On Modeling Geometric Joint Sink Mobility with Delay-Tolerant Cluster-less Wireless Sensor Networks

Moving Sink (MS) in Wireless Sensor Networks (WSNs) has appeared as a blessing because it collects data directly from the nodes where the concept of relay nodes is becomes obsolete. There are, however, a few challenges to be taken care of, like data delay tolerance and trajectory of MS which is NP-hard. In our proposed scheme, we divide the square field in small squares. Middle point of the partitioned area is the sojourn location of the sink, and nodes around MS are in its transmission range, which send directly the sensed data in a delay-tolerant fashion. Two sinks are moving simultaneously; one inside and having four sojourn locations and other in outer trajectory having twelve sojourn locations. Introduction of the joint mobility enhances network life and ultimately throughput. As the MS comes under the NP-hard problem, we convert it into a geometric problem and define it as, Geometric Sink Movement (GSM). A set of linear programming equations has also been given in support of GSM which prolongs network life time

Cooperative Hyper-Scheduling based improving Energy Aware Life Time Maximization in Wireless Body Sensor Network Using Topology Driven Clustering Approach

The Wireless Body Sensor Network (WBSN) is an incredible developing data transmission network for modern day communication especially in Biosensor device networks. Due to energy consumption in biomedical data transfer have impacts of sink nodes get loss information on each duty cycle because of Traffic interruptions. The reason behind the popularity of WBSN characteristics contains number of sensor nodes to transmit data in various dense regions. Due to increasing more traffic, delay, bandwidth consumption, the energy losses be occurred to reduce the lifetime of the WBSN transmission. So, the sensor nodes are having limited energy or power, by listening to the incoming signals, it loses certain amount of energy to make data losses because of improper route selection. To improve the energy aware lifetime maximization through Traffic Aware Routing (TAR) based on scheduling. Because the performance of scheduling is greatly depending on the energy of nodes and lifetime of the network. To resolve this problem, we propose a Cooperative Hyper-scheduling (CHS) based improving energy aware life time maximization (EALTM) in Wireless Body sensor network using Topology Driven Clustering Approach (TDCA).Initially the method maintains the traces of transmission performed by different Bio-sensor nodes in different duty cycle. The method considers the energy of different nodes and history of earlier transmission from the Route Table (RT) whether the transmission behind the Sink node. Based on the RT information route discovery was performed using Traffic Aware Neighbors Discovery (TAND) to estimate Data Transmission Support Measure (DTSM) on each Bio-sensor node which its covers sink node. These nodes are grouped into topology driven clustering approach for route optimization. Then the priority is allocated based on The Max-Min DTSM, the Cooperative Hyper-scheduling was implemented to schedule the transmission with support of DTSM to reduce the energy losses in WBSN. This improves the energy level to maximization the life time of data transmission in WBSN than other methods to produce best performance in throughput energy level

Thirty Years of Machine Learning: The Road to Pareto-Optimal Wireless Networks

Future wireless networks have a substantial potential in terms of supporting a broad range of complex compelling applications both in military and civilian fields, where the users are able to enjoy high-rate, low-latency, low-cost and reliable information services. Achieving this ambitious goal requires new radio techniques for adaptive learning and intelligent decision making because of the complex heterogeneous nature of the network structures and wireless services. Machine learning (ML) algorithms have great success in supporting big data analytics, efficient parameter estimation and interactive decision making. Hence, in this article, we review the thirty-year history of ML by elaborating on supervised learning, unsupervised learning, reinforcement learning and deep learning. Furthermore, we investigate their employment in the compelling applications of wireless networks, including heterogeneous networks (HetNets), cognitive radios (CR), Internet of things (IoT), machine to machine networks (M2M), and so on. This article aims for assisting the readers in clarifying the motivation and methodology of the various ML algorithms, so as to invoke them for hitherto unexplored services as well as scenarios of future wireless networks.Comment: 46 pages, 22 fig

Energy efficient routing in wireless sensor network based on mobile sink guided by stochastic hill climbing

