As integrated circuits become smaller in size, antenna design has become the size limiting factor for RF front ends. The size reduction of an antenna is limited due to tradeoffs between its size and its performance. Thus, combining antenna designs with other system components can reutilize parts of the system and significantly reduce its overall size. The biggest challenge is in minimizing the interference between the antenna and other components so that the radiation performance is not compromised. This is especially true for antenna arrays where the radiation pattern is important. Antenna size reduction is also desired for wireless sensors where the devices need to be unnoticeable to the subjects being monitored. In addition to reducing the interference between components, the environmental effect on the antenna needs to be considered based on sensors' deployment. This dissertation focuses on solving the two challenges: 1) designing compact multi-frequency arrays that maintain directive radiation across their operating bands and 2) developing integrated antennas for sensors that are protected against hazardous environmental conditions. The first part of the dissertation addresses various multi-frequency directive antennas arrays that can be used for base stations, aerospace/satellite applications. A cognitive radio base station antenna that maintains a consistent radiation pattern across the operating frequencies is introduced. This is followed by multi-frequency phased array designs that emphasize light-weight and compactness for aerospace applications. The size and weight of the antenna element is reduced by using paper-based electronics and internal cavity structures. The second part of the dissertation addresses antenna designs for sensor systems such as wireless sensor networks and RFID-based sensors. Solar cell integrated antennas for wireless sensor nodes are introduced to overcome the mechanical weakness posed by conventional monopole designs. This can significantly improve the sturdiness of the sensor from environmental hazards. The dissertation also introduces RFID-based strain sensors as a low-cost solution to massive sensor deployments. With an antenna acting as both the sensing device as well as the communication medium, the cost of an RFID sensor is dramatically reduced. Sensors' strain sensitivities are measured and theoretically derived. Their environmental sensitivities are also investigated to calibrate them for real world applications.

Parkinson’s disease is associated with reduced coordination between respiration and locomotion. For the neurological rehabilitation research, it requires a long-time monitoring system, which enables the online analysis of the patient’s vegetative locomotor coordination. In this work a real time step detector using three-dimensional accelerometer signal for the patients with Parkinson‘s disease is developed. This step detector is a complement for a recently developed system included of intelligent, wirelessly communicating sensors. The system helps to focus on the scientific questions whether this coordination may serve as a measure for the rehabilitation progress of PD patients. / +46-762453110 +46-462886970

Surveillance systems are usually employed to monitor wide areas in which their usersaim to detect and/or observe events or phenomena of their interest. The use ofwireless sensor networks in such systems is of particular interest as these networks can provide a relative low cost and robust solution to cover large areas. Emerging applications in this context are proposing the use of wireless sensor networks composed of both static and mobile sensor nodes. Motivation for this trend is toreduce deployment and operating costs, besides providing enhanced functionalities.The usage of both static and mobile sensor nodes can reduce the overall systemcosts, by making low-cost simple static sensors cooperate with more expensive andpowerful mobile ones. Mobile wireless sensor networks are also desired in somespecific scenarios in which mobility of sensor nodes is required, or there is a specificrestriction to the usage of static sensors, such as secrecy. Despite the motivation,systems that use different combinations of static and mobile sensor nodes are appearing and with them, challenges in their interoperation. This is specially the case for surveillance systems.This work focuses on the proposal of solutions for wireless sensor networks including static and mobile sensor nodes specifically regarding cooperative andcontext aware mission setup and performance. Orthogonally to the setup and performance problems and related cooperative and context aware solutions, the goalof this work is to keep the communication costs as low as possible in the executionof the proposed solutions. This concern comes from the fact that communication increases energy consumption, which is a particular issue for energy constrained sensor nodes often used in wireless sensor networks, especially if battery supplied. Inthe case of the mobile nodes, this energy constraint may not be valid, since their motion might need much more energy. For this type of node the problem incommunicating is related to the links’ instabilities and short time windows availableto receive and transmit data. Therefore, it is better to communicate as little as possible. For the interaction among static and mobile sensor nodes, all thesecommunication constraints have to be considered.For the interaction among static sensor nodes, the problems of dissemination and allocation of sensing missions are studied and a solution that explores local information is proposed and evaluated. This solution uses mobile software agentsthat have capabilities to take autonomous decisions about the mission dissemination and allocation using local context information so that the mission’s requirementscan be fulfilled. For mobile wireless sensor networks, the problem studied is how to perform the handover of missions among the nodes according to their movements.This problem assumes that each mission has to be done in a given area of interest. In addition, the nodes are assumed to move according to different movement patterns,passing through these areas. It is also assumed that they have no commitment in staying or moving to a specific area due to the mission that they are carrying. To handle this problem, a mobile agent approach is proposed in which the agents implement the sensing missions’ migration from node to node using geographical context information to decide about their migrations. For the networks combining static and mobile sensor nodes, the cooperation among them is approached by abiologically-inspired mechanism to deliver data from the static to the mobile nodes.The mechanism explores an analogy based on the behaviour of ants building and following trails to provide data delivery, inspired by the ant colony algorithm. It is used to request the displacement of mobile sensors to a given location according tothe need of more sophisticated sensing equipment/devices that they can provide, so that a mission can be accomplished.The proposed solutions are flexible, being able to be applied to different application domains, and less complex than many existing approaches. The simplicity of the solutions neither demands great computational efforts nor large amounts of memory space for data storage. Obtained experimental results provide evidence of the scalability of these proposed solutions, for example by evaluatingtheir cost in terms of communication, among other metrics of interest for eachsolution. These results are compared to those achieved by reference solutions (optimum and flooding-based), providing indications of the proposed solutions’ efficiency. These results are considered close to the optimum one and significantly better than the ones achieved by flooding-based solutions.

