thesis describes the software and hardware extension of multiagent platform WSageNt to ensure communication between basestation and web interface Control Panel using GSM network. Sensor node FITmote is used as a basestation and modem Teltonika is used as a interface to GSM. The physical interconnection of the devices implementing the newly created bridge to connect different logic voltage levels of their serial interface. Application for basestation was extended to serial communication with modem. This extend provide communication over GSM network to Internet. Application on control server also was modified for TCP/IP communication.

This thesis is focused on wireless sensor networks and implementation tools for creation and simulation of applications. It describes WSnageNt project, which is intended to support agents in wireless sensor networks. The main objective of this thesis is to extend the WSageNt project with new features that will allow to create agents with more capabilities. These features will be then used to extend the WSageNt project with network node movement tracking capability.

This work deals with implementation of an agent platform, which is able to run agent code in wireless sensor networks. Implementation has been done for MICAz platform, which uses TinyOS operating system for developing applications. This work contains list of chosen TinyOS parts and illustrates, how such a platform can be used for our purposes. We will describe main features of ALLL language and we will also demonstrate some examples of agents.