This dissertation presents contributions to the fields of mobility modeling, wireless sensor networks (WSNs) with mobile sinks, and opportunistic communication in theme parks. The two main directions of our contributions are human mobility models and strategies for the mobile sink positioning and communication in wireless networks. The first direction of the dissertation is related to human mobility modeling. Modeling the movement of human subjects is important to improve the performance of wireless networks with human participants and the validation of such networks through simulations. The movements in areas such as theme parks follow specific patterns that are not taken into consideration by the general purpose mobility models. We develop two types of mobility models of theme park visitors. The first model represents the typical movement of visitors as they are visiting various attractions and landmarks of the park. The second model represents the movement of the visitors as they aim to evacuate the park after a natural or man-made disaster. The second direction focuses on the movement patterns of mobile sinks and their communication in responding to various events and incidents within the theme park. When an event occurs, the system needs to determine which mobile sink will respond to the event and its trajectory. The overall objective is to optimize the event coverage by minimizing the time needed for the chosen mobile sink to reach the incident area. We extend this work by considering the positioning problem of mobile sinks and preservation of the connected topology. We propose a new variant of p-center problem for optimal placement and communication of the mobile sinks. We provide a solution to this problem through collaborative event coverage of the WSNs with mobile sinks. Finally, we develop a network model with opportunistic communication for tracking the evacuation of theme park visitors during disasters. This model involves people with smartphones that store and carry messages. The mobile sinks are responsible for communicating with the smartphones and reaching out to the regions of the emergent events.

Sensing and analysis of a structure for the purpose of detecting, tracking, and evaluating damage and deterioration, during both regular operation and extreme events, is referred to as Structural Health Monitoring (SHM). SHM is a multi-disciplinary field, with a complete system incorporating sensing technology, hardware, signal processing, networking, data analysis, and management for interpretation and decision making. However, many of these processes and subsequent integration into a practical SHM framework are in need of development. In this study, various components of an SHM system will be investigated. A particular focus is paid to the investigation of a previously developed damage detection methodology for global condition assessment of a laboratory structure with a decking system. First, a review of some of the current SHM applications, which relate to a current UCF Structures SHM study monitoring a full-scale movable bridge, will be presented in conjunction with a summary of the critical components for that project. Studies for structural condition assessment of a 4-span bridge-type steel structure using the SHM data collected from laboratory based experiments will then be presented. For this purpose, a time series analysis method using ARX models (Auto-Regressive models with eXogeneous input) for damage detection with free response vibration data will be expanded upon using both wired and wireless acceleration data. Analysis using wireless accelerometers will implement a sensor roaming technique to maintain a dense sensor field, yet require fewer sensors. Using both data types, this ARX based time series analysis method was shown to be effective for damage detection and localization for this relatively complex laboratory structure. Finally, application of the proposed methodologies on a real-life structure will be discussed, along with conclusions and recommendations for future work

Surface acoustic wave (SAW) devices are a solution for today’s ever growing need for passive wireless sensors. Orthogonal frequency coding (OFC) together with time division multiplexing (TDM) provides a large number of codes and coding algorithms producing devices that have excellent collision properties. Novel SAW noise-like re- flector (NLR) structures with pulse position modulation (PPM) are shown to exhibit good auto- and cross-correlation, and anti-collision properties. Multi-track, multi-transducer approaches yield devices with adjustable input impedances and enhanced collision properties for OFC TDM SAW sensor devices. Each track-transducer is designed for optimum performance for loss, coding, and chip reflectivity. Experimental results and theoretical predictions confirm a constant Q for SAW transducers for a given operational bandwidth, independent of device and transducer embodiment. Results on these new NLR SAW structures and devices along with a new novel 915 MHz transceiver based on a software radio approach was designed, built, and analyzed. Passive wireless SAW temperature sensors were interrogated and demodulated in a spread spectrum correlator system using a new adaptive filter. The first-ever SAW OFC four-sensor operation was demonstrated at a distance of 1 meter and a single sensor was shown to operate up to 3 meters. Comments on future work and directions are also presented

