Wireless Sensor Networks (WSNs) are wireless networks that have recently drawn significant research attention since they offer unique benefits and versatility with respect to sensing, allowing low-power and low-cost rapid deployment for many applications that do not need human supervision. WSNs are self-created and self-organized by the collection of a large number of sensor nodes interconnected by multi-hop wireless paths. The sensor nodes are network embedded systems with Integrated Chips (ICs) to allow signal processing and micro-sensing. Each wireless sensor node is a micro-electro-mechanical device and can only be equipped with a limited power reserve. While energy consumption occurs in sensing, data processing and communications, care should be exercised to make the most of the expendable power source for the node. Though considerable research is being done in the area of energy saving techniques for WSNs, most of the proposed techniques have focused on energy awareness at different network layers in WSNs. Furthermore, most of the proposed techniques are based on protocols for mobile ad hoc networks that do not look into the possibility of a cross-layer design strategy that can exploit the unique features of WSNs. There still exists the need for a universal protocol that can be applied to such networks in general. In this thesis, we focus such a research on optimizing the energy consumption by suggesting a novel cross-layer architecture at the network/data-link layer for sensor networks. We have developed a scheme for better and improved energy efficiency in WSNs by combining the ideas of energy-efficient cluster formation and medium access together. Our cross-layer scheme provides good performance in terms of WSN-lifetime, scalability and minimizing network-wide energy consumption. The scheme is based on a collaborative approach supported by formation of dynamic clusters functioning with a traffic aware MAC (medium access control) scheme. Our MAC scheme incorporates a self-learning, traffic adaptive algorithm for varying traffic conditions inherent to the WSNs. The design methodology and results in this thesis aim at producing a reliable and scalable energy-aware sensing network, in spite of node failures, minimizing energy consumption at the same time. / Master of Science

With the increase in applications of wireless sensor networks, data extraction and visualisation have become a key issue to develop and operate these networks. Wireless sensor networks typically gather data at a discrete number of locations. By bestowing the ability to predict inter-node values upon the network, it is proposed that it will become possible to build applications that are unaware of the concrete reality of sparse data. The aim of this thesis is to develop a service for maximising information return from large scale wireless sensor networks. This aim will be achieved through the development of a distributed information extraction and visualisation service called the mapping service. In the distributed mapping service, groups of network nodes cooperate to produce local maps which are cached and merged at a sink node, producing a map of the global network. Such a service would greatly simplify the production of higher-level information-rich representations suitable for informing other network services and the delivery of field information visualisations. The proposed distributed mapping service utilises a blend of both inductive and deductive models to successfully map sense data and the universal physical principles. It utilises the special characteristics of the application domain to render visualisations in a map format that are a precise reflection of the concrete reality. This service is suitable for visualising an arbitrary number of sense modalities. It is capable of visualising from multiple independent types of the sense data to overcome the limitations of generating visualisations from a single type of a sense modality. Furthermore, the proposed mapping service responds to changes in the environmental conditions that may impact the visualisation performance by continuously updating the application domain model in a distributed manner. Finally, a newdistributed self-adaptation algorithm, Virtual Congress Algorithm,which is based on the concept of virtual congress is proposed, with the goal of saving more power and generating more accurate data visualisation.

Recently, wireless sensor networks have become one of the most exciting areas for research and development. However, sensor nodes are battery operated, thus the sensor's ability to perform its assigned tasks is limited by its battery capacity; therefore, energy efficiency is considered to be a key issue in designing WSN applications. Clustering has emerged as a useful mechanism for trade-off between certain design goal conflicts; the network life time, and the amount of data obtained. However, different sources of energy waste still exist. Furthermore, in such dynamic environments, different data rate requirements emerge due to the current network status, thus adapting a response to the changing network is essential, rather than following the same principle during the network's lifespan. This thesis presents dynamic techniques to adapt to network changes, through which the limited critical energy source can be wisely managed so that the WSN application can achieve its intended design goals. Two approaches have been taken to decreasing the energy use. The first approach is to develop two dynamic round time controllers, called the minimum round time controller MIN-RC and the variable round time controller VAR-RC, whereas the second approach improves intra-cluster communication using a Co-Cluster head; both approaches show better energy utilisation compared to traditional protocols. A third approach has been to develop a general hybrid protocol H-RC that can adapt different applications requirements; it can also tolerate different data rate requirements for the same application during the system's lifetime.

