An antenna for a wireless sensor network for trains is designed and built. The network will monitor temperature and vibrations of the wheel bearings on the train wagons. Doing this will allow for an earlier detection of damaged wheels, which will ease planning of maintenance and reduce wear on the rails considerably. The requirement of the system is that it is to be installed without any cables attached to the sensor nodes. This calls for wireless communication, and that for that antennas are needed.A train is a difficult environment to transmit electromagnetic (EM) waves in. It is full of metal and EM-waves cannot pass through a conducting material. Having much metal in its vicinity also affects the function of the antenna. This needs to be taken into consideration when making the design.The constructed antenna is a small dual-layer patch antenna. Dual layer means that it is constructed out of two sheets known as substrates of isolating material with different characteristics. The lower one of these substrates is made in such a way that integration with a circuit board is possible. Such integration would reduce the production cost considerably. The antenna is designed for direct placement on a conducting surface. This surface could be part of the train. It uses the surrounding metal as a ground plane in order to reduce its size. The result is a small patch antenna with good radiation qualities in metallic surroundings. The longest side is 18.35 mm, equaling 14.9 % of the wavelength that the antenna is designed for. / WISENET

The technology for the realization of wireless sensors has been available for a long time, but due to progress  and  development  in  electrical  engineering  such  sensors  can  be  manufactured  cost effectively  and  in  large  numbers  nowadays.  This  availability  and  the  possibility  of  creating cooperating  wireless  networks  which  consist  of  such  sensors  nodes,  has  led  to  a  rapidly  growing popularity  of  a  technology  named  Wireless  Sensor  Networks  (WSN).  Its  disadvantage  is  a  high complexity in the task of programming applications based on WSN, which is a result of its distributed and  embedded  characteristic.  To  overcome  this  shortcoming,  software  agents  have  been  identified as  a  suitable  programming  paradigm.  The  agent  based  approach  commonly  uses  a  middleware  for the execution of the software agent. This thesis is meant to compare such agent middleware in their performance in the WSN domain. Therefore two prototypes of applications based on different agent models are implemented for a given set of middleware. After the implementation measurements are extracted  in  various  experiments,  which  give  information  about  the  runtime  performance  of  every middleware in the test set.  In the following analysis it is examined whether each middleware under test  is  suited  for  the  implemented  applications  in  WSN.  Thereupon,  the  results  are  discussed  and compared with the author’s expectations. Finally a short outlook of further possible development and improvements is presented.

Wireless sensor networks have attracted the interest of the process industry. A process plant typically contains thousands of devices, monitoring or controlling the process. Today, all these devices are usually connected with wires. Using wireless technology simplifies deployment of new devices in a network and eliminates the need for extensive wiring. But wireless communication is also more sensitive than its wired counterpart. Therefore work is needed to make wireless sensor networks a viable option in many applications. Important issues are, for example, robustness, energy efficiency, and latency. One of the leading communication protocols for industrial wireless sensor networks is the WirelessHART protocol. This thesis investigates three ways of improving performance of the protocol, in terms of reliability and energy requirements. First, the structure of a WirelessHART packet is studied and the removal of certain fields is suggested to make the communication overhead smaller. Second, forward error correcting codes are evaluated using simulations in MATLAB. Third, measurement experiments in actual industrial environments are conducted where radio signals are transmitted and received. The variability of the received signal strength is measured and the effect that polarization diversity has on the signal variability is analyzed. The findings indicate that substantial improvements can be attained by employing polarization diversity, which can reduce channel variability and increase the expected signal strength significantly. The improvements in channel gain can be on the order of several tens of dB. The evaluations of forward error correcting codes show that the reliability is improved, with a channel gain of 3 dB. The study of the WirelessHART packet structure indicate that the packet sizes can be reduced by 15%. In turn, this also reduces energy requirements and packet error rates by 15%. This is equivalent to a gain in SNR on the order of a tenth of a dB.

