Spectrum-efficient Architecture for Cognitive Wireless Sensor Networks

Projecte realitzat en col.laboració amb el centre Université Libre de BruxellesHoy en día existe la creencia de que en unos pocos años las actuales Redes Inalámbricas de Sensores estarán presentes en muchas aplicaciones. Mientras estas sigan actuando en la banda sin licencia de ISM 2,4GHz, tendrán que coexistir con otras exitosas tecnologías como Wi-Fi o Bluetooth. En consecuencia, resulta obvio asegurar que la banda en cuestión estará superpoblada en un futuro próximo. Sin embargo y gracias a las nuevas técnicas de Radio Cognitiva, que permitirán la aplicación de un eficiente Acceso al Espectro Dinámico, se conseguirá una distribución racional, dentro del espectro disponible en ese momento y lugar, de las comunicaciones inalámbricas que se estén llevando a cabo. Esta actuación permitirá acceder a frecuencias menos pobladas para poder transmitir con menos interferencias e incluso con menos pérdidas de propagación. A lo largo de este trabajo se va a presentar una arquitectura eficiente, espectralmente hablando, para Redes Inalámbricas de Sensores y Cognitivas. Este esquema desarrolla un protocolo de recolección de datos, para una red con topología de árbol, totalmente escalable y con finalidades genéricas. A través de las pruebas realizadas, podemos afirmar que nuestro esquema, sin alterar el ciclo normal de recolección de datos, puede detectar la presencia de otras Redes Inalámbricas de Sensores y, consecuentemente, migrar la red a nueva frecuencia mientras que todas estas operaciones están ocultas al usuario final. También es eficiente a nivel de energía, ya que no se realizan comprobaciones redundantes de la presencia de otras redes. De esta manera, nuestra propuesta asegura un mejor comportamiento en caso de la existencia de una Red Inalámbrica de Sensores externa, sin realizar operaciones complicadas ni añadiendo más tráfico a la red

An optimal path selection using lion optimization routing protocol for mobile ad-hoc network

MANET is a set of nodes that communicate with each other directly or indirectly. The nodes in MANET can be moved freely. The dynamic nature of the network makes several challenges. One of the challenges in routing is to transfer the data from the start node (source) to the end node (destination). Routing suffers from several metrics such as power-consuming, delay, packet delivery ratio, etc. This paper proposed a new protocol called the Lion Optimization Routing protocol (LORP) based on the lion algorithm and AODV protocol. This protocol uses the Lion Optimization Algorithm to select the optimal path. Firstly, we use lion optimization to select the optimal path using the LOA maximization algorithm depending on three main metrics Power Efficiency, Throughput, and Packet Delivery Ratio. Secondly, we use the LOA minimization algorithm to select the optimal path using two metrics Delay and Short Path. In LOA Maximization algorithm metrics calculated and choose the max path value. The result of this protocol is compared with AODV, DSR, and ANTHOCNET

Efficient Garbage Disposal Management in Metropolitan Cities Using VANETs

Rapid increase in population, has led to improper waste management in metropolitan cities resulting in increased pests and spreading of diseases. An efficient method to dispose this waste has been designed with Wireless Sensor Networks (WSN) using VANETs. IEEE 802.11p has been adopted and multicast routing has been proposed to be implemented in Garbage Collecting Vehicle’s (GCV) On Board Units (OBU) for effective communication. Road Side Units (RSU) and sensors have been made use of in the response system. Filling up of multiple bins at the same time and usage of reserve GCVs has been considered. The prototype VANET based efficient garbage disposal system is induced in a metropolitan city environment and has been simulated in NS2and the results are encouraging for implementation

Location Error Minimization with the Help of Run Time Coordinates Estimation Method

The energy is the limited resource of communication in Wireless Sensor Network (WSN). The nodes proper functions in WSN are depend on the battery power. The each node in network are mobile and having different mobility speed. The topology in WSN is forming completely dynamic and change according to time instance. The signal strength of node/s is varying according to power capacity of nodes. The less energy of sensor nodes is shows weak signal strength that means having weak Received Signal Strength (RSS). If the signal strength of nodes are reduced that means the nodes have insufficient energy. In this research we proposed the Location based RSS scheme to improve energy utilization.  In this research we compare the performance of protocols like existing AIES-RSS and proposed Location based RSS. The performance of proposed scheme is better than AIES-RSS and the performance of proposed scheme is provides better routing performance in WSN as compare to AIES-RSS. If the RSS of any node in network is weak that means the nodes energy level is down. If the node/s having sufficient amount of energy then their signal strength is high. The Location records of sensor nodes are provides the information of location that’s why routing efficiency is improves and also the energy consumption is reduced. The proposed method is improves the energy utilization and also the residual energy cost is maximum after complete simulation. The proposed scheme is provides the strong connection by that the packet dropping and overhead is minimized. Keywords:- RSS, Routing, Location, AIES-RSS, Energy, proposed RSS, WSN

Efficient Compressive Sampling of Spatially Sparse Fields in Wireless Sensor Networks

Wireless sensor networks (WSN), i.e. networks of autonomous, wireless sensing nodes spatially deployed over a geographical area, are often faced with acquisition of spatially sparse fields. In this paper, we present a novel bandwidth/energy efficient CS scheme for acquisition of spatially sparse fields in a WSN. The paper contribution is twofold. Firstly, we introduce a sparse, structured CS matrix and we analytically show that it allows accurate reconstruction of bidimensional spatially sparse signals, such as those occurring in several surveillance application. Secondly, we analytically evaluate the energy and bandwidth consumption of our CS scheme when it is applied to data acquisition in a WSN. Numerical results demonstrate that our CS scheme achieves significant energy and bandwidth savings wrt state-of-the-art approaches when employed for sensing a spatially sparse field by means of a WSN.Comment: Submitted to EURASIP Journal on Advances in Signal Processin

Context Aware Computing for The Internet of Things: A Survey

As we are moving towards the Internet of Things (IoT), the number of sensors deployed around the world is growing at a rapid pace. Market research has shown a significant growth of sensor deployments over the past decade and has predicted a significant increment of the growth rate in the future. These sensors continuously generate enormous amounts of data. However, in order to add value to raw sensor data we need to understand it. Collection, modelling, reasoning, and distribution of context in relation to sensor data plays critical role in this challenge. Context-aware computing has proven to be successful in understanding sensor data. In this paper, we survey context awareness from an IoT perspective. We present the necessary background by introducing the IoT paradigm and context-aware fundamentals at the beginning. Then we provide an in-depth analysis of context life cycle. We evaluate a subset of projects (50) which represent the majority of research and commercial solutions proposed in the field of context-aware computing conducted over the last decade (2001-2011) based on our own taxonomy. Finally, based on our evaluation, we highlight the lessons to be learnt from the past and some possible directions for future research. The survey addresses a broad range of techniques, methods, models, functionalities, systems, applications, and middleware solutions related to context awareness and IoT. Our goal is not only to analyse, compare and consolidate past research work but also to appreciate their findings and discuss their applicability towards the IoT.Comment: IEEE Communications Surveys & Tutorials Journal, 201