Distributed cognitive radio systems with temperature-interference constraints and overlay scheme

Cognitive radio represents a promising paradigm to further increase transmission rates in wireless networks, as well as to facilitate the deployment of self-organized networks such as femtocells. Within this framework, secondary users (SU) may exploit the channel under the premise to maintain the quality of service (QoS) on primary users (PU) above a certain level. To achieve this goal, we present a noncooperative game where SU maximize their transmission rates, and may act as well as relays of the PU in order to hold their perceived QoS above the given threshold. In the paper, we analyze the properties of the game within the theory of variational inequalities, and provide an algorithm that converges to one Nash Equilibrium of the game. Finally, we present some simulations and compare the algorithm with another method that does not consider SU acting as relays.

Cognitive strategies for reducing energy consumption in wireless sensor networks

El consumo energético de las Redes de Sensores Inalámbricas (WSNs por sus siglas en inglés) es un problema histórico que ha sido abordado desde diferentes niveles y visiones, ya que no solo afecta a la propia supervivencia de la red sino que el creciente uso de dispositivos inteligentes y el nuevo paradigma del Internet de las Cosas hace que las WSNs tengan cada vez una mayor influencia en la huella energética. Debido a la tendencia al alza en el uso de estas redes se añade un nuevo problema, la saturación espectral. Las WSNs operan habitualmente en bandas sin licencia como son las bandas Industrial, Científica y Médica (ISM por sus siglas en inglés). Estas bandas se comparten con otro tipo de redes como Wi-Fi o Bluetooth cuyo uso ha crecido exponencialmente en los últimos años. Para abordar este problema aparece el paradigma de la Radio Cognitiva (CR), una tecnología que permite el acceso oportunista al espectro. La introducción de capacidades cognitivas en las WSNs no solo permite optimizar su eficiencia espectral sino que también tiene un impacto positivo en parámetros como la calidad de servicio, la seguridad o el consumo energético. Sin embargo, por otra parte, este nuevo paradigma plantea algunos retos relacionados con el consumo energético. Concretamente, el sensado del espectro, la colaboración entre los nodos (que requiere comunicación adicional) y el cambio en los parámetros de transmisión aumentan el consumo respecto a las WSN clásicas. Teniendo en cuenta que la investigación en el campo del consumo energético ha sido ampliamente abordada puesto que se trata de una de sus principales limitaciones, asumimos que las nuevas estrategias deben surgir de las nuevas capacidades añadidas por las redes cognitivas. Por otro lado, a la hora de diseñar estrategias de optimización para CWSN hay que tener muy presentes las limitaciones de recursos de estas redes en cuanto a memoria, computación y consumo energético de los nodos. En esta tesis doctoral proponemos dos estrategias de reducción de consumo energético en CWSNs basadas en tres pilares fundamentales. El primero son las capacidades cognitivas añadidas a las WSNs que proporcionan la posibilidad de adaptar los parámetros de transmisión en función del espectro disponible. La segunda es la colaboración, como característica intrínseca de las CWSNs. Finalmente, el tercer pilar de este trabajo es teoría de juegos como algoritmo de soporte a la decisión, ampliamente utilizado en WSNs debido a su simplicidad. Como primer aporte de la tesis se presenta un análisis completo de las posibilidades introducidas por la radio cognitiva en materia de reducción de consumo para WSNs. Gracias a las conclusiones extraídas de este análisis, se han planteado las hipótesis de esta tesis relacionadas con la validez de usar capacidades cognitivas como herramienta para la reducción de consumo en CWSNs. Una vez presentada las hipótesis, pasamos a desarrollar las principales contribuciones de la tesis: las dos estrategias diseñadas para reducción de consumo basadas en teoría de juegos y CR. La primera de ellas hace uso de un juego no cooperativo que se juega mediante pares de jugadores. En la segunda estrategia, aunque el juego continúa siendo no cooperativo, se añade el concepto de colaboración. Para cada una de las estrategias se presenta el modelo del juego, el análisis formal de equilibrios y óptimos y la descripción de la estrategia completa donde se incluye la interacción entre nodos. Con el propósito de probar las estrategias mediante simulación e implementación en dispositivos reales hemos desarrollado un marco de pruebas compuesto por un simulador cognitivo y un banco de pruebas formado por nodos cognitivos capaces de comunicarse en tres bandas ISM desarrollados en el B105 Lab. Este marco de pruebas constituye otra de las aportaciones de la tesis que permitirá el avance en la investigación en el área de las CWSNs. Finalmente, se presentan y discuten los resultados derivados de la prueba de las estrategias desarrolladas. La primera estrategia proporciona ahorros de energía mayores al 65% comparados con una WSN sin capacidades cognitivas y alrededor del 25% si la comparamos con una estrategia cognitiva basada en el