In conjunction with the possibility of inexpensive wireless communication, many products of tomorrow are developed with the support for wireless communication. The technology enables the possibilty of wireless communication to small plattforms at a realistic price. The cheap connectivity allows for great creativity and gives the developers imagination a wide discretion in the development of new products. This thesis aims to evaluate how the serial communication protocol Modbus RTU - RS232, performs and behaves when transported through meshed networks (Atmel lightweight mesh will be used in this thesis). The work was commissioned by M2M Solutions in J¨onk¨oping. The report will answer the following questions1. How does Modbus RTU behaves when transported through a meshed network. 2. How does Modbus RTU preform when transported through Atmel Lightweight Mesh.The authors have chosen to conduct action research to answer established questions. A test system consisting of both hardware and software was designed and created. With this system, several different tests were conducted and the results were observed and subjected to reflection. The different tests varied the distance, the network’s composition and location of the network infrastructure. Through observation of the test system and evaluation of the recorded data conclusions concering Modbus RTU’s performance and behavior during transport in Atmel lightweigh mesh has been drawn. The test system has been designed with the help of clients and previously made research. Modbus behaves nominally during transportation through Atmel lightweight mesh. Before the network is fully established, an inability to transport data has beend observed. The performance is evaluated by the time it takes to send data, the time is greatly affected by the following factors; Network composition and changes in signal strength (that creates changes in transport routes). For each additional node that traffic is transported through an increase of 5-10ms in the responstime was noted. The network’s ability to change the transport route is also expected to increase performance. The wireless communication provides a longer range than during transportation by standard conventional cable.Considering the results, the authors believe that Modbus RTU has the potential for use in transportation through wireless, meshed networks. One possible scenario is when several Modbus RTU masters are beeing used and data needs to be transported over large distances.

Energy harvesting is becoming increasingly important in low-power applications where energy from the environment is used to power the system alone, or to supplement a battery. For example, pulse oximeter sensors inside helmets of road racing cyclists are powered by the sun. These sensors have become smaller and more practical without the limitation of a finite energy supply. Harvested energy from an energy transducer (solar, piezoelectric, etc.) must be maximized to ensure these devices can survive periods where environmental energy is scarce. The conversion process from the transducer to usable power for the device is not perfectly efficient. Specifically, the output voltage of a solar cell is a function of the light intensity, and by extension the load it powers. A small perturbation of the light source quickly diminishes the available power. The wasted power reduces the energy available for the application, and can be improved using an approach called maximum power point tracking (MPPT). This technique maximizes harvesting efficiency by dynamically impedance matching the transducer to its load. This report introduces the Maximum Efficient Solar Harvester (MESH), an MPPT algorithm tuned for a specific Wireless Sensor Network (WSN) application. MESH specifically controls the operation of the DC-DC converter in a solar power management unit (PMU). The control is done by monitoring the available light and feeding that information to choose the optimal operating point DC-DC converter. This operating point has a direct dependency on the overall efficiency of the system. For MESH to be practical, the cost and power overhead of adding this functionality must be assessed. Empirical results indicate that MESH improves the maximum efficiency of the popular Texas Instruments (TI) RF2500-SEH WSN platform by an average of 20%, which far exceeds the power overhead it incurs. The cost is also found to be minimal, as WSN platforms already include a large portion of the hardware required to implement MESH. The report was done in collaboration with Shahil Rais. It covers the hardware components and the bench automation environment; Rais's companion report focuses on software implementation and MESH architecture definition. / text

