Distance-based sensor node localization by using ultrasound, RSSI and ultra-wideband - A comparision between the techniques

Wireless sensor networks (WSNs) have become one of the most important topics in wireless communication during the last decade. In a wireless sensor system, sensors are spread over a region to build a sensor network and the sensors in a region co-operate to each other to sense, process, filter and routing. Sensor Positioning is a fundamental and crucial issue for sensor network operation and management. WSNs have so many applications in different areas such as health-care, monitoring and control, rescuing and military; they all depend on nodes being able to accurately determine their locations. This master’s thesis is focused on distance-based sensor node localization techniques; Received signal strength indicator, ultrasound and ultra-wideband. Characteristics and factors which affect these distance estimation techniques are analyzed theoretically and through simulation the quality of these techniques are compared in different scenarios. MDS, a centralized algorithm is used for solving the coordinates. It is a set of data analysis techniques that display the structure of distance-like data as a geometrical picture. Centralized and distributed implementations of MDS are also discussed. All simulations and computations in this thesis are done in Matlab. Virtual WSN is simulated on Sensorviz. Sensorviz is a simulation and visualization tool written by Andreas Savvides.fi=Opinnäytetyö kokotekstinä PDF-muodossa.|en=Thesis fulltext in PDF format.|sv=Lärdomsprov tillgängligt som fulltext i PDF-format

Distance-based sensor node localization by using ultrasound, RSSI and ultra-wideband - A comparision between the techniques

Wireless sensor networks (WSNs) have become one of the most important topics in wireless communication during the last decade. In a wireless sensor system, sensors are spread over a region to build a sensor network and the sensors in a region co-operate to each other to sense, process, filter and routing. Sensor Positioning is a fundamental and crucial issue for sensor network operation and management. WSNs have so many applications in different areas such as health-care, monitoring and control, rescuing and military; they all depend on nodes being able to accurately determine their locations. This master’s thesis is focused on distance-based sensor node localization techniques; Received signal strength indicator, ultrasound and ultra-wideband. Characteristics and factors which affect these distance estimation techniques are analyzed theoretically and through simulation the quality of these techniques are compared in different scenarios. MDS, a centralized algorithm is used for solving the coordinates. It is a set of data analysis techniques that display the structure of distance-like data as a geometrical picture. Centralized and distributed implementations of MDS are also discussed. All simulations and computations in this thesis are done in Matlab. Virtual WSN is simulated on Sensorviz. Sensorviz is a simulation and visualization tool written by Andreas Savvides.fi=Opinnäytetyö kokotekstinä PDF-muodossa.|en=Thesis fulltext in PDF format.|sv=Lärdomsprov tillgängligt som fulltext i PDF-format

Localisation in wireless sensor networks for disaster recovery and rescuing in built environments

A thesis submitted to the University of Bedfordshire in partial fulfilment of the requirements for the degree of Doctor of PhilosophyProgress in micro-electromechanical systems (MEMS) and radio frequency (RF) technology has fostered the development of wireless sensor networks (WSNs). Different from traditional networks, WSNs are data-centric, self-configuring and self-healing. Although WSNs have been successfully applied in built environments (e.g. security and services in smart homes), their applications and benefits have not been fully explored in areas such as disaster recovery and rescuing. There are issues related to self-localisation as well as practical constraints to be taken into account. The current state-of-the art communication technologies used in disaster scenarios are challenged by various limitations (e.g. the uncertainty of RSS). Localisation in WSNs (location sensing) is a challenging problem, especially in disaster environments and there is a need for technological developments in order to cater to disaster conditions. This research seeks to design and develop novel localisation algorithms using WSNs to overcome the limitations in existing techniques. A novel probabilistic fuzzy logic based range-free localisation algorithm (PFRL) is devised to solve localisation problems for WSNs. Simulation results show that the proposed algorithm performs better than other range free localisation algorithms (namely DVhop localisation, Centroid localisation and Amorphous localisation) in terms of localisation accuracy by 15-30% with various numbers of anchors and degrees of radio propagation irregularity. In disaster scenarios, for example, if WSNs are applied to sense fire hazards in building, wireless sensor nodes will be equipped on different floors. To this end, PFRL has been extended to solve sensor localisation problems in 3D space. Computational results show that the 3D localisation algorithm provides better localisation accuracy when varying the system parameters with different communication/deployment models. PFRL is further developed by applying dynamic distance measurement updates among the moving sensors in a disaster environment. Simulation results indicate that the new method scales very well

A Learning-based Approach to Exploiting Sensing Diversity in Performance Critical Sensor Networks