sensado periódico del espectro para el cambio de canal de acuerdo a un nivel de ruido fijado. Este algoritmo se comporta de forma similar independientemente del nivel de ruido siempre que éste sea espacialmente uniformemente. Esta estrategia, a pesar de su sencillez, nos asegura el comportamiento óptimo en cuanto a consumo energético debido a la utilización de teoría de juegos en la fase de diseño del comportamiento de los nodos. La estrategia colaborativa presenta mejoras respecto a la anterior en términos de protección frente al ruido en escenarios de ruido más complejos donde aporta una mejora del 50% comparada con la estrategia anterior. ABSTRACT Energy consumption in Wireless Sensor Networks (WSNs) is a known historical problem that has been addressed from different areas and on many levels. But this problem should not only be approached from the point of view of their own efficiency for survival. A major portion of communication traffic has migrated to mobile networks and systems. The increased use of smart devices and the introduction of the Internet of Things (IoT) give WSNs a great influence on the carbon footprint. Thus, optimizing the energy consumption of wireless networks could reduce their environmental impact considerably. In recent years, another problem has been added to the equation: spectrum saturation. Wireless Sensor Networks usually operate in unlicensed spectrum bands such as Industrial, Scientific, and Medical (ISM) bands shared with other networks (mainly Wi-Fi and Bluetooth). To address the efficient spectrum utilization problem, Cognitive Radio (CR) has emerged as the key technology that enables opportunistic access to the spectrum. Therefore, the introduction of cognitive capabilities to WSNs allows optimizing their spectral occupation. Cognitive Wireless Sensor Networks (CWSNs) do not only increase the reliability of communications, but they also have a positive impact on parameters such as the Quality of Service (QoS), network security, or energy consumption. These new opportunities introduced by CWSNs unveil a wide field in the energy consumption research area. However, this also implies some challenges. Specifically, the spectrum sensing stage, collaboration among devices (which requires extra communication), and changes in the transmission parameters increase the total energy consumption of the network. When designing CWSN optimization strategies, the fact that WSN nodes are very limited in terms of memory, computational power, or energy consumption has to be considered. Thus, light strategies that require a low computing capacity must be found. Since the field of energy conservation in WSNs has been widely explored, we assume that new strategies could emerge from the new opportunities presented by cognitive networks. In this PhD Thesis, we present two strategies for energy consumption reduction in CWSNs supported by three main pillars. The first pillar is that cognitive capabilities added to the WSN provide the ability to change the transmission parameters according to the spectrum. The second pillar is that the ability to collaborate is a basic characteristic of CWSNs. Finally, the third pillar for this work is the game theory as a decision-making algorithm, which has been widely used in WSNs due to its lightness and simplicity that make it valid to operate in CWSNs. For the development of these strategies, a complete analysis of the possibilities is first carried out by incorporating the cognitive abilities into the network. Once this analysis has been performed, we expose the hypotheses of this thesis related to the use of cognitive capabilities as a useful tool to reduce energy consumption in CWSNs. Once the analyses are exposed, we present the main contribution of this thesis: the two designed strategies for energy consumption reduction based on game theory and cognitive capabilities. The first one is based on a non-cooperative game played between two players in a simple and selfish way. In the second strategy, the concept of collaboration is introduced. Despite the fact that the game used is also a non-cooperative game, the decisions are taken through collaboration. For each strategy, we present the modeled game, the formal analysis of equilibrium and optimum, and the complete strategy describing the interaction between nodes. In order to test the strategies through simulation and implementation in real devices, we have developed a CWSN framework composed by a CWSN simulator based on Castalia and a testbed based on CWSN nodes able to communicate in three different ISM bands. We present and discuss the results derived by the energy optimization strategies. The first strategy brings energy improvement rates of over 65% compared to WSN without cognitive techniques. It also brings energy improvement rates of over 25% compared with sensing strategies for changing channels based on a decision threshold. We have also seen that the algorithm behaves similarly even with significant variations in the level of noise while working in a uniform noise scenario. The collaborative strategy presents improvements respecting the previous strategy in terms of noise protection when the noise scheme is more complex where this strategy shows improvement rates of over 50%.