In recent years, the development of a large variety of mobile computing devices has led to wide scale deployment and use of wireless ad hoc and sensor networks. Wireless Sensor Networks consist of battery powered, tiny and cheap "motes", having sensing and wireless communication capabilities. Although wireless motes have limited battery power, communication and computation capabilities, the range of their application is vast. In the first part of the dissertation, we have addressed the specific application of Biomedical Sensor Networks. To solve the problem of data routing in these networks, we have proposed the Adaptive Least Temperature Routing (ALTR) algorithm that reduces the average temperature rise of the nodes in the in-vivo network while routing data efficiently. For delay sensitive biomedical applications, we proposed the Hotspot Preventing Routing (HPR) algorithm which avoids the formation of hotspots (regions having very high temperature) in the network. HPR forwards the packets using the shortest path, bypassing the regions of high temperature and thus significantly reduces the average packet delivery delay, making it suitable for real-time applications of in-vivo networks. We also proposed another routing algorithm suitable for being used in a network of id-less biomedical sensor nodes, namely Routing Algorithm for networks of homogeneous and Id-less biomedical sensor Nodes (RAIN). Finally we developed Biocomm, a cross-layer MAC and Routing protocol co-design for Biomedical Sensor Networks, which optimizes the overall performance of an in-vivo network through cross-layer interactions. We performed extensive simulations to show that the proposed Biocomm protocol performs much better than the other existing MAC and Routing protocols in terms of preventing the formation of hotspots, reducing energy consumption of nodes and preventing network congestion when used in an in-vivo network. In the second part of the dissertation, we have addressed the problems of habitat-monitoring sensor networks, broadcast algorithms for sensor networks and the congestion problem in sensor networks as well as one non-sensor network application, namely, on-chip communication networks. Specifically, we have proposed a variation of HPR algorithm, called Hotspot Preventing Adaptive Routing (HPAR) algorithm, for efficient data routing in Networks On-Chip catering to their specific hotspot prevention issues. A protocol similar to ALTR has been shown to perform well in a sensor network deployed for habitat monitoring. We developed a reliable, low overhead broadcast algorithm for sensor networks namely Topology Adaptive Gossip (TAG) algorithm. To reduce the congestion problem in Wireless Sensor Networks, we proposed a tunable cross-layer Congestion Reducing Medium Access Control (CRMAC) protocol that utilizes buffer status information from the Network layer to give prioritized medium access to congested nodes in the MAC layer and thus preventing congestion and packet drops. CRMAC can also be easily tuned to satisfy different application-specific performance requirements. With the help of extensive simulation results we have shown how CRMAC can be adapted to perform well in different applications of Sensor Network like Emergency Situation that requires a high network throughput and low packet delivery latency or Long-term Monitoring application requiring energy conservation.

A proof of concept is created that demonstrates how low-cost sensors and a simple software solution can be used to proactively detect IED placement. The main goal is to detect suspicious behavior; Specifically we derive requirements that loitering, meandering, improper location and object placement shall be detected. Current methods being used to detect Improvised Explosive Devices (IEDs) are costly in terms of equipment and risk to life, and many are retroactive; IED detection occurs long after explosives are placed. A prototype system is explored with the quality attributes of being low-cost, proactive and using simple software methods. A wireless sensor network of simple sensors may alert authorities to people in the act of placing IEDs. Previous work with Crossbow Motes showed that a network of infrared motion sensors can be used to detect loitering. In this prototype nine other sensors are reverse engineered to determine their true operating specifications. Then a prototype sensor network is developed to explore which low-cost sensors can be used to detect suspicious behavior. The results indicate that five low-cost sensors are effective in detecting suspicious behavior: infrared motion, infrared distance, light, force sensors and pressure sensors meet our requirements.

Energy consumption is one of the most constrained requirements for the development and implementation of wireless sensor networks. Many design aspects affect energy consumption, ranging from the hardware components, operations of the sensors, the communication protocols, the application algorithms, duty cycles and others. Efficient simulation tool can be used to estimate the contribution to energy consumption of all of these factors, and significantly decrease the efforts and time spent to choose the right solution that fits best to a particular application. In this work we present design space exploration methodology for ultra low power embedded systems and wireless sensor networks. The methodology takes inspiration from Platform Based Design (PBD) paradigm and defines separate abstraction layers for all system aspects that directly contribute power consumption of target applications. To support presented methodology we built a SystemC-based discrete event simulation framework, called “PASES”, that provides power-aware simulation and analysis of wireless sensor networks and sensor nodes. Its modular architecture allows flexible, extensible and rapid modeling of custom HW platforms, SW application models, communication protocols, energy sources, environment dynamics and nodes mobility. Based on the feedback gained from PASES, the optimal and energy-efficient solution for the specific project of interest can be selected. The proposed approach improves state-of-the-art by providing fast and reliable power-aware system-level exploration for a wide range of custom applications

