Cognitive test-bed for wireless sensor networks

Cognitive Wireless Sensor Networks are an emerging technology with a vast potential to avoid traditional wireless problems such as reliability, interferences and spectrum scarcity in Wireless Sensor Networks. Cognitive Wireless Sensor Networks test-beds are an important tool for future developments, protocol strategy testing and algorithm optimization in real scenarios. A new cognitive test-bed for Cognitive Wireless Sensor Networks is presented in this paper. This work in progress includes both the design of a cognitive simulator for networks with a high number of nodes and the implementation of a new platform with three wireless interfaces and a cognitive software for extracting real data. Finally, as a future work, a remote programmable system and the planning for the physical deployment of the nodes at the university building is presented.

The Balanced Cross-Layer Design Routing Algorithm in Wireless Sensor Networks Using Fuzzy Logic

Recently, the cross-layer design for the wireless sensor network communication protocol has become more and more important and popular. Considering the disadvantages of the traditional cross-layer routing algorithms, in this paper we propose a new fuzzy logic-based routing algorithm, named the Balanced Cross-layer Fuzzy Logic (BCFL) routing algorithm. In BCFL, we use the cross-layer parameters’ dispersion as the fuzzy logic inference system inputs. Moreover, we give each cross-layer parameter a dynamic weight according the value of the dispersion. For getting a balanced solution, the parameter whose dispersion is large will have small weight, and vice versa. In order to compare it with the traditional cross-layer routing algorithms, BCFL is evaluated through extensive simulations. The simulation results show that the new routing algorithm can handle the multiple constraints without increasing the complexity of the algorithm and can achieve the most balanced performance on selecting the next hop relay node. Moreover, the Balanced Cross-layer Fuzzy Logic routing algorithm can adapt to the dynamic changing of the network conditions and topology effectively.

Cognitive strategies for security in wireless sensor networks

Las redes de sensores inalámbricas son uno de los sectores con más crecimiento dentro de las redes inalámbricas. La rápida adopción de estas redes como solución para muchas nuevas aplicaciones ha llevado a un creciente tráfico en el espectro radioeléctrico. Debido a que las redes inalámbricas de sensores operan en las bandas libres Industrial, Scientific and Medical (ISM) se ha producido una saturación del espectro que en pocos años no permitirá un buen funcionamiento. Con el objetivo de solucionar este tipo de problemas ha aparecido el paradigma de Radio Cognitiva (CR). La introducción de las capacidades cognitivas en las redes inalámbricas de sensores permite utilizar estas redes para aplicaciones con unos requisitos más estrictos respecto a fiabilidad, cobertura o calidad de servicio. Estas redes que aúnan todas estas características son llamadas redes de sensores inalámbricas cognitivas (CWSNs). La mejora en prestaciones de las CWSNs permite su utilización en aplicaciones críticas donde antes no podían ser utilizadas como monitorización de estructuras, de servicios médicos, en entornos militares o de vigilancia. Sin embargo, estas aplicaciones también requieren de otras características que la radio cognitiva no nos ofrece directamente como, por ejemplo, la seguridad. La seguridad en CWSNs es un aspecto poco desarrollado al ser una característica no esencial para su funcionamiento, como pueden serlo el sensado del espectro o la colaboración. Sin embargo, su estudio y mejora es esencial de cara al crecimiento de las CWSNs. Por tanto, esta tesis tiene como objetivo implementar contramedidas usando las nuevas capacidades cognitivas, especialmente en la capa física, teniendo en cuenta las limitaciones con las que cuentan las WSNs. En el ciclo de trabajo de esta tesis se han desarrollado dos estrategias de seguridad contra ataques de especial importancia en redes cognitivas: el ataque de simulación de usuario primario (PUE) y el ataque contra la privacidad eavesdropping. Para mitigar el ataque PUE se ha desarrollado una contramedida basada en la detección de anomalías. Se han implementado dos algoritmos diferentes para detectar este ataque: el algoritmo de Cumulative Sum y el algoritmo de Data Clustering. Una vez comprobado su validez se han comparado entre sí y se han investigado los efectos que pueden afectar al funcionamiento de los mismos. Para combatir el ataque de eavesdropping se ha desarrollado una contramedida basada en la inyección de ruido artificial de manera que el atacante no distinga las señales con información del ruido sin verse afectada la comunicación que nos interesa. También se ha estudiado el impacto que tiene esta contramedida en los recursos de la red. Como resultado paralelo se ha desarrollado un marco de pruebas para CWSNs que consta de un simulador y de una red de nodos cognitivos reales. Estas herramientas han sido esenciales para la implementación y extracción de resultados de la tesis. ABSTRACT Wireless Sensor Networks (WSNs) are one of the fastest growing sectors in wireless networks. The fast introduction of these networks as a solution in many new applications has increased the traffic in the radio spectrum. Due to the operation of WSNs in the free industrial, scientific, and medical (ISM) bands, saturation has ocurred in these frequencies that will make the same operation methods impossible in the future. Cognitive radio (CR) has appeared as a solution for this problem. The networks that join all the mentioned features together are called cognitive wireless sensor networks (CWSNs). The adoption of cognitive features in WSNs allows the use of these networks in applications with higher reliability, coverage, or quality of service requirements. The improvement of the performance of CWSNs allows their use in critical applications where they could not be used before such as structural monitoring, medical care, military scenarios, or security monitoring systems. Nevertheless, these applications also need other features that cognitive radio does not add directly, such as security. The security in CWSNs has not yet been explored fully because it is not necessary field for the main performance of these networks. Instead, other fields like spectrum sensing or collaboration have been explored deeply. However, the study of security in CWSNs is essential for their growth. Therefore, the main objective of this thesis is to study the impact of some cognitive radio attacks in CWSNs and to implement countermeasures using new cognitive capabilities, especially in the physical layer and considering the limitations of WSNs. Inside the work cycle of this thesis, security strategies against two important kinds of attacks in cognitive networks have been developed. These attacks are the primary user emulator (PUE) attack and the eavesdropping attack. A countermeasure against the PUE attack based on anomaly detection has been developed. Two different algorithms have been implemented: the cumulative sum algorithm and the data clustering algorithm. After the verification of these solutions, they have been compared and the side effects that can disturb their performance have been analyzed. The developed approach against the eavesdropping attack is based on the generation of artificial noise to conceal information messages. The impact of this countermeasure on network resources has also been studied. As a parallel result, a new framework for CWSNs has been developed. This includes a simulator and a real network with cognitive nodes. This framework has been crucial for the implementation and extraction of the results presented in this thesis.