Vertical handover supporting pervasive computing in future wireless networks

A variety of current and future wired and wireless networking technologies can be transformed into a seamless communication environments through application of context-based vertical handovers. Such seamless communication environments are needed for future pervasive/ubiquitous systems. Pervasive systems are context aware and need to adapt to context changes, including network disconnections and changes in network Quality of Service (QoS). Vertical handover is one of many possible adaptation methods. It allows users to roam freely between heterogeneous networks while maintaining the continuity of their applications. This paper proposes a vertical handover mechanism suitable for multimedia applications in pervasive systems. The paper focuses on the handover decision making process which uses context information regarding user devices, user location, network environment and requested QoS. (C) 2004 Elsevier B.V. All rights reserved.

Vertical handover based adaptions for multimedia applications in pervasive systems

This paper proposes an architecture for pervasive computing which utilizes context information to provide adaptations based on vertical handovers (handovers between heterogeneous networks) while supporting application Quality of Service (QoS). The future of mobile computing will see an increase in ubiquitous network connectivity which allows users to roam freely between heterogeneous networks. One of the requirements for pervasive computing is to adapt computing applications or their environment if current applications can no longer be provided with the requested QoS. One of possible adaptations is a vertical handover to a different network. Vertical handover operations include changing network interfaces on a single device or changes between different devices. Such handovers should be performed with minimal user distraction and minimal violation of communication QoS for user applications. The solution utilises context information regarding user devices, user location, application requirements, and network environment. The paper shows how vertical handover adaptations are incorporated into the whole infrastructure of a pervasive system

Vertical handovers as adaption methods in pervasive systems

Pervasive systems need to be context aware and need to adapt to context changes, including network disconnections and changes in network Quality of Service (QoS). Vertical handover (handover between heterogeneous networks) is one of possible adaptation methods. It allows users to roam freely between heterogeneous networks while maintaining continuity of their applications. This paper proposes a vertical handover approach suitable for multimedia applications in pervasive systems. It describes the adaptability decision making process which uses vertical handovers to support users mobility and provision of QoS suitable for users’ applications. The process evaluates context information regarding user devices, User location, network environment, and user perceived QoS of applications.

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.

Performance analysis of DSRC priority mechanism for road safety applications in vehicular networks

Dedicated short range communications (DSRC) has been regarded as one of the most promising technologies to provide robust communications for large scale vehicle networks. It is designed to support both road safety and commercial applications. Road safety applications will require reliable and timely wireless communications. However, as the medium access control (MAC) layer of DSRC is based on the IEEE 802.11 distributed coordination function (DCF), it is well known that the random channel access based MAC cannot provide guaranteed quality of services (QoS). It is very important to understand the quantitative performance of DSRC, in order to make better decisions on its adoption, control, adaptation, and improvement. In this paper, we propose an analytic model to evaluate the DSRC-based inter-vehicle communication. We investigate the impacts of the channel access parameters associated with the different services including arbitration inter-frame space (AIFS) and contention window (CW). Based on the proposed model, we analyze the successful message delivery ratio and channel service delay for broadcast messages. The proposed analytical model can provide a convenient tool to evaluate the inter-vehicle safety applications and analyze the suitability of DSRC for road safety applications.

