Energy efficient adaptive cooperative communications in wireless sensor networks

Energy efficiency is one of the most important performances of a wireless sensor network. In this paper, we show that choosing a proper transmission scheme given the channel and network conditions can ensure a high energy performance in different transmission environments. Based on the energy models we established for both cooperative and non-cooperative communications, the efficiency in terms of energy consumption per bit for different transmission schemes is investigated. It is shown that cooperative transmission schemes can outperform non-cooperative schemes in energy efficiency in severe channel conditions and when the source-destination distance is in a medium or long range. But the latter is more energy efficient than the former for short-range transmission. For cooperative transmission schemes, the number of transmission branches and the number of relays per branch can also be properly selected to adapt to the variations of the transmission environment, so that the total energy consumption can be minimized.

Semantic enabled sensor network design

Wireless Sensor Network (WSN) systems have become more and more popular in our modern life. They have been widely used in many areas, such as smart homes/buildings, context-aware devices, military applications, etc. Despite the increasing usage, there is a lack of formal description and automated verification for WSN system design. In this paper, we present an approach to support the rigorous verification of WSN modeling using the Semantic Web technology We use Web Ontology Language (OWL) and Semantic Web Rule Language (SWRL) to define a meta-ontology for the modeling of WSN systems. Furthermore, we apply ontology reasoners to perform automated verification on customized WSN models and their instances. We demonstrate and evaluate our approach through a Light Control System (LCS) as the case study.

Trust based security mechanisms for wireless sensor networks

Wireless sensor networks are emerging as effective tools in the gathering and dissemination of data. They can be applied in many fields including health, environmental monitoring, home automation and the military. Like all other computing systems it is necessary to include security features, so that security sensitive data traversing the network is protected. However, traditional security techniques cannot be applied to wireless sensor networks. This is due to the constraints of battery power, memory, and the computational capacities of the miniature wireless sensor nodes. Therefore, to address this need, it becomes necessary to develop new lightweight security protocols. This dissertation focuses on designing a suite of lightweight trust-based security mechanisms and a cooperation enforcement protocol for wireless sensor networks. This dissertation presents a trust-based cluster head election mechanism used to elect new cluster heads. This solution prevents a major security breach against the routing protocol, namely, the election of malicious or compromised cluster heads. This dissertation also describes a location-aware, trust-based, compromise node detection, and isolation mechanism. Both of these mechanisms rely on the ability of a node to monitor its neighbors. Using neighbor monitoring techniques, the nodes are able to determine their neighbors’ reputation and trust level through probabilistic modeling. The mechanisms were designed to mitigate internal attacks within wireless sensor networks. The feasibility of the approach is demonstrated through extensive simulations. The dissertation also addresses non-cooperation problems in multi-user wireless sensor networks. A scalable lightweight enforcement algorithm using evolutionary game theory is also designed. The effectiveness of this cooperation enforcement algorithm is validated through mathematical analysis and simulation. This research has advanced the knowledge of wireless sensor network security and cooperation by developing new techniques based on mathematical models. By doing this, we have enabled others to build on our work towards the creation of highly trusted wireless sensor networks. This would facilitate its full utilization in many fields ranging from civilian to military applications.

Cooperative and adaptive medium access control in multi-hop wireless networks

Due to low cost and easy deployment, multi-hop wireless networks become a very attractive communication paradigm. However, IEEE 802.11 medium access control (MAC) protocol widely used in wireless LANs was not designed for multi-hop wireless networks. Although it can support some kinds of ad hoc network architecture, it does not function efficiently in those wireless networks with multi-hop connectivity. Therefore, our research is focused on studying the medium access control in multi-hop wireless networks. The objective is to design practical MAC layer protocols for supporting multihop wireless networks. Particularly, we try to prolong the network lifetime without degrading performances with small battery-powered devices and improve the system throughput with poor quality channels. ^ In this dissertation, we design two MAC protocols. The first one is aimed at minimizing energy-consumption without deteriorating communication activities, which provides energy efficiency, latency guarantee, adaptability and scalability in one type of multi-hop wireless networks (i.e. wireless sensor network). Methodologically, inspired by the phase transition phenomena in distributed networks, we define the wake-up probability, which maintained by each node. By using this probability, we can control the number of wireless connectivity within a local area. More specifically, we can adaptively adjust the wake-up probability based on the local network conditions to reduce energy consumption without increasing transmission latency. The second one is a cooperative MAC layer protocol for multi-hop wireless networks, which leverages multi-rate capability by cooperative transmission among multiple neighboring nodes. Moreover, for bidirectional traffic, the network throughput can be further increased by using the network coding technique. It is a very helpful complement for current rate-adaptive MAC protocols under the poor channel conditions of direct link. Finally, we give an analytical model to analyze impacts of cooperative node on the system throughput. ^