Wireless sensor networks for human health monitoring, military surveillance, and disaster warning all have stringent accuracy requirements for detecting and classifying events while maximizing system lifetime. to meet high accuracy requirements and maximize system lifetime, we must address sensing diversity: sensing capability differences among both heterogeneous and homogeneous sensors in a specific deployment. Existing approaches either ignore sensing diversity entirely and assume all sensors have similar capabilities or attempt to overcome sensing diversity through calibration. Instead, we use machine learning to take advantage of sensing differences among heterogeneous sensors to provide high accuracy and energy savings for performance critical applications.;In this dissertation, we provide five major contributions that exploit the nuances of specific sensor deployments to increase application performance. First, we demonstrate that by using machine learning for event detection, we can explore the sensing capability of a specific deployment and use only the most capable sensors to meet user accuracy requirements. Second, we expand our diversity exploiting approach to detect multiple events using a distributed manner. Third, we address sensing diversity in body sensor networks, providing a practical, user friendly solution for activity recognition. Fourth, we further increase accuracy and energy savings in body sensor networks by sharing sensing resources among neighboring body sensor networks. Lastly, we provide a learning-based approach for forwarding event detection decisions to data sinks in an environment with mobile sensor nodes

Towards Real-time Wireless Sensor Networks

Wireless sensor networks are poised to change the way computer systems interact with the physical world. We plan on entrusting sensor systems to collect medical data from patients, monitor the safety of our infrastructure, and control manufacturing processes in our factories. To date, the focus of the sensor network community has been on developing best-effort services. This approach is insufficient for many applications since it does not enable developers to determine if a system\u27s requirements in terms of communication latency, bandwidth utilization, reliability, or energy consumption are met. The focus of this thesis is to develop real-time network support for such critical applications. The first part of the thesis focuses on developing a power management solution for the radio subsystem which addresses both the problem of idle-listening and power control. In contrast to traditional power management solutions which focus solely on reducing energy consumption, the distinguishing feature of our approach is that it achieves both energy efficiency and real-time communication. A solution to the idle-listening problem is proposed in Energy Efficient Sleep Scheduling based on Application Semantics: ESSAT). The novelty of ESSAT lies in that it takes advantage of the common features of data collection applications to determine when to turn on and off a node\u27s radio without affecting real-time performance. A solution to the power control problem is proposed in Real-time Power Aware-Routing: RPAR). RPAR tunes the transmission power for each packet based on its deadline such that energy is saved without missing packet deadlines. The main theoretical contribution of this thesis is the development of novel transmission scheduling techniques optimized for data collection applications. This work bridges the gap between wireless sensor networks and real-time scheduling theory, which have traditionally been applied to processor scheduling. The proposed approach has significant advantages over existing design methodologies:: 1) it provides predictable performance allowing for the performance of a system to be estimated upon its deployment,: 2) it is possible to detect and handle overload conditions through simple rate control mechanisms, and: 3) it easily accommodates workload changes. I developed this framework under a realistic interference model by coordinating the activities at the MAC, link, and routing layers. The last component of this thesis focuses on the development of a real-time patient monitoring system for general hospital units. The system is designed to facilitate the detection of clinical deterioration, which is a key factor in saving lives and reducing healthcare costs. Since patients in general hospital wards are often ambulatory, a key challenge is to achieve high reliability even in the presence of mobility. To support patient mobility, I developed the Dynamic Relay Association Protocol -- a simple and effective mechanism for dynamically discovering the right relays for forwarding patient data -- and a Radio Mapping Tool -- a practical tool for ensuring network coverage in 802.15.4 networks. We show that it is feasible to use low-power and low-cost wireless sensor networks for clinical monitoring through an in-depth clinical study. The study was performed in a step-down cardiac care unit at Barnes-Jewish Hospital. This is the first long-term study of such a patient monitoring system

An approach to understand network challenges of wireless sensor network in real-world environments