Sensor nodes are deployed over sensing fields for the purpose of monitoring certain phenomena of interest. The sensor nodes perform specific measurements, process the sensed data, and send the data to a base station over a wireless channel. The base station collects data from the sensor nodes, analyses this data, and reports it to the users. Wireless sensor networks are different from traditional networks, because of the following constraints. Typically, a large number of sensor nodes need to be randomly deployed and, in most cases, they are deployed in unreachable environments; however, the sensor nodes may fail, and they are subject to power constraints. Energy is one of the most important design constraints of wireless sensor networks. Energy consumption, in a sensor node, occurs due to many factors, such as: sensing the environment, transmitting and receiving data, processing data, and communication overheads. Since the sensor nodes behave as router nodes for data propagation, of the other sensor nodes to the base station, network connectivity decreases gradually. This may result in disconnected sub networks of sensor nodes. In order to prolong the network¿s lifetime, energy efficient protocols should be designed for the characteristics of the wireless sensor network. Sensor nodes in different regions of the sensing field can collaborate to aggregate the data that they gathered. Data aggregation is defined as the process of aggregating the data from sensor nodes to reduce redundant transmissions. It reduces a large amount of the data traffic on the network, it requires less energy, and it avoids information overheads by not sending all of the unprocessed data throughout the sensor network. Grouping sensor nodes into clusters is useful because it reduces the energy consumption. The clustering technique can be used to perform data aggregation. The clustering procedure involves the selection of cluster heads in each of the cluster, in order to coordinate the member nodes. The cluster head is responsible for: gathering the sensed data from its cluster¿s nodes, aggregating the data, and then sending the aggregated data to the base station. An adaptive clustering protocol was introduced to select the heads in the wireless sensor network. The proposed clustering protocol will dynamically change the cluster heads to obtain the best possible performance, based on the remaining energy level of sensor nodes and the average energy of clusters. The OMNET simulator will be used to present the design and implementation of the adaptive clustering protocol and then to evaluate it. This research has conducted extensive simulation experiments, in order to fully study and analyse the proposed energy efficient clustering protocol. It is necessary for all of the sensor nodes to remain alive for as long as possible, since network quality decreases as soon as a set of sensor nodes die. The goal of the energy efficient clustering protocol is to increase the lifetime and stability period of the sensor network. This research also introduces a new bidirectional data gathering protocol. This protocol aims to form a bidirectional ring structure among the sensor nodes, within the cluster, in order to reduce the overall energy consumption and enhance the network¿s lifetime. A bidirectional data gathering protocol uses a source node to transmit data to the base station, via one or more multiple intermediate cluster heads. It sends data through energy efficient paths to ensure the total energy, needed to route the data, is kept to a minimum. Performance results reveal that the proposed protocol is better in terms of: its network lifetime, energy dissipation, and communication overheads.

Wireless sensor network (WSN) technology has gained significant importance due to its potential support for a wide range of applications. Most of the WSN applications consist of a large numbers of distributed nodes that work together to achieve common objects. Running a large number of nodes requires an efficient mechanism to bring them all together in order to form a multi-hop wireless network that can accomplish some specific tasks. Even with recent developments made in WSN technology, numbers of important challenges still stand as vulnerabilities for WSNs, including energy waste sources, synchronisation leaks, low network capacity and self-configuration difficulties. However, energy efficiency remains the priority challenging problem due to the scarce energy resources available in sensor nodes. These concerns are managed by medium access control (MAC) layer protocols. MAC protocols designed specifically for WSN have an additional responsibility of managing radio activity to conserve energy in addition to the traditional functions. This thesis presents advanced research work carried out in the context of saving energy whilst achieving the desired network performance. Firstly the thesis contributes by proposing Overlapped Schedules for MAC layer, in which the schedules of the neighbour clusters are overlapped by introducing a small shift time between them, aiming to compensate the synchronisation errors. Secondly, this thesis proposed a modified architecture derived from S-MAC protocol which significantly supports higher traffic levels whilst achieving better energy efficiency. This is achieved by applying a parallel transmission concept on the communicating nodes. As a result, the overall efficiency of the channel contention mechanism increases and leads to higher throughput with lower energy consumption. Finally, this thesis proposed the use of the Adaptive scheme on Border Nodes to increase the power efficiency of the system under light traffic load conditions. The scheme focuses on saving energy by forcing the network border nodes to go off when not needed. These three contributions minimise the contention window period whilst maximising the capacity of the available channel, which as a result increase network performance in terms of energy efficiency, throughput and latency. The proposed system is shown to be backwards compatible and able to satisfy both traditional and advanced applications. The new MAC protocol has been implemented and evaluated using NS-2 simulator, under different traffic loads and varying duty cycle values. Results have shown that the proposed solutions are able to significantly enhance the performance of WSNs by improving the energy efficiency, increasing the system throughput and reducing the communication delay.