Traffic based energy consumption optimisation to improve the lifetime and performance of ad hoc wireless sensor networks

Ad hoc wireless sensor networks (WSNs) are formed from self-organising configurations of distributed, energy constrained, autonomous sensor nodes. The service lifetime of such sensor nodes depends on the power supply and the energy consumption, which is typically dominated by the communication subsystem. One of the key challenges in unlocking the potential of such data gathering sensor networks is conserving energy so as to maximize their post deployment active lifetime. This thesis described the research carried on the continual development of the novel energy efficient Optimised grids algorithm that increases the WSNs lifetime and improves on the QoS parameters yielding higher throughput, lower latency and jitter for next generation of WSNs. Based on the range and traffic relationship the novel Optimised grids algorithm provides a robust traffic dependent energy efficient grid size that minimises the cluster head energy consumption in each grid and balances the energy use throughout the network. Efficient spatial reusability allows the novel Optimised grids algorithm improves on network QoS parameters. The most important advantage of this model is that it can be applied to all one and two dimensional traffic scenarios where the traffic load may fluctuate due to sensor activities. During traffic fluctuations the novel Optimised grids algorithm can be used to re-optimise the wireless sensor network to bring further benefits in energy reduction and improvement in QoS parameters. As the idle energy becomes dominant at lower traffic loads, the new Sleep Optimised grids model incorporates the sleep energy and idle energy duty cycles that can be implemented to achieve further network lifetime gains in all wireless sensor network models. Another key advantage of the novel Optimised grids algorithm is that it can be implemented with existing energy saving protocols like GAF, LEACH, SMAC and TMAC to further enhance the network lifetimes and improve on QoS parameters. The novel Optimised grids algorithm does not interfere with these protocols, but creates an overlay to optimise the grids sizes and hence transmission range of wireless sensor nodes.

In-Motes EYE:a real time application for automobiles in wireless sensor networks

Wireless sensor networks have been identified as one of the key technologies for the 21st century. In order to overcome their limitations such as fault tolerance and conservation of energy, we propose a middleware solution, In-Motes. In-Motes stands as a fault tolerant platform for deploying and monitoring applications in real time offers a number of possibilities for the end user giving him in parallel the freedom to experiment with various parameters, in an effort the deployed applications to run in an energy efficient manner inside the network. The proposed scheme is evaluated through the In-Motes EYE application, aiming to test its merits under real time conditions. In-Motes EYE application which is an agent based real time In-Motes application developed for sensing acceleration variations in an environment. The application was tested in a prototype area, road alike, for a period of four months.

A hierarchical localization scheme for large scale underwater wireless sensor networks

In this paper, we study the localization problem in large-scale Underwater Wireless Sensor Networks (UWSNs). Unlike in the terrestrial positioning, the global positioning system (GPS) can not work efficiently underwater. The limited bandwidth, the severely impaired channel and the cost of underwater equipment all makes the localization problem very challenging. Most current localization schemes are not well suitable for deep underwater environment. We propose a hierarchical localization scheme to address the challenging problems. The new scheme mainly consists of four types of nodes, which are surface buoys, Detachable Elevator Transceivers (DETs), anchor nodes and ordinary nodes. Surface buoy is assumed to be equipped with GPS on the water surface. A DET is attached to a surface buoy and can rise and down to broadcast its position. The anchor nodes can compute their positions based on the position information from the DETs and the measurements of distance to the DETs. The hierarchical localization scheme is scalable, and can be used to make balances on the cost and localization accuracy. Initial simulation results show the advantages of our proposed scheme. © 2009 IEEE.