The objective of the presented report focuses on the data acquisition of pressure and heart beat rates from external sensors over the TinyOS 2.x platform. This sensing application may be used in the e-health care field in order to sample the data information. The designed test-bed consists of several hardware devices, containing an MIB520CB USB interface board, two MICAz motes, an MDA300CA data acquisition board and external sensors for the pressure and heart beat rate. The programming language is NesC,which is used to build applications under the TinyOS 2.x environment. Data information is sampled from the external sensors, and this is then realized by the mote via the on-board ADC channel. The values are then transferred from one mote to another over radio communication. Finally, the expected results are transmitted to the PC by using serial communication. The report also discusses the sensing outcomes in order to determine the practical usage of the sensor devices. This project represents a common sensing application in wireless sensor networks, demonstrating a small case within the e-health care monitoring system. In order to meet the specific demands and to save resources, the wireless sensor networks are widely used in various applications. The designed test-bed could be also deployed as a part of larger-scale wireless sensor networks in order to achieve the requirements in relation to the sensing data information for further detailed use in future work.

Wireless sensor networks (WSN) have generated tremendous interest among researchers these years because of their potential usage in a wide variety of applications.<p> Sensor nodes are inexpensive portable devices with limited processing power and energy resources. Sensor nodes can be used to collect information from the environment, locally process this data and transmit the sensed data back to the user.<p> This thesis proposes a new reliable data delivery protocol for general point-to-point data delivery (unicasting) in wireless sensor networks. The new protocol is designed that aims at providing 100% reliability when possible as well as minimizing overhead and network delay. The design of the new protocol includes three components. The new protocol adopts a NACK-based hop-by-hop loss detection and recovery scheme using end-to-end sequence numbers. In order to solve the single/last packet problem in the NACK-based approach, a hybrid ACK/NACK scheme is proposed where an ACK-based approach is used as a supplement to the NACK-based approach to solve the single/last packet problem. The proposed protocol also has a new queue management scheme that gives priority to new data. By introducing the idea of a Ready_Bit and newer packet first rule in the transmission queue, nodes can detect and recover lost packets in parallel with the normal data transmission process. The performance of the new protocol is tested in a Crossbow MicaZ testbed. Experimental results show that the new protocol performs well under various system and protocol parameter settings.

In this thesis, we present analytical analysis of key distribution schemes on wireless sensor networks. Since wireless sensor network is under unreliable environment, many random key pre-distribution based schemes have been developed to enhance security. Most of these schemes need to guarantee the existence of specific properties, such as disjoint secure paths or disjoint secure cliques, to achieve a secure cooperation among nodes. Two of the basic questions are as follows: 1. Under what conditions does a large-scale sensor network contain a certain structure? 2. How can one give a quantitative analysis behave as n grows to the infinity? However, analyzing such a structure or combinatorial problem is complicated in classical wireless network models such as percolation theories or random geometric graphs. Particularly, proofs in geometric setting models often blend stochastic geometric and combinatorial techniques and are more technically challenging. To overcome this problem, an approximative quasi-random graph is employed to eliminate some properties that are difficult to tackle. The most well-known solutions of this kind problems are probably Szemeredi's regularity lemma for embedding. The main difficulty from the fact that the above questions involve extremely small probabilities. These probabilities are too small to estimate by means of classical tools from probability theory, and thus a specific counting methods is inevitable.

In the literature, most distributed detection developed so far mainly focuses on the test rule based on fixed sample size. However, in the real situations, sequential tests are more suitable to be utilized since it might achieve the same detection performance by using fewer number of samples as compared with the fixed-sample-size test. Thus, this theses will propose a new distributed sequential detection approach for the applications in wireless sensor networks(WSNs) and cognitive radios(CRs). First we refer to the sequential detection, and it has been developed by Wald in 1994, which is well known as the sequential probability ratio test (SPRT). The SPRT is proved to be able to decrease the required average sample numbers or reducing the average detection time. Indeed, the SPRT is the optimal sequential detection in terms of the minimizing the required number of samples given the constraint of false alarm and miss probabilities when the observation samples are independent and identical distributed (i.i.d.). However, if the observation samples are not dentically distributed, by simulation results show that the SPRT is not the optimal test. Based on a heuristic approach, this thesis then developed a new distributed detection scheme based on the sorted samples. Finally , the simulation results obtained by this thesis shows that the proposed scheme can further reduce the number of samples required for making the final decision as compared with SPRT.