Mitigating inconsistencies by coupling data cleaning, filtering, and contextual data validation in wireless sensor networks

With the advent of peer to peer networks, and more importantly sensor networks, the desire to extract useful information from continuous and unbounded streams of data has become more prominent. For example, in tele-health applications, sensor based data streaming systems are used to continuously and accurately monitor Alzheimer's patients and their surrounding environment. Typically, the requirements of such applications necessitate the cleaning and filtering of continuous, corrupted and incomplete data streams gathered wirelessly in dynamically varying conditions. Yet, existing data stream cleaning and filtering schemes are incapable of capturing the dynamics of the environment while simultaneously suppressing the losses and corruption introduced by uncertain environmental, hardware, and network conditions. Consequently, existing data cleaning and filtering paradigms are being challenged. This dissertation develops novel schemes for cleaning data streams received from a wireless sensor network operating under non-linear and dynamically varying conditions. The study establishes a paradigm for validating spatio-temporal associations among data sources to enhance data cleaning. To simplify the complexity of the validation process, the developed solution maps the requirements of the application on a geometrical space and identifies the potential sensor nodes of interest. Additionally, this dissertation models a wireless sensor network data reduction system by ascertaining that segregating data adaptation and prediction processes will augment the data reduction rates. The schemes presented in this study are evaluated using simulation and information theory concepts. The results demonstrate that dynamic conditions of the environment are better managed when validation is used for data cleaning. They also show that when a fast convergent adaptation process is deployed, data reduction rates are significantly improved. Targeted applications of the developed methodology include machine health monitoring, tele-health, environment and habitat monitoring, intermodal transportation and homeland security.

Resource management and optimization in wireless mesh networks

A wireless mesh network is a mesh network implemented over a wireless network system such as wireless LANs. Wireless Mesh Networks(WMNs) are promising for numerous applications such as broadband home networking, enterprise networking, transportation systems, health and medical systems, security surveillance systems, etc. Therefore, it has received considerable attention from both industrial and academic researchers. This dissertation explores schemes for resource management and optimization in WMNs by means of network routing and network coding.^ In this dissertation, we propose three optimization schemes. (1) First, a triple-tier optimization scheme is proposed for load balancing objective. The first tier mechanism achieves long-term routing optimization, and the second tier mechanism, using the optimization results obtained from the first tier mechanism, performs the short-term adaptation to deal with the impact of dynamic channel conditions. A greedy sub-channel allocation algorithm is developed as the third tier optimization scheme to further reduce the congestion level in the network. We conduct thorough theoretical analysis to show the correctness of our design and give the properties of our scheme. (2) Then, a Relay-Aided Network Coding scheme called RANC is proposed to improve the performance gain of network coding by exploiting the physical layer multi-rate capability in WMNs. We conduct rigorous analysis to find the design principles and study the tradeoff in the performance gain of RANC. Based on the analytical results, we provide a practical solution by decomposing the original design problem into two sub-problems, flow partition problem and scheduling problem. (3) Lastly, a joint optimization scheme of the routing in the network layer and network coding-aware scheduling in the MAC layer is introduced. We formulate the network optimization problem and exploit the structure of the problem via dual decomposition. We find that the original problem is composed of two problems, routing problem in the network layer and scheduling problem in the MAC layer. These two sub-problems are coupled through the link capacities. We solve the routing problem by two different adaptive routing algorithms. We then provide a distributed coding-aware scheduling algorithm. According to corresponding experiment results, the proposed schemes can significantly improve network performance.^