Wireless Underground Sensor Networks (WUSNs) are the networks of wireless sensors that operate below the ground surface. These sensors are either buried completely in soil medium, or placed within a bounded open underground space, such as underground mines and tunnels. WUSNs enable a wide variety of novel applications, including intelligent irrigation, underground structure monitoring, and border patrol and intruder detection. This thesis is concerned with establishing reliable and efficient communications in the network of wireless sensor nodes that are deployed in either soil medium or underground mines and tunnels. In particular, to realize WUSNs in soil medium, two types of signal propagation techniques including Electromagnetic (EM) waves and Magnetic Induction (MI) are explored. For EM wave-based WUSNs, the heterogeneous network architecture and dynamic connectivity are investigated based on a comprehensive channel model in soil medium. Then a spatio-temporal correlation-based data collection schemes is developed to reduce the sensor density while keeping high monitoring accuracy. For MI-based WUSNs, the MI channel is first analytically characterized. Then based on the MI channel model, the MI waveguide technique is developed in order to enlarge the underground transmission range. Finally, the optimal deployment algorithms for MI waveguides in WUSNs are analyzed to construct the WUSNs with high reliability and low costs. To realize WUSNs in underground mines and tunnels, a mode-based analytical channel model is first proposed to accurately characterize the signal propagation in both empty and obstructed mines and tunnels. Then the Multiple-Input and Multiple-Output (MIMO) system and cooperative communication system are optimized to establish reliable and efficient communications in underground mines and tunnels.

As the trends towards decentralization, miniaturization, and longevity of deployment continue in many domains, power management has become increasingly important. In this work, we develop power-aware control strategies for wireless sensor networks to improve the lifetime of the network and to ensure that the desired performance is guaranteed. For the case of static networks (networks of agents with no mobility), we identify the problem of the effects of power variations on the performance of an individual sensing device and on the entire network. To address this problem in a randomly deployed sensor network comprising of sensing devices whose sensing range is a function of transmitted power, we propose power-aware controllers to compensate for the variations in available power and maintain desired performance. We also propose a novel energy-efficient sleep-scheduling scheme that is random in nature and allows limited coordination among neighboring sensors for making switching decisions. This scheme is based on the concept of a hard-core point process from stochastic geometry, in which neighboring points are allowed to interact with each other through some predefined interaction laws. For the case of mobile networks (networks of agents with mobility), we propose a solid framework for distributed power-aware mobility strategies that can achieve any desired global objective while minimizing total energy consumption. This goal is achieved by first exploring fundamental trade-offs among various modes of operations of mobile devices and then exploiting these trade-offs for minimizing energy consumption. Through this framework, a whole class of decentralized power-aware controllers emerge for solving canonical problems in multi-agent systems like connectivity maintenance, rendezvous, and coverage control.

Thesis (M.S.)--Mississippi State University. Department of Computer Science and Engineering. / Title from title screen. Includes bibliographical references.

Recently, wireless sensor networks have become one of the most exciting areas for research and development. However, sensor nodes are battery operated, thus the sensor¿s ability to perform its assigned tasks is limited by its battery capacity; therefore, energy efficiency is considered to be a key issue in designing WSN applications. Clustering has emerged as a useful mechanism for trade-off between certain design goal conflicts; the network life time, and the amount of data obtained. However, different sources of energy waste still exist. Furthermore, in such dynamic environments, different data rate requirements emerge due to the current network status, thus adapting a response to the changing network is essential, rather than following the same principle during the network¿s lifespan. This thesis presents dynamic techniques to adapt to network changes, through which the limited critical energy source can be wisely managed so that the WSN application can achieve its intended design goals. Two approaches have been taken to decreasing the energy use. The first approach is to develop two dynamic round time controllers, called the minimum round time controller MIN-RC and the variable round time controller VAR-RC, whereas the second approach improves intra-cluster communication using a Co-Cluster head; both approaches show better energy utilisation compared to traditional protocols. A third approach has been to develop a general hybrid protocol H-RC that can adapt different applications requirements; it can also tolerate different data rate requirements for the same application during the system¿s lifetime.

A wireless sensor network (WSN) is a spatially distributed network used to monitor the physical and environmental conditions such as temperature, pressure, sound, humidity, heat, etc. WSNs can be modeled using different simulation frameworks like OMNeT++, Prowler, Atarraya, PiccSIM, Network Simulator, etc. In this research, Simulink framework was used to model WSN system. The complete WSN consisting of transmitting nodes, communication channel, and receiver nodes are built in the Simulink framework. Orthogonal frequency division multiplexing technique was used to transmit the information. The implemented wireless sensor system behavior is studied using temperature as the measurement parameter at different values of signal to noise ratio. The plots of bit error rate versus signal to noise ratio and frame error rate versus signal to noise ratio are generated in the Simulink framework. It is easy to study the effect of different physical layer parameters on the performance of wireless sensor networks by implementing WSN in the Simulink framework.

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Sensors have been an integral part of our life since a long time. Traditionally, the transmit information to a data collection center through a physical wire. However, with the introduction of Bluetooth Low Energy (BLE) communication protocol, more research is being done into the field of wireless sensor networks (WSN). BLE was introduced to target low power applications. The CC2650 Launchpad designed by Texas Instruments (TI) can lead to a bulky final product. The aim was to design hardware for the CC2650 micro-controller with the aim of making it more compact for use in WSNs. A top-down approach was used wherein the available product is studied to identify the redundant and reverse engineer it to design a new product. A 2 layer printed circuit board (PCB) was designed which resulted in a 64 percent decrease in size compared to the Launchpad. Also, experiments were performed to test the proof of concept.