Clustering schemes can reduce energy consumption, prolong network lifetime and improve scalability in wireless sensor networks (WSNs). In a typical cluster-based WSN, sensor nodes are organized into clusters. Each cluster elects a cluster head (CH) node. The CH is responsible for collecting the sensed data from cluster members, aggregating data and transmitting data to the sink node via a multi-hop path through intermediate CHs. Thus, the use of cluster techniques not only shortens the transmission distances for sensor nodes but also reduces energy consumption; however, each cluster imposes a larger load on the CH. Under this situation, CHs closer to the sink node tend to use up their batteries faster than those farther away from the sink node due to imbalanced traffics among CHs. To overcome this problem, we contribute to the energy balancing issues in WSNs from two aspects. In the first work, we first analyze the corona model. Based on analysis results, we found that nearly balanced energy consumption of WSNs can be achieved with the additional help of arranging different initial conditions. We then propose the Energy-balanced Node Deployment with Balanced Energy (END-BE) scheme and Energy-balanced Node Deployment with Maximum Life-Time (END-MLT) scheme, which determine the cluster density for each corona according to the energy consumption of each CH. Simulation results show that energy consumption is nearly balanced by implementing END-BE, and the network lifetime is greatly improved by adopting END-MLT. In the second work, we development a novel cluster-based routing protocol for corona-structured wireless sensor networks in order to balance the energy consumption among CHs. Based on the relaying traffic of each CH conveys, adequate radius for each corona can be determined through nearly balanced energy depletion analysis, which leads to balanced energy consumption among CHs. Simulation results demonstrate that our clustering approach effectively improves the network lifetime, residual energy and reduces the number of CH rotations in comparison with the Multi-Layer Clustering Routing Algorithm (MLCRA).

A local reconfiguration algorithm (INP) for reliable routing in wireless sensor networks that consist of many static (fixed) energy-constrained nodes is introduced in the dissertation. For routing around crash fault nodes, a communication tree structure connecting sensor nodes to the base station (sink or root) is dynamically reconfigured during information dissemination. Unlike other location based routing approaches, INP does not take any support from a high costing system that gives position information such as GPS. For reconfigurations, INP uses only local relational information in the tree structure among nearby nodes by collaboration between the nodes that does not need global maintenance, so that INP is energy efficient and it scales to large sensor networks. The performance of the algorithm is compared to the single path with repair routing scheme (SWR) that uses a global metric and the modified GRAdient broadcast scheme (GRAB-F) that uses interleaving multiple paths by computation and by simulations. The comparisons demonstrate that using local relative information is mostly enough for reconfigurations, and it consumes less energy and mostly better delivery rates than other algorithms especially in dense environments. For the control observer to know the network health status, two new diagnosis algorithms (Repre and Local) that deal with crash faults for wireless sensor networks are also introduced in the dissertation. The control observer knows not only the static faults found by periodic testing but also the dynamic faults found by a path reconfiguration algorithm like INP that is invoked from evidence during information dissemination. With based on this information, the control observer properly treats the network without lateness. Local algorithm is introduced for providing scalability to reduce communication energy consumption when the network size grows. The performance of these algorithms is computationally compared with other crash faults identification algorithm (WSNDiag). The comparisons demonstrate that maintaining the communication tree with local reconfigurations in Repre and Local needs less energy than making a tree per each diagnosis procedure in WSNDiag. They also demonstrate that providing scalability in Local needs less energy than other approaches.

Pulse synchronization is the evolution of spontaneous firing action across a network of sensor nodes. In the pulse synchronization model all nodes across a network produce a pulse, or "fire", at regular intervals even without access to a shared global time. Previous researchers have proposed the Reachback Firefly algorithm for pulse synchronization, in which nodes react to the firings of other nodes by changing their period. We propose an extension to this algorithm for tolerating arbitrary or Byzantine faults of nodes. Our algorithm queues up all the firings heard in the current cycle and discards outliers at the end of the cycle. An adjustment is computed with the remaining values and used as a starting point of the next cycle. Through simulation we validate the performance of our algorithm and study the overhead in terms of convergence time and periodicity. The simulation considers two specific kinds of Byzantine faults, the No Jump model where faulty nodes follow their own firing cycle without reacting to firings heard from other nodes and the Random Jump model where faulty nodes fire at any random time in their cycle.