Trust Based Security Mechanisms for Wireless Sensor Networks

Wireless sensor networks are emerging as effective tools in the gathering and dissemination of data. They can be applied in many fields including health, environmental monitoring, home automation and the military. Like all other computing systems it is necessary to include security features, so that security sensitive data traversing the network is protected. However, traditional security techniques cannot be applied to wireless sensor networks. This is due to the constraints of battery power, memory, and the computational capacities of the miniature wireless sensor nodes. Therefore, to address this need, it becomes necessary to develop new lightweight security protocols. This dissertation focuses on designing a suite of lightweight trust-based security mechanisms and a cooperation enforcement protocol for wireless sensor networks. This dissertation presents a trust-based cluster head election mechanism used to elect new cluster heads. This solution prevents a major security breach against the routing protocol, namely, the election of malicious or compromised cluster heads. This dissertation also describes a location-aware, trust-based, compromise node detection, and isolation mechanism. Both of these mechanisms rely on the ability of a node to monitor its neighbors. Using neighbor monitoring techniques, the nodes are able to determine their neighbors’ reputation and trust level through probabilistic modeling. The mechanisms were designed to mitigate internal attacks within wireless sensor networks. The feasibility of the approach is demonstrated through extensive simulations. The dissertation also addresses non-cooperation problems in multi-user wireless sensor networks. A scalable lightweight enforcement algorithm using evolutionary game theory is also designed. The effectiveness of this cooperation enforcement algorithm is validated through mathematical analysis and simulation. This research has advanced the knowledge of wireless sensor network security and cooperation by developing new techniques based on mathematical models. By doing this, we have enabled others to build on our work towards the creation of highly trusted wireless sensor networks. This would facilitate its full utilization in many fields ranging from civilian to military applications.

Mitigating Inconsistencies by Coupling Data Cleaning, Filtering, and Contextual Data Validation in Wireless Sensor Networks

With the advent of peer to peer networks, and more importantly sensor networks, the desire to extract useful information from continuous and unbounded streams of data has become more prominent. For example, in tele-health applications, sensor based data streaming systems are used to continuously and accurately monitor Alzheimer's patients and their surrounding environment. Typically, the requirements of such applications necessitate the cleaning and filtering of continuous, corrupted and incomplete data streams gathered wirelessly in dynamically varying conditions. Yet, existing data stream cleaning and filtering schemes are incapable of capturing the dynamics of the environment while simultaneously suppressing the losses and corruption introduced by uncertain environmental, hardware, and network conditions. Consequently, existing data cleaning and filtering paradigms are being challenged. This dissertation develops novel schemes for cleaning data streams received from a wireless sensor network operating under non-linear and dynamically varying conditions. The study establishes a paradigm for validating spatio-temporal associations among data sources to enhance data cleaning. To simplify the complexity of the validation process, the developed solution maps the requirements of the application on a geometrical space and identifies the potential sensor nodes of interest. Additionally, this dissertation models a wireless sensor network data reduction system by ascertaining that segregating data adaptation and prediction processes will augment the data reduction rates. The schemes presented in this study are evaluated using simulation and information theory concepts. The results demonstrate that dynamic conditions of the environment are better managed when validation is used for data cleaning. They also show that when a fast convergent adaptation process is deployed, data reduction rates are significantly improved. Targeted applications of the developed methodology include machine health monitoring, tele-health, environment and habitat monitoring, intermodal transportation and homeland security.

Modelagem do consumo de energia de redes de sensores sem fio usando SystemC-AMS e stateflow

This work aims at modeling power consumption at the nodes of a Wireless Sensor Network (WSN). For doing so, a finite state machine was implemented by means of SystemC-AMS and Stateflow modeling and simulation tools. In order to achieve this goal, communication data in a WSN were collected. Based on the collected data, a simulation environment for power consumption characterization, which aimed at describing the network operation, was developed. Other than performing power consumption simulation, this environment also takes into account a discharging model as to analyze the battery charge level at any given moment. Such analysis result in a graph illustrating the battery voltage variations as well as its state of charge (SOC). Finally, a case study of the WSN power consumption aims to analyze the acquisition mode and network data communication. With this analysis, it is possible make adjustments in node-sensors to reduce the total power consumption of the network.