In Wireless Sensor Networks (WSNs), the reduction of energy consumption in the batteries of a sensor node is an important task. Sensor nodes of WSNs perform three significant functions such as data sensing, data transmitting and data relaying. Routing technique is one of the methods to enhance the sensor nodes battery lifetime. Energy optimization is done by using one of the heuristic routing methods for sensing and transmitting the data. To enhance the energy optimization mainly concentrated on data relaying. In this work stochastic hill climbing is adapted. The proposed solution for data relaying utilizes geographical routing and mobile sink technique. The sink collects the data from cluster heads and movement of the sink is routed by stochastic hill climbing. Network simulator 2 is used for experimentation purpose. This work also compares with the existing routing protocols like Energy-efficient Low Duty Cycle (ELDC), Threshold sensitive Energy Efficient sensor Network (TEEN) and Adaptive clustering protocol. The proposed work shows promising results with respect to lifetime, average energy of nodes and packet delivery ratio

Design and stochastic analysis of emerging large-scale wireless-powered sensor networks

Undeniably, the progress in wireless networks during the last two decades is extraordinary. However, the ever-increasing upward trend in the numbers of wireless devices that will overwhelm every field of our everyday life, e.g., building automation, traffic management, health-care, etc., will introduce several issues in terms of communication and energy provision that need to be handled in advance. Regarding the communication issues, it is imperative to ensure the correct operation of the vast collection of nodes, especially for life-critical applications. Two well-known metrics that can characterize sufficiently the network reliability are the coverage and the connectivity probability that are derived by taking into account the network topology, the channel conditions between every transmitter-receiver pair, and the interference from other nodes. Nevertheless, considering all those factors is not straightforward. Lately, stochastic geometry has come into prominence, which is a mathematical tool to study the average network performance over many spatial realizations, while considering all aforementioned factors. Moreover, the other crucial issue for the large-scale dense network deployments of the future is their energy supply. Traditional battery charging or swapping for the wireless devices is both inconvenient and harms the environment, especially if we take into account the enormous numbers of nodes. Therefore, novel solutions have to be found using renewable energy sources to zero down the significant electricity consumption. Wireless energy harvesting is a convenient and environmentally-friendly approach to prolong the lifetime of networks by harvesting the energy from radio-frequency (RF) signals and converting it to direct current electricity through specialized hardware. The RF energy could be harvested from signals generated in the same or other networks. However, if the amount of harvested energy is not sufficient, solar-powered dedicated transmitters could be employed. In this way, we can achieve a favorable outcome by having both a zero-energy network operation and convenience in the charging of the wireless devices. Still, extensive investigation should be done in order to ensure that the communication performance is not affected. To that end, in this thesis, we study the communication performance in large-scale networks using tools from stochastic geometry. The networks that we study comprise wireless devices that are able to harvest the energy of RF signals. In the first part of the thesis, we present the effects of wireless energy harvesting from the transmissions of the cooperative network on the coverage probability and the network lifetime. In the second part of the thesis, we first employ batteryless nodes that are powered by dedicated RF energy transmitters to study the connectivity probability. Then, we assume that the dedicated transmitters are powered by solar energy to study the connectivity in a clustered network and investigate, for the first time, the reliability of zero-energy networks. Finally, we conclude the thesis by providing insightful research challenges for future works.Innegablemente, el progreso en las redes inalámbricas durante las últimas dos décadas es extraordinario. Sin embargo, la creciente tendencia al alza en el número de dispositivos inalámbricos que abarcarán todos los ámbitos de nuestra vida cotidiana, como la automatización de edificios, la gestión del tráfico, la atención sanitaria, etc., introducirá varias cuestiones en términos de comunicación y suministro de energía que se debe tener en cuenta con antelación. Respecto a los problemas de comunicación, es imprescindible asegurar el correcto funcionamiento de la vasta colección de nodos, especialmente para las aplicaciones vitales. Dos métricas bien conocidas que pueden caracterizar suficientemente la fiabilidad de la red son la probabilidad de cobertura y la de conectividad, que se derivan teniendo en cuenta la topología de la red, las condiciones del canal entre cada par transmisor-receptor y la interferencia de otros nodos. Sin embargo, considerar todos esos factores no es sencillo. Últimamente, la geometría estocástica ha llegado a la prominencia como un metodo de análisis, que es una herramienta matemática para estudiar el rendimiento promedio de la red sobre muchas realizaciones espaciales, teniendo en cuenta todos los factores mencionados. Además, la otra cuestión crucial para los despliegues de alta densidad de las redes futuras es su suministro de energía. La carga o el intercambio de baterías para los dispositivos inalámbricos es inconveniente y daña el medio ambiente, especialmente si tenemos en cuenta el enorme número de nodos utilizados. Por lo tanto, se deben encontrar nuevas soluciones utilizando fuentes de energía renovables para reducir el consumo de electricidad. La recolección de energía inalámbrica es un método conveniente y respetuoso con el medio ambiente para prolongar la vida útil de las redes recolectando la energía de las señales de radiofrecuencia (RF) y convirtiéndola en electricidad de corriente continua mediante un hardware especializado. La energía de RF podría ser obtenida a partir de señales generadas en la misma o en otras redes. Sin embargo, si la cantidad de energía obtenida no es suficiente, podrían emplearse transmisores de energía inalambricos que la obtuvieran mediante paneles fotovoltaicos. De esta manera, podemos lograr un resultado favorable teniendo tanto una operación de red de energía cero como una conveniencia en la carga de los dispositivos inalámbricos. Por lo tanto, una investigación exhaustiva debe hacerse con el fin de garantizar que el rendimiento de la comunicación no se ve afectada. En esta tesis se estudia el rendimiento de la comunicación en redes de gran escala utilizando técnicas de geometría estocástica. Las redes que se estudian comprenden dispositivos inalámbricos capaces de recoger la energía de las señales RF. En la primera parte de la tesis, presentamos los efectos de la recolección de energía inalámbrica de las transmisiones de la red cooperativa sobre la probabilidad de cobertura y la vida útil de la red. En la segunda parte de la tesis, primero empleamos nodos sin baterías que son alimentados por transmisores de energía de RF para estudiar la probabilidad de conectividad. A continuación, asumimos que los transmisores dedicados son alimentados por energía solar para estudiar la conectividad en una red agrupada (clustered network) e investigar, por primera vez, la fiabilidad de las redes de energía cero. Finalmente, concluimos la tesis aportando nuevas lineas de investigación para trabajos futuro