Τα Δίκτυα Αισθητήρων αποτελούνται από ένα μεγάλο αριθμό μικρών αυτόνομων συσκευών, που αλληλεπιδρούν με το άμεσο περιβάλλον τους μέσω αισθητήρων, επικοινωνούν μεταξύ τους ασύρματα και συνεργάζονται φέροντας εις πέρας εργασίες που δε θα μπορούσε να ολοκληρώσει μία μόνο συσκευή. Κάθε συσκευή του δικτύου διαθέτει περιορισμένη υπολογιστική δύναμη και ενεργειακούς πόρους, επομένως η όσο το δυνατόν λιγότερη κατανάλωση ενέργειας είναι βασικό πρόβλημα των δικτύων αισθητήρων για τη μεγιστοποίηση του χρόνου ζωής τους. Συνήθως τα δίκτυα αισθητήρων αναπτύσσονται σε μεγάλες περιοχές ενδιαφέροντος για την υποστήριξη σημαντικών εφαρμογών του πραγματικού κόσμου. Η πληροφορία που ανιχνεύεται από τους κόμβους αισθητήρων προωθείται προς ένας σταθερό, συνήθως, κέντρο ελέγχου, με αναμεταδόσεις των δεδομένων στους ενδιάμεσους κόμβους. Η διαδικασία αυτή έχει ως αποτέλεσμα τη μεγάλη κατανάλωση ενέργειας στις συσκευές, ιδιαίτερα σε αυτές που βρίσκονται κοντά στο κέντρο ελέγχου, αφού πρέπει να αναμεταδίδουν και τα δεδομένα που φτάνουν από το υπόλοιπο δίκτυο προς το κέντρο ελέγχου. Για την επίτευξη μιας πιο ισορροπημένης και αποδοτικής διαδικασίας συλλογής δεδομένων, τα τελευταία χρόνια έχει υιοθετηθεί μια νέα προσέγγιση, όπου το κέντρο ελέγχου είναι κινητό. Η βασική ιδέα είναι ότι το κέντρο ελέγχου διαθέτει σημαντικά και εύκολα ανανεώσιμα αποθέματα ενέργειας, επομένως μπορεί να κινείται στην περιοχή όπου έχει αναπτυχθεί το δίκτυο αισθητήρων, αναλαμβάνοντας να συλλέξει τα δεδομένα από τους κόμβους με πολύ μικρό κόστος. Ωστόσο, η μετάδοση των δεδομένων μπορεί να παρουσιάζει σημαντικές καθυστερήσεις. Στην παρούσα εργασία αναπτύχθηκαν πρωτόκολλα ελέγχου της κίνησης ενός κέντρου ελέγχου σε δίκτυο αισθητήρων με ανομοιογενή ανάπτυξη των κόμβων αισθητήρων, με στόχο την αποδοτική, ως προς την ενέργεια και τον χρόνο παράδοσης, συλλογή των δεδομένων. Συγκεκριμένα, το κέντρο ελέγχου διαιρεί νοητά το δίκτυο σε περιοχές τις οποίες και επισκέπτεται διαδοχικά, σταματώντας σε κάθε περιοχή για ένα συγκεκριμένο χρονικό διάστημα, ώστε να συλλέξει τα δεδομένα. Προτείνουμε δύο τρόπους κίνησης του κέντρου ελέγχου, ντετερμινιστικό και τυχαίο. Στην τυχαία κίνηση, η επιλογή της επόμενης περιοχής την οποία θα επισκεφτεί το κέντρο ελέγχου γίνεται με τυχαίο τρόπο, εισάγοντας όμως ένα όρο μεροληψίας, έτσι ώστε να προτιμούνται περιοχές που έχουν δεχτεί λιγότερες επισκέψεις. Επιπλέον η μέθοδός μας αποφασίζει το χρόνο παύσης σε κάθε περιοχή λαμβάνοντας υπόψιν κάποιες βασικές παραμέτρους του δικτύου, όπως τα αρχικά αποθέματα ενέργειας των κόμβων αισθητήρων και την πυκνότητα της κάθε περιοχής, έτσι ώστε να παραμένει περισσότερο χρόνο σε περιοχές με μεγαλύτερη πυκνότητα, άρα και μεγαλύτερη ποσότητα πληροφορίας. Με τον τρόπο αυτό επιτυγχάνεται η γρήγορη κάλυψη όλου του δικτύου, καθώς επίσης και η δίκαιη εξυπηρέτηση των επιμέρους περιοχών του δικτύου. Τα προτεινόμενα πρωτόκολλα αξιολογήθηκαν πειραματικά μέσω προσομοίωσης, χρησιμοποιώντας ποικίλες τιμές για βασικές παραμέτρους του δικτύου και σύγκρινοντάς τα με σχετικές υπάρχουσες ευρέως αποδεκτές μεθόδους. Τα αποτελέσματα που πήραμε δείχνουν ότι τόσο ο χρόνος παράδοσης των μηνυμάτων, όσο και η ενέργεια που καταλώθηκε διατηρούνται σε χαμηλά επίπεδα, βελτιώνοντας σημαντικά την προηγούμενη σχετική έρευνα. / Wireless Sensor Networks consist of a large number of small, autonomous devices, that are able to interact with their inveronment by sensing and collaborate to fulfill their tasks, as, usually, a single node is incapable of doing so; and they use wireless communication to enable this collaboration. Each device has limited computational and energy resources, thus a basic issue in the applicastions of wireless sensor networks is the low energy consumption and hence, the maximization of the network lifetime. The collected data is disseminated to a static control point – data sink in the network, using node to node - multi-hop data propagation. However, sensor devices consume significant amounts of energy in addition to increased implementation complexity, since a routing protocol is executed. Also, a point of failure emerges in the area near the control center where nodes relay the data from nodes that are farther away. Recently, a new approach has been developed that shifts the burden from the sensor nodes to the sink. The main idea is that the sink has significant and easily replenishable energy reserves and can move inside the area the sensor network is deployed, in order to acquire the data collected by the sensor nodes at very low energy cost. However, the need to visit all the regions of the network may result in large delivery delays. In this work we have developed protocols that control the movement of the sink in wireless sensor networks with non-uniform deployment of the sensor nodes, in order to succeed an efficient (with respect to both energy and latency) data collection. More specifically, a graph formation phase is executed by the sink during the initialization: the network area is partitioned in equal square regions, where the sink, pauses for a certain amount of time, during the network traversal, in order to collect data. We propose two network traversal methods, a deterministic and a random one. When the sink moves in a random manner, the selection of the next area to visit is done in a biased random manner depending on the frequency of visits of its neighbor areas. Thus, less frequently visited areas are favored. Moreover, our method locally determines the stop time needed to serve each region with respect to some global network resources, such as the initial energy reserves of the nodes and the density of the region, stopping for a greater time interval at regions with higher density, and hence more traffic load. In this way, we achieve accelerated coverage of the network as well as fairness in the service time of each region.Besides randomized mobility, we also propose an optimized deterministic trajectory without visit overlaps, including direct (one-hop) sensor-to-sink data transmissions only. We evaluate our methods via simulation, in diverse network settings and comparatively to related state of the art solutions. Our findings demonstrate significant latency and energy consumption improvements, compared to previous research.