Estudo e desenvolvimento de algoritmos criptográficos para redes de sensores sem fio, utilizando técnicas de programação genética

Cryptography is the main form to obtain security in any network. Even in networks with great energy consumption restrictions, processing and memory limitations, as the Wireless Sensors Networks (WSN), this is no different. Aiming to improve the cryptography performance, security and the lifetime of these networks, we propose a new cryptographic algorithm developed through the Genetic Programming (GP) techniques. For the development of the cryptographic algorithm’s fitness criteria, established by the genetic GP, nine new cryptographic algorithms were tested: AES, Blowfish, DES, RC6, Skipjack, Twofish, T-DES, XTEA and XXTEA. Starting from these tests, fitness functions was build taking into account the execution time, occupied memory space, maximum deviation, irregular deviation and correlation coefficient. After obtaining the genetic GP, the CRYSEED and CRYSEED2 was created, algorithms for the 8-bits devices, optimized for WSNs, i.e., with low complexity, few memory consumption and good security for sensing and instrumentation applications.

Estudo e desenvolvimento de algoritmos criptográficos para redes de sensores sem fio, utilizando técnicas de programação genética

Cryptography is the main form to obtain security in any network. Even in networks with great energy consumption restrictions, processing and memory limitations, as the Wireless Sensors Networks (WSN), this is no different. Aiming to improve the cryptography performance, security and the lifetime of these networks, we propose a new cryptographic algorithm developed through the Genetic Programming (GP) techniques. For the development of the cryptographic algorithm’s fitness criteria, established by the genetic GP, nine new cryptographic algorithms were tested: AES, Blowfish, DES, RC6, Skipjack, Twofish, T-DES, XTEA and XXTEA. Starting from these tests, fitness functions was build taking into account the execution time, occupied memory space, maximum deviation, irregular deviation and correlation coefficient. After obtaining the genetic GP, the CRYSEED and CRYSEED2 was created, algorithms for the 8-bits devices, optimized for WSNs, i.e., with low complexity, few memory consumption and good security for sensing and instrumentation applications.

Sviluppo di una interfaccia per l'integrazione della piattaforma inerziale X-Nucleo con una rete di sensori wireless

Questo elaborato presenta il progetto di una interfaccia per l'aggiunta di sensori inerziali ad un nodo di una WSN (Wireless Sensor Network) �finalizzato al monitoraggio delle frane. Analizzando i vantaggi che avrebbe portato l'utilizzo di ulteriori sensori, si �e cercato di fornire un valido approccio di progettazione; in particolare l'idea �e quella di integrarli con un giroscopio ed un accelerometro aventi applicazioni in altri settori. Con questo particolare utilizzo, essi possono portare ad un miglior monitoraggio riuscendo a rilevare i movimenti in modo dettagliato ed a riconoscere i falsi allarmi. Nell'approccio che si intende suggerire verranno sfruttate schede per la prototipazione rapida, user-friendly e con costi decisamente accessibili, adatte alla sperimentazione elettronica e per lo sviluppo di nuovi dispositivi. Attraverso l'utilizzo di ambienti di sviluppo appositamente creati, si sono simulate le comunicazioni tra nodo e scheda di sensori, mettendo in evidenza i vantaggi ottenuti. Buona parte del progetto ha riguardato la programmazione in linguaggio C/C++, con una particolare attenzione al risparmio energetico.