The demand for large-scale sensing capabilities and scalable communication networks to monitor and control entities within smart buildings have fuelled the exponential growth in Wireless Sensor Network (WSN). WSN proves to be an attractive enabler because of its accurate sensing, low installation cost and flexibility in sensor placement. While WSN offers numerous benefits, it has yet to realise its full potential due to its susceptibility to network challenges in the environment that it is deployed. Particularly, spatial challenges in the indoor environment are known to degrade WSN communication reliability and have led to poor estimations of link quality. Existing WSN solutions often generalise all link failures and tackle them as a single entity. However, under the persistent influence of spatial challenges, failing to provide precise solutions may cause further link failures and higher energy consumption of battery-powered devices. Therefore, it is crucial to identify the causes of spatial- related link failures in order to improve WSN communication reliability. This thesis investigates WSN link failures under the influence of spatial challenges in real-world indoor environments. Novel and effective strategies are developed to evaluate the WSN communication reliability. By distinguishing between spatial challenges such as a poorly deployed environment and human movements, solutions are devised to reduce link failures and improve the lifespans of energy constraint WSN nodes. In this thesis, WSN test beds using proprietary wireless sensor nodes are developed and deployed in both controlled and uncontrolled office environments. These test beds provide diverse platforms for investigation into WSN link quality. In addition, a new data extraction feature called Network Instrumentation (NI) is developed and implemented onto the communication stacks of wireless sensor nodes to collect ZigBee PRO parameters that are under the influence of environmental dynamics. To understand the relationships between WSN and Wi-Fi devices communications, an investigation on frequency spectrum sharing is conducted between IEEE 802.15.4 and IEEE 802.11 bgn standards. It is discovered that the transmission failure of WSN nodes under persistent Wi-Fi interference is largely due to channel access failure rather than corrupted packets. The findings conclude that both technologies can co- exist as long as there is sufficient frequency spacing between Wi-Fi and WSN communication and adequate operating distance between the WSN nodes, and between the WSN nodes and the Wi-Fi interference source. Adaptive Network-based Fuzzy Inference System (ANFIS) models are developed to predict spatial challenges in an indoor environment. These challenges are namely, “no failure”, “failure due to poorly deployed environment” and “failure due to human movement”. A comparison of models has found that the best-produced model represents the properties of signal strength, channel fluctuations, and communication success rates. It is recognised that the interpretability of ANFIS models have reduced due to the “curse of dimensionality”. Hence, Non-Dominated Sorting Genetic Algorithm (NSGA-II) technique is implemented to reduce the complexity of these ANFIS models. This is followed by a Fuzzy rule sensitivity analysis, where the impacts of Fuzzy rules on model accuracy are found to be dependent on factors such as communication range and controlled or uncontrolled environment. Long-term WSN routing stability is measured, taking into account the adaptability and robustness of routing paths in the real-world environments. It is found that routing stability is subjected to the implemented routing protocol, deployed environment and routing options available. More importantly, the probability of link failures can be as high as 29.9% when a next hop’s usage rate falls less than 10%. This suggests that a less dominant next hop is subjected to more link failures and is short-lived. Overall, this thesis brings together diverse WSN test beds in real-world indoor environments and a new data extraction platform to extract link quality parameters from ZigBee PRO stack for a representative assessment of WSN link quality. This produces realistic perspectives of the interactions between WSN communication reliability and the environmental dynamics, particularly spatial challenges. The outcomes of this work include an in-depth system level understanding of real-world deployed applications and an insightful measure of large-scale WSN communication performance. These findings can be used as building blocks for a reliable and sustainable network architecture built on top of resource–constrained WSN

Models and Protocols for Resource Optimization in Wireless Mesh Networks

Wireless mesh networks are built on a mix of fixed and mobile nodes interconnected via wireless links to form a multihop ad hoc network. An emerging application area for wireless mesh networks is their evolution into a converged infrastructure used to share and extend, to mobile users, the wireless Internet connectivity of sparsely deployed fixed lines with heterogeneous capacity, ranging from ISP-owned broadband links to subscriber owned low-speed connections. In this thesis we address different key research issues for this networking scenario. First, we propose an analytical predictive tool, developing a queuing network model capable of predicting the network capacity and we use it in a load aware routing protocol in order to provide, to the end users, a quality of service based on the throughput. We then extend the queuing network model and introduce a multi-class queuing network model to predict analytically the average end-to-end packet delay of the traffic flows among the mobile end users and the Internet. The analytical models are validated against simulation. Second, we propose an address auto-configuration solution to extend the coverage of a wireless mesh network by interconnecting it to a mobile ad hoc network in a transparent way for the infrastructure network (i.e., the legacy Internet interconnected to the wireless mesh network). Third, we implement two real testbed prototypes of the proposed solutions as a proof-of-concept, both for the load aware routing protocol and the auto-configuration protocol. Finally we discuss the issues related to the adoption of ad hoc networking technologies to address the fragility of our communication infrastructure and to build the next generation of dependable, secure and rapidly deployable communications infrastructures

A new connectivity strategy for wireless mesh networks using dynamic spectrum access