An area localization scheme for large scale underwater wireless sensor networks

In this paper, we study an area localization problem in large scale Underwater Wireless Sensor Networks (UWSNs). The limited bandwidth, the severely impaired channel and the cost of underwater equipment all makes the underwater localization problem very challenging. Exact localization is very difficult for UWSNs in deep underwater environment. We propose a Mobile DETs based efficient 3D multi-power Area Localization Scheme (3D-MALS) to address the challenging problem. In the proposed scheme, the ideas of 2D multi-power Area Localization Scheme(2D-ALS) [6] and utilizing Detachable Elevator Transceiver (DET) are used to achieve the simplicity, location accuracy, scalability and low cost performances. The DET can rise and down to broadcast its position. And it is assumed that all the underwater nodes underwater have pressure sensors and know their z coordinates. The simulation results show that our proposed scheme is very efficient. © 2009 IEEE.

An adaptive code position modulation scheme for wireless sensor networks

In this letter, an energy-efficient adaptive code position modulation scheme is proposed for wireless sensor networks to provide the relatively stable bit error ratio (BER) performance expected by the upper layers. The system is designed with focus on the adaptive control of transmission power, which is adjusted based on the measured power density of background noise. Interfaces among the modulation module, packet scheduling module and upper layer are provided for flexible adjustments to adapt to the background noise and deliver expected application quality. Simulations with Signal Processing Worksystem (SPW) validate the effectiveness of the scheme. © 2005 IEEE.

Radio range adjustment for energy efficient wireless sensor networks

In wireless ad hoc sensor networks, energy use is in many cases the most important constraint since it corresponds directly to operational lifetime. Topology management schemes such as GAF put the redundant nodes for routing to sleep in order to save the energy. The radio range will affect the number of neighbouring nodes, which collaborate to forward data to a base station or sink. In this paper we study a simple linear network and deduce the relationship between optimal radio range and traffic. We find that half of the power can be saved if the radio range is adjusted appropriately compared with the best case where equal radio ranges are used.

Energy efficient transmission protocol for distributed source coding in sensor networks

Distributed source coding (DSC) has recently been considered as an efficient approach to data compression in wireless sensor networks (WSN). Using this coding method multiple sensor nodes compress their correlated observations without inter-node communications. Therefore energy and bandwidth can be efficiently saved. In this paper, we investigate a randombinning based DSC scheme for remote source estimation in WSN and its performance of estimated signal to distortion ratio (SDR). With the introduction of a detailed power consumption model for wireless sensor communications, we quantitatively analyze the overall network energy consumption of the DSC scheme. We further propose a novel energy-aware transmission protocol for the DSC scheme, which flexibly optimizes the DSC performance in terms of either SDR or energy consumption, by adapting the source coding and transmission parameters to the network conditions. Simulations validate the energy efficiency of the proposed adaptive transmission protocol. © 2007 IEEE.

Energy aware data gathering based on adaptive modulation scaling in wireless sensor networks

Energy consumption has been a key concern of data gathering in wireless sensor networks. Previous research works show that modulation scaling is an efficient technique to reduce energy consumption. However, such technique will also impact on both packet delivery latency and packet loss, therefore, may result in adverse effects on the qualities of applications. In this paper, we study the problem of modulation scaling and energy-optimization. A mathematical model is proposed to analyze the impact of modulation scaling on the overall energy consumption, end-to-end mean delivery latency and mean packet loss rate. A centralized optimal management mechanism is developed based on the model, which adaptively adjusts the modulation levels to minimize energy consumption while ensuring the QoS for data gathering. Experimental results show that the management mechanism saves significant energy in all the investigated scenarios. Some valuable results are also observed in the experiments. © 2004 IEEE.

Energy hole mitigation through cooperative transmission in wireless sensor networks

The energy balancing capability of cooperative communication is utilized to solve the energy hole problem in wireless sensor networks. We first propose a cooperative transmission strategy, where intermediate nodes participate in two cooperative multi-input single-output (MISO) transmissions with the node at the previous hop and a selected node at the next hop, respectively. Then, we study the optimization problems for power allocation of the cooperative transmission strategy by examining two different approaches: network lifetime maximization (NLM) and energy consumption minimization (ECM). For NLM, the numerical optimal solution is derived and a searching algorithm for suboptimal solution is provided when the optimal solution does not exist. For ECM, a closed-form solution is obtained. Numerical and simulation results show that both the approaches have much longer network lifetime than SISO transmission strategies and other cooperative communication schemes. Moreover, NLM which features energy balancing outperforms ECM which focuses on energy efficiency, in the network lifetime sense.