Three information measures are discussed and used as objective functions for optimization of wireless sensor networks (WSNs) and radar systems. In addition, a long-term system performance measure is developed for evaluating the performance of slow-fading WSNs. Three system applications are considered: a distributed detection system, a distributed multiple hypothesis system, and a radar target recognition system.First, we consider sensor power optimization for distributed binary detection systems. The system communicates over slow-fading orthogonal multiple access channels. In earlier work, it was demonstrated that system performance could be improved by adjusting transmit power to maximize the J-divergence measure of a binary detection system. We define outage probability for slow-fading system as a long-term performance measure, and analytically develop the detection outage with the given system model.Based on the analytical result of the outage probability, diversity gain is derived and shown to be proportional to the number of the sensor nodes. Then, we extend the optimized power control strategy to a distributed multiple hypothesis system, and enhance the power optimization by exploiting a priori probabilities and local sensor statistics. We also extend outage probability to the distributed multiple-hypotheses problem. The third application is radar waveform design with a new performance measure: Task-Specific Information (TSI). TSI is an information-theoretic measure formulated for one or more specific sensor tasks by encoding the task(s) directly into the signal model via source variables. For example, we consider the problem of correctly classifying a linear system from a set of known alternatives, and the source variable takes the form of an indicator vector that selects the transfer function of the true hypothesis. We then compare the performance of TSI with conventional waveforms and other information-theoretic waveform designs via simulation. We apply radar-specific constraints and signal models to the waveform optimization.