Wireless sensor networks are emerging from the mobile ad hoc network concept and as such they share many similarities. However, it is not the similarities that differentiates sensor networks from their ad hoc counterparts, it is the differences. One of the most important difference is that they should operate unattended for long periods of time. This is especially important since they usually rely on a finite energy source to function. To get this into a perspective, a sensor network constitutes of a sensor field where a number of sensor nodes are deployed. The sensor nodes relay the gathered information to a base station from which the data are forwarded either through a network or directly to the enduser. The communication between sensor nodes are conducted in an ad hoc manner, which means that paths toward the base station are dynamically constructed based on current network conditions. The network conditions changes and examples of this includes node failure, deactivated nodes, variations in the radio channel characteristics, etc. As mentioned above, the sensor nodes are energy constrained and one of the more important design criteria is the life time of a sensor node or network. To be able to evaluate this criteria an energy dissipation model is needed. Most of the energy dissipation models developed for wireless sensor networks are not based on the basic sensor node architecture and as such they where not accurate enough for our needs. Thus, an energy dissipation model was developed. This model utilises the basic sensor node architecture to obtain the operation states available and their corresponding state transitions. Communication is the most energy consuming task a sensor node can undertake. As such, the contributed energy dissipation model is used to evaluate this aspect of the proposed controlled flooding protocols. Generally, the controlled flooding protocols tries to minimise the number of forwarding nodes and by doing this they lower the energy consumed in the network. Along with this, the communication overhead of a protocol also needs to be taken into account. Our idea is to utilise the received signal strength directly to make forwarding decisions based on a cost function. This idea has a number of key features, which are: no additional overhead in the message, no neighbour knowledge and no location information are needed. The results from the proposed flooding protocols are promising as they have a lower number of forwarding nodes and a longer lifetime than the others. / <p>Report code: LIU-TEK-LIC-2007:43.</p>

Background: With the global decline of honey bee populations, safeguarding these vital pollinators has become crucial. Varroa destructor mites are a primary threat, weakening bees and facilitating the spread of diseases, which can decimate colonies and disrupt ecosystems. This thesis investigates the application of a Wireless sensor network (WSN) for the monitoring and control of varroasis spread within bee colonies across large geographical areas. Objectives: The main objective of this research is to develop an integrated method that combines biological insights into varroasis with WSN functionalities for real-time disease monitoring and control. By doing so, the study aims to contribute to the development of a scalable and sustainable approach to apiculture and disease management. Methods: A multi-phase methodological approach was employed, encompassing the modelling of biological phenomena, formulation of WSN functionalities, and the design of a scalable WSN architecture. Simulation studies were conducted, followed by the development of a theoretical framework to support the practical application of the proposed WSN system. A key aspect of the methodology is the introduction of energy estimation models to evaluate the operational feasibility of the WSN. Results: The results indicate that the WSN is capable of dynamically adjusting its monitoring rate in response to changes in infection dynamics, effectively identifying and managing varroa mite populations. The system demonstrated adaptability to various infection rates, with the potential to improve the timely and targeted treatment of infested colonies. Energy consumption data further affirms the operational viability of the WSN. Conclusions: The study concludes that integrating WSNs with biological models is a viable solution for the real-time monitoring and management of varroasis. The proposed WSN system holds promise for enhancing the health and productivity of bee colonies on a broad scale, offering a novel contribution to the fields of apiculture and environmental monitoring.