Development of miniaturized antennas and adaptive tuning solutions for body sensor network applications

Wireless Sensor Networks (WSNs) are currently having a revolutionary impact in rapidly emerging wearable applications such as health and fitness monitoring amongst many others. These types of Body Sensor Network (BSN) applications require highly integrated wireless sensor devices for use in a wearable configuration, to monitor various physiological parameters of the user. These new requirements are currently posing significant design challenges from an antenna perspective. This work addresses several design challenges relating to antenna design for these types of applications. In this thesis, a review of current antenna solutions for WSN applications is first presented, investigating both commercial and academic solutions. Key design challenges are then identified relating to antenna size and performance. A detailed investigation of the effects of the human body on antenna impedance characteristics is then presented. A first-generation antenna tuning system is then developed. This system enables the antenna impedance to be tuned adaptively in the presence of the human body. Three new antenna designs are also presented. A compact, low-cost 433 MHz antenna design is first reported and the effects of the human body on the impedance of the antenna are investigated. A tunable version of this antenna is then developed, using a higher performance, second-generation tuner that is integrated within the antenna element itself, enabling autonomous tuning in the presence of the human body. Finally, a compact sized, dual-band antenna is reported that covers both the 433 MHz and 2.45 GHz bands to provide improved quality of service (QoS) in WSN applications. To date, state-of-the-art WSN devices are relatively simple in design with limited antenna options available, especially for the lower UHF bands. In addition, current devices have no capability to deal with changing antenna environments such as in wearable BSN applications. This thesis presents several contributions that advance the state-of-the-art in this area, relating to the design of miniaturized WSN antennas and the development of antenna tuning solutions for BSN applications.

A framework for experimental determination of localised vertical pedestrian forces on full-scale structures using wireless attitude and heading reference systems

A major weakness among loading models for pedestrians walking on flexible structures proposed in recent years is the various uncorroborated assumptions made in their development. This applies to spatio-temporal characteristics of pedestrian loading and the nature of multi-object interactions. To alleviate this problem, a framework for the determination of localised pedestrian forces on full-scale structures is presented using a wireless attitude and heading reference systems (AHRS). An AHRS comprises a triad of tri-axial accelerometers, gyroscopes and magnetometers managed by a dedicated data processing unit, allowing motion in three-dimensional space to be reconstructed. A pedestrian loading model based on a single point inertial measurement from an AHRS is derived and shown to perform well against benchmark data collected on an instrumented treadmill. Unlike other models, the current model does not take any predefined form nor does it require any extrapolations as to the timing and amplitude of pedestrian loading. In order to assess correctly the influence of the moving pedestrian on behaviour of a structure, an algorithm for tracking the point of application of pedestrian force is developed based on data from a single AHRS attached to a foot. A set of controlled walking tests with a single pedestrian is conducted on a real footbridge for validation purposes. A remarkably good match between the measured and simulated bridge response is found, indeed confirming applicability of the proposed framework.

Performance Analysis of IP based WSNs in real time systems

Wireless sensor networks (WSNs) are the key enablers of the internet of things (IoT) paradigm. Traditionally, sensor network research has been to be unlike the internet, motivated by power and device constraints. The IETF 6LoWPAN draft standard changes this, defining how IPv6 packets can be efficiently transmitted over IEEE 802.15.4 radio links. Due to this 6LoWPAN technology, low power, low cost micro- controllers can be connected to the internet forming what is known as the wireless embedded internet. Another IETF recommendation, CoAP allows these devices to communicate interactively over the internet. The integration of such tiny, ubiquitous electronic devices to the internet enables interesting real-time applications. This thesis work attempts to evaluate the performance of a stack consisting of CoAP and 6LoWPAN over the IEEE 802.15.4 radio link using the Contiki OS and Cooja simulator, along with the CoAP framework Californium (Cf). Ultimately, the implementation of this stack on real hardware is carried out using a raspberry pi as a border router with T-mote sky sensors as slip radios and CoAP servers relaying temperature and humidity data. The reliability of the stack was also demonstrated during scalability analysis conducted on the physical deployment. The interoperability is ensured by connecting the WSN to the global internet using different hardware platforms supported by Contiki and without the use of specialized gateways commonly found in non IP based networks. This work therefore developed and demonstrated a heterogeneous wireless sensor network stack, which is IP based and conducted performance analysis of the stack, both in terms of simulations and real hardware.