Wireless Sensor Networks (WSNs) have significant potential in many application domains, and are poised for growth in many markets ranging from agriculture and animal welfare to home and office automation. Although sensor network deployments have only begun to appear, the industry still awaits the maturing of this technology to realize its full benefits. The main constraints to large scale commercial adoption of sensor networks are the lack of available network management and control tools for determining the degree of data aggregation prior to transforming it into useful information, localizing the sensors accurately so that timely emergency actions can be taken at exact location, and scheduling data packets so that data are sent based on their priority and fairness. Moreover, due to the limited communication range of sensors, a large geographical area cannot be covered, which limits sensors application domain. Thus, we investigate a scalable and flexible WSN architecture that relies on multi-modal nodes equipped with IEEE 802.15.4 and IEEE 802.11 in order to use a Wi-Fi overlay as a seamless gateway to the Internet through WiMAX networks. We focus on network management approaches such as sensors localization, data scheduling, routing, and data aggregation for the WSN plane of this large scale multimodal network architecture and find that most existing approaches are not scalable, energy efficient, and fault tolerant. Thus, we introduce an efficient approach for each of localization, data scheduling, routing, and data aggregation; and compare the performance of proposed approaches with existing ones in terms of network energy consumptions, localization error, end-to-end data transmission delay and packet delivery ratio. Simulation results, theoretical and statistical analysis show that each of these approaches outperforms the existing approaches. To the best of our knowledge, no integrated network management solution comprising efficient localization, data scheduling, routing, and data aggregation approaches exists in the literature for a large scale WSN. Hence, we e±ciently integrate all network management components so that it can be used as a single network management solution for a large scale WSN, perform experimentations to evaluate the performance of the proposed framework, and validate the results through statistical analysis. Experimental results show that our proposed framework outperforms existing approaches in terms of localization energy consumptions, localization accuracy, network energy consumptions and end-to-end data transmission delay.

Cellular automata (CA) are an interesting computation medium to study because of their simplicity and inherently parallel operation. These characteristics make them a useful and efficient computation tool for applications such as cryptography and physical systems modelling, particularly when implemented on specialized parallel hardware. In this dissertation, we study a number of applications of CA and develop new theoretical results used for them. We begin by presenting conditions which guarantee that a composition of marker cellular automata has the same neighbourhood as each of the individual components. We show that, under certain technical assumptions, a marker cellular automaton has a unique inverse with a given neighbourhood. We use these results to develop a working key generation algorithm for a public-key cryptosystem based on reversible cellular automata originally conceived by Kari. We also give an improvement to a CA algorithm which solves a version of the convex hull problem, ensuring that the algorithm does not require a global rule change and correcting the operation in a special case. Finally, we study a modified version of an established CA-based car traffic flow model for the single-lane highway case, and use CA as a modelling tool to investigate the coverage problem in wireless sensor network design. We developed functional software implementations for all of these experiments. / Thesis (Master, Computing) -- Queen's University, 2009-03-23 11:20:58.666

Wireless Sensor Network (WSN) is a widely researched technology that has applications in a broad variety of fields ranging from medical, industrial, automotive and pharmaceutical to even office and home environments. It is composed of a network of self-organizing sensor nodes that operate in complex environments without human intervention for long periods of time. The energy available to these nodes, usually in the form of a battery, is very limited. Consequently, energy saving algorithms that maximize the network lifetime are sought-after. Link adaptation polices can significantly increase the data rate and effectively reduce energy consumption. In this sense, they have been studied for power optimization in WSNs in recent research proposals. In this thesis, we first examine the Adaptive Modulation (AM) schemes for flat-fading channels, with data rate and transmit power varied to achieve minimum energy consumption. Its variant, Adaptive Modulation with Idle mode (AMI), is also investigated. An Adaptive Sleep with Adaptive Modulation (ASAM) algorithm is then proposed to dynamically adjust the operating durations of both the transmission and sleep stages based on channel conditions in order to minimize energy consumption. Furthermore, adaptive power allocation schemes are developed to improve energy efficiency for multi-hop relay networks. Experiments indicate that a notable reduction in energy consumption can be achieved by jointly considering the data rate and the transmit power in WSNs. The proposed ASAM algorithm considerably improves node lifetime relative to AM and AMI. Channel conditions play an important role in energy consumption for both AM and ASAM protocols. In addition, the number of modulation stages is also found to substantially affect energy consumption for ASAM. Node lifetime under different profiles of traffic intensity is also investigated. The optimal power control values and optimal power allocation factors are further derived for single-hop networks and multi-hop relay networks, respectively. Results suggest that both policies are more suitable for ASAM than for AM. Finally, the link adaptation techniques are evaluated based on the power levels of commercial IEEE 802.15.4-compliant transceivers, and ASAM consistently outperforms AM and AMI in terms of energy saving, resulting in substantially longer node lifetime. / Thesis (Master, Electrical & Computer Engineering) -- Queen's University, 2011-02-08 18:26:29.222