Indiana University-Purdue University Indianapolis (IUPUI) / This study proposes and evaluates an average consensus scheme for wireless sensor networks. For this purpose, two communication error models, the fading signal error model and approximated fading signal error model, are introduced and incorporated into the proposed decentralized average consensus scheme. Also, a mathematical analysis is introduced to derive the approximated fading signal model from the fading signal model. Finally, differnt simulation scenarios are introduced and their results analyzed to evaluate the performance of the proposed scheme and its effectiveness in meeting the needs of wireless sensor networks.

Indiana University-Purdue University Indianapolis (IUPUI) / Sensor nodes forming a network and using wireless communications are highly useful in a variety of applications including battle field (military) surveillance, building security, medical and health services, environmental monitoring in harsh conditions, for scientific investigations on other planets, etc. But these wireless sensors are resource constricted: limited power supply, bandwidth for communication, processing speed, and memory space. One possible way of achieve maximum utilization of those constrained resource is applying signal processing and compressing the sensor readings. Usually, processing data consumes much less power than transmitting data in wireless medium, so it is effective to apply data compression by trading computation for communication before transmitting data for reducing total power consumption by a sensor node. However the existing state of the art compression algorithms are not suitable for wireless sensor nodes due to their limited resource. Therefore there is a need to design signal processing (compression) algorithms considering the resource constraint of wireless sensors. In our work, we designed a lightweight codec system aiming surveillance as a target application. In designing the codec system, we have proposed new design ideas and also tweak the existing encoding algorithms to fit the target application. Also during data transmission among sensors and between sensors and base station, the data has to be secured. We have addressed some security issues by assessing the security of wavelet tree shuffling as the only security mechanism.

In recent years, many strides have been achieved in the area of Wireless Sensor Networks (WSNs), which is leading to constant innovations in the types of applications that WSNs can support. Much advancement has also been achieved in the area of smart homes, enabling its occupants to manually and easily control their utility expenses. In this thesis, both areas of research will be colluded for a simple, yet critical application: efficient and economical comfort control in smart residential spaces. The goal is to design a central, modular energy consumption control system for residential spaces, which manages energy consumption in all aspects of a typical residence. This thesis is concerned with two facets of energy consumption in residences. The first facet is concerned with controlling when the heating, ventilating, and air conditioning unit (HVAC) operates for each room separately. This is in contrast to a typical HVAC system where comfort is provided across the floor as a whole. The second facet is concerned with controlling the lighting in each room so as to not exceed a certain input value. The communication network that supports the realization of these coveted goals is based on Zigbee interconnected sensor nodes which pour data unto a smart thermostat which does all the required calculations and activates the modules required for comfort control and energy management, if needed. A Java-based discrete event simulator is then written up to simulate a floor of a typical Canadian single-family dwelling. The simulation assumes error-less communication and proceeds to record certain room variables and the ongoing cost of operation periodically. These results from the simulator are compared to the results of the well known simulator, created by DesignBuilder, which describes typical home conditions. The conclusion from this analysis is that the Comfort Control and Energy Management Algorithms (CEMA) are feasible, and that their implementation incurs significant monetary savings.

A growing number of smart items are entering our daily lives as the Internet of Things becomes increasingly prevalent. ICT device miniaturization introduces a brand-new material type called Communicating Material (CM). The term “communications material” refers to a single system that includes a material equipped with communication devices. In this paper, the main limitation of CM was studied - the issue of energy consumption. Due to the limited battery capacity of sensor nodes, the issue of network lifetime comes to the fore, emphasizing the importance of power management and optimization for each sensor node. The first and most important step in tackling this problem is to precisely estimate and calculate each node's power usage. In addition, the WSN's embeddedness in the material makes it challenging to replace batteries and measure network power consumption, necessitating the development of a different approach to power consumption estimation. Thus, our work explores all the different approaches to energy estimation in WSN and tries to choose the best method that fits our WSN platform.

Internet of Things (IoT) has drawn much attention in recent years. With IoT, physical world entities get connected through internet. IoT is used currently in various applications, such as environmental monitoring, control systems, farming, home automation, security and surveillance systems etc. The aim of this research is to design a low-cost, energy-efficient, reliable and scalable embedded application for the smart greenhouse monitoring system. The IoT based system designed in this thesis uses various sensors to measure the air and soil quality parameters in the greenhouse, and monitor real-time data online using web-server and mobile phone based applications. A ZigBee based wireless sensor network is implemented to transport various sensory data to the gateway. Among other contributions, the designed system develops a new routing algorithm by introducing a confirmed delivery of packets and re-routing features. We also introduced an efficient cost metric for making routing decisions within WSN using hops count, and simple bi-directional link quality estimator using PRR and current battery voltage of neighbor nodes. We also verified the stability of the system by conducting various performance tests. The system is equipped with data analytic functions for the online examination of the data. The designed system adopts event-based triggering and data aggregation methods to reduce the number of transmissions, and develops a new algorithm for such purpose. The web-server and mobile applications have user interface to display the output of the data analytic services, warning, control operations and give access to query data of the user's interest.

The existence of a coordinate system can often improve the routing in a wireless sensor network. While most coordinate systems correspond to the geometrical or geographical coordinates, in recent years researchers had proposed the use of virtual coordinates. Virtual coordinates depend only on the topology of the network as defined by the connectivity of the nodes, without requiring geographical information. The work in this thesis extends the use of virtual coordinates to scenarios where the wireless sensor network has a mobile sink. One reason to use a mobile sink is to distribute the energy consumption more evenly among the sensor nodes and thus extend the life-time of the network. We developed two algorithms, MS-DVCR and CU-DVCR which perform routing towards a mobile sink using virtual coordinates. In contrast to the baseline virtual coordinate routing MS-DVCR limits routing updates triggered by the sink movement to a local area around the sink. In contrast, CU-DVCR limits the route updates to a circular area on the boundary of the local area. We describe the design justification and the implementation of these algorithms. Using a set of experimental studies, we show that MS-DVCR and CU-DVCR achieve a lower energy consumption compared to the baseline virtual coordinate routing without any noticeable impact on routing performance. In addition, CU-DVCR provides a lower energy consumption than MS-DVCR for the case of a fast moving sink.

The low-energy characteristics of Wireless Sensor Networks (WSNs) pose a great design challenge for MAC protocol design. The cluster-based scheme is a promising solution. Recent studies have proposed different cluster-based MAC protocols. We propose an intra-cluster communication bit-map-assisted (BMA) MAC protocol. BMA is intended for event-driven applications. The scheduling of BMA can change dynamically according to the unpredictable variations of sensor networks. In terms of energy efficiency, BMA reduces energy consumption due to idle listening and collisions. In this study, we develop two different analytic energy models for BMA, conventional TDMA and energy efficient TDMA (E-TDMA) when used as intra-cluster MAC schemes. Simulation experiments are constructed to validate the analytic models. Both analytic and simulation results show that in terms of energy efficiency, BMA performance heavily depends on the sensor node traffic offer load, the number of sensor nodes within a cluster, the data packet size and, in some cases, the number of sessions per round. BMA is superior for the cases of low and medium traffic loads, relatively few sensor nodes per cluster, and relatively large data packet sizes. In addition, BMA outperforms the TDMA-based MAC schemes in terms of average packet latency.

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