Unified model for performance analysis of IEEE 802.11 ad hoc networks in unsaturated conditions

IEEE 802.11 standard has achieved huge success in the past decade and is still under development to provide higher physical data rate and better quality of service (QoS). An important problem for the development and optimization of IEEE 802.11 networks is the modeling of the MAC layer channel access protocol. Although there are already many theoretic analysis for the 802.11 MAC protocol in the literature, most of the models focus on the saturated traffic and assume infinite buffer at the MAC layer. In this paper we develop a unified analytical model for IEEE 802.11 MAC protocol in ad hoc networks. The impacts of channel access parameters, traffic rate and buffer size at the MAC layer are modeled with the assistance of a generalized Markov chain and an M/G/1/K queue model. The performance of throughput, packet delivery delay and dropping probability can be achieved. Extensive simulations show the analytical model is highly accurate. From the analytical model it is shown that for practical buffer configuration (e.g. buffer size larger than one), we can maximize the total throughput and reduce the packet blocking probability (due to limited buffer size) and the average queuing delay to zero by effectively controlling the offered load. The average MAC layer service delay as well as its standard deviation, is also much lower than that in saturated conditions and has an upper bound. It is also observed that the optimal load is very close to the maximum achievable throughput regardless of the number of stations or buffer size. Moreover, the model is scalable for performance analysis of 802.11e in unsaturated conditions and 802.11 ad hoc networks with heterogenous traffic flows. © 2012 KSI.

Call admission control algorithms in OFDM-based wireless multiservice networks

Orthogonal frequency division multiplexing (OFDM) is becoming a fundamental technology in future generation wireless communications. Call admission control is an effective mechanism to guarantee resilient, efficient, and quality-of-service (QoS) services in wireless mobile networks. In this paper, we present several call admission control algorithms for OFDM-based wireless multiservice networks. Call connection requests are differentiated into narrow-band calls and wide-band calls. For either class of calls, the traffic process is characterized as batch arrival since each call may request multiple subcarriers to satisfy its QoS requirement. The batch size is a random variable following a probability mass function (PMF) with realistically maximum value. In addition, the service times for wide-band and narrow-band calls are different. Following this, we perform a tele-traffic queueing analysis for OFDM-based wireless multiservice networks. The formulae for the significant performance metrics call blocking probability and bandwidth utilization are developed. Numerical investigations are presented to demonstrate the interaction between key parameters and performance metrics. The performance tradeoff among different call admission control algorithms is discussed. Moreover, the analytical model has been validated by simulation. The methodology as well as the result provides an efficient tool for planning next-generation OFDM-based broadband wireless access systems.

Bandwidth management of WiMAX systems and performance modeling

WiMAX has been introduced as a competitive alternative for metropolitan broadband wireless access technologies. It is connection oriented and it can provide very high data rates, large service coverage, and flexible quality of services (QoS). Due to the large number of connections and flexible QoS supported by WiMAX, the uplink access in WiMAX networks is very challenging since the medium access control (MAC) protocol must efficiently manage the bandwidth and related channel allocations. In this paper, we propose and investigate a cost-effective WiMAX bandwidth management scheme, named the WiMAX partial sharing scheme (WPSS), in order to provide good QoS while achieving better bandwidth utilization and network throughput. The proposed bandwidth management scheme is compared with a simple but inefficient scheme, named the WiMAX complete sharing scheme (WCPS). A maximum entropy (ME) based analytical model (MEAM) is proposed for the performance evaluation of the two bandwidth management schemes. The reason for using MEAM for the performance evaluation is that MEAM can efficiently model a large-scale system in which the number of stations or connections is generally very high, while the traditional simulation and analytical (e.g., Markov models) approaches cannot perform well due to the high computation complexity. We model the bandwidth management scheme as a queuing network model (QNM) that consists of interacting multiclass queues for different service classes. Closed form expressions for the state and blocking probability distributions are derived for those schemes. Simulation results verify the MEAM numerical results and show that WPSS can significantly improve the network's performance compared to WCPS.