The introduction of Dynamic Spectrum Access (DSA) marked an important juncture in the evolution of wireless networks. DSA is a spectrum assignment paradigm where devices are able to make real-time adjustment to their spectrum usage and adapt to changes in their spectral environment to meet performance objectives. DSA allows spectrum to be used more efficiently and may be considered as a viable approach to the ever increasing demand for spectrum in urban areas and the need for coverage extension to unconnected communities. While DSA can be applied to any spectrum band, the initial focus has been in the Ultra-High Frequency (UHF) band traditionally used for television broadcast because the band is lightly occupied and also happens to be ideal spectrum for sparsely populated rural areas. Wireless access in general is said to offer the most hope in extending connectivity to rural and unconnected peri-urban communities. Wireless Mesh Networks (WMN) in particular offer several attractive characteristics such as multi-hopping, ad-hoc networking, capabilities of self-organising and self-healing, hence the focus on WMNs. Motivated by the desire to leverage DSA for mesh networking, this research revisits the aspect of connectivity in WMNs with DSA. The advantages of DSA when combined with mesh networking not only build on the benefits, but also creates additional challenges. The study seeks to address the connectivity challenge across three key dimensions, namely network formation, link metric and multi-link utilisation. To start with, one of the conundrums faced in WMNs with DSA is that the current 802.11s mesh standard provides limited support for DSA, while DSA related standards such as 802.22 provide limited support for mesh networking. This gap in standardisation complicates the integration of DSA in WMNs as several issues are left outside the scope of the applicable standard. This dissertation highlights the inadequacy of the current MAC protocol in ensuring TVWS regulation compliance in multi-hop environments and proposes a logical link MAC sub-layer procedure to fill the gap. A network is considered compliant in this context if each node operates on a channel that it is allowed to use as determined for example, by the spectrum database. Using a combination of prototypical experiments, simulation and numerical analysis, it is shown that the proposed protocol ensures network formation is accomplished in a manner that is compliant with TVWS regulation. Having tackled the compliance problem at the mesh formation level, the next logical step was to explore performance improvement avenues. Considering the importance of routing in WMNs, the study evaluates link characterisation to determine suitable metric for routing purposes. Along this dimension, the research makes two main contributions. Firstly, A-link-metric (Augmented Link Metric) approach for WMN with DSA is proposed. A-link-metric reinforces existing metrics to factor in characteristics of a DSA channel, which is essential to improve the routing protocol's ranking of links for optimal path selection. Secondly, in response to the question of “which one is the suitable metric?”, the Dynamic Path Metric Selection (DPMeS) concept is introduced. The principal idea is to mechanise the routing protocol such that it assesses the network via a distributed probing mechanism and dynamically binds the routing metric. Using DPMeS, a routing metric is selected to match the network type and prevailing conditions, which is vital as each routing metric thrives or recedes in performance depending on the scenario. DPMeS is aimed at unifying the years worth of prior studies on routing metrics in WMNs. Simulation results indicate that A-link-metric achieves up to 83.4 % and 34.6 % performance improvement in terms of throughput and end-to-end delay respectively compared to the corresponding base metric (i.e. non-augmented variant). With DPMeS, the routing protocol is expected to yield better performance consistently compared to the fixed metric approach whose performance fluctuates amid changes in network setup and conditions. By and large, DSA-enabled WMN nodes will require access to some fixed spectrum to fall back on when opportunistic spectrum is unavailable. In the absence of fully functional integrated-chip cognitive radios to enable DSA, the immediate feasible solution for the interim is single hardware platforms fitted with multiple transceivers. This configuration results in multi-band multi-radio node capability that lends itself to a variety of link options in terms of transmit/receive radio functionality. The dissertation reports on the experimental performance evaluation of radios operating in the 5 GHz and UHF-TVWS bands for hybrid back-haul links. It is found that individual radios perform differently depending on the operating parameter settings, namely channel, channel-width and transmission power subject to prevailing environmental (both spectral and topographical) conditions. When aggregated, if the radios' data-rates are approximately equal, there is a throughput and round-trip time performance improvement of 44.5 - 61.8 % and 7.5 - 41.9 % respectively. For hybrid links comprising radios with significantly unequal data-rates, this study proposes an adaptive round-robin (ARR) based algorithm for efficient multilink utilisation. Numerical analysis indicate that ARR provides 75 % throughput improvement. These results indicate that network optimisation overall requires both time and frequency division duplexing. Based on the experimental test results, this dissertation presents a three-layered routing framework for multi-link utilisation. The top layer represents the nodes' logical interface to the WMN while the bottom layer corresponds to the underlying physical wireless network interface cards (WNIC). The middle layer is an abstract and reductive representation of the possible and available transmission, and reception options between node pairs, which depends on the number and type of WNICs. Drawing on the experimental results and insight gained, the study builds criteria towards a mechanism for auto selection of the optimal link option. Overall, this study is anticipated to serve as a springboard to stimulate the adoption and integration of DSA in WMNs, and further development in multi-link utilisation strategies to increase capacity. Ultimately, it is hoped that this contribution will collectively contribute effort towards attaining the global goal of extending connectivity to the unconnected