Adaptive rate control of dedicated short range communications based vehicle networks for road safety applications

Dedicated Short Range Communication (DSRC) is a promising technique for vehicle ad-hoc network (VANET) and collaborative road safety applications. As road safety applications require strict quality of services (QoS) from the VANET, it is crucial for DSRC to provide timely and reliable communications to make safety applications successful. In this paper we propose two adaptive message rate control algorithms for low priority safety messages, in order to provide highly available channel for high priority emergency messages while improve channel utilization. In the algorithms each vehicle monitors channel loads and independently controls message rate by a modified additive increase and multiplicative decrease (AIMD) method. Simulation results demonstrated the effectiveness of the proposed rate control algorithms in adapting to dynamic traffic load.

Service differentiation for the bandwidth request scheme in fixed IEEE 802.16 networks

IEEE 802.16 standards have been developed as one of the technical solutions for broadband wireless access systems. It has high data rate, large network coverage, flexible QoS schemes and cheap network deployment. Various flexible mechanisms related to QoS provisioning have been specified for uplink traffic at the medium access control (MAC) layer in the standards. Among the mechanisms, contention based bandwidth request scheme can be used to indicate bandwidth demands to the base station for the non-real-time polling and besteffort services. These two services are used for most application with unknown traffic characteristics. Due to the diverse QoS requirements of those applications, service differentiation (SD) is anticipated over the contention based bandwidth request scheme. In this paper we investigate the SD with the bandwidth request scheme by means of assigning different channel access parameters and bandwidth allocation priorities. The effectiveness of the differentiation schemes are evaluated by simulations. It is observed that the initial backoff window can be efficient in SD, and if combined with the bandwidth allocation priority, the SD performances will be better. ©2008 IEEE.

Two-phases control of DSRC Vehicle networks for road intersection coexisting safety applications

In this paper we propose a two phases control method for DSRC vehicle networks at road intersection, where multiple road safety applications may coexist. We consider two safety applications, emergency safety application with high priority and routine safety applications with low priority. The control method is designed to provide high availability and low latency for emergency safety applications while leave as much as possible bandwidth for routine applications. It is expected to be capable of adapting to changing network conditions. In the first phase of the method we use a simulation based offline approach to find out the best configurations for message rate and MAC layer parameters for given numbers of vehicles. In the second phase we use the configurations identified by simulations at roadside access point (AP) for system operation. A utilization function is proposed to balance the QoS performances provided to multiple safety applications. It is demonstrated that the proposed method can largely improve the system performance when compared to fixed control method.

Adaptive congestion control of DSRC vehicle networks for collaborative road safety applications

Congestion control is critical for the provisioning of quality of services (QoS) over dedicated short range communications (DSRC) vehicle networks for road safety applications. In this paper we propose a congestion control method for DSRC vehicle networks at road intersection, with the aims of providing high availability and low latency channels for high priority emergency safety applications while maximizing channel utilization for low priority routine safety applications. In this method a offline simulation based approach is used to find out the best possible configurations of message rate and MAC layer backoff exponent (BE) for a given number of vehicles equipped with DSRC radios. The identified best configurations are then used online by an roadside access point (AP) for system operation. Simulation results demonstrated that this adaptive method significantly outperforms the fixed control method under varying number of vehicles. The impact of estimation error on the number of vehicles in the network on system level performance is also investigated.

Market-awareness in service-based systems

Service-based systems are applications built by composing pre-existing services. During design time and according to the specifications, a set of services is selected. Both, service providers and consumers exist in a service market that is constantly changing. Service providers continuously change their quality of services (QoS), and service consumers can update their specifications according to what the market is offering. Therefore, during runtime, the services are periodically and manually checked to verify if they still satisfy the specifications. Unfortunately, humans are overwhelmed with the degree of changes exhibited by the service market. Consequently, verification of the compliance specification and execution of the corresponding adaptations when deviations are detected cannot be carried out in a manual fashion. In this work, we propose a framework to enable online awareness of changes in the service market in both consumers and providers by representing them as active software agents. At runtime, consumer agents concretize QoS specifications according to the available market knowledge. Services agents are collectively aware of themselves and of the consumers' requests. Moreover, they can create and maintain virtual organizations to react actively to demands that come from the market. In this paper we show preliminary results that allow us to conclude that the creation and adaptation of service-based systems can be carried out by a self-organized service market system. © 2012 IEEE.