Design and stochastic analysis of emerging large-scale wireless-powered sensor networks

Premi Extraordinari de Doctorat, promoció 2016-2017. Àmbit d’Enginyeria de les TICUndeniably, the progress in wireless networks during the last two decades is extraordinary. However, the ever-increasing upward trend in the numbers of wireless devices that will overwhelm every field of our everyday life, e.g., building automation, traffic management, health-care, etc., will introduce several issues in terms of communication and energy provision that need to be handled in advance. Regarding the communication issues, it is imperative to ensure the correct operation of the vast collection of nodes, especially for life-critical applications. Two well-known metrics that can characterize sufficiently the network reliability are the coverage and the connectivity probability that are derived by taking into account the network topology, the channel conditions between every transmitter-receiver pair, and the interference from other nodes. Nevertheless, considering all those factors is not straightforward. Lately, stochastic geometry has come into prominence, which is a mathematical tool to study the average network performance over many spatial realizations, while considering all aforementioned factors. Moreover, the other crucial issue for the large-scale dense network deployments of the future is their energy supply. Traditional battery charging or swapping for the wireless devices is both inconvenient and harms the environment, especially if we take into account the enormous numbers of nodes. Therefore, novel solutions have to be found using renewable energy sources to zero down the significant electricity consumption. Wireless energy harvesting is a convenient and environmentally-friendly approach to prolong the lifetime of networks by harvesting the energy from radio-frequency (RF) signals and converting it to direct current electricity through specialized hardware. The RF energy could be harvested from signals generated in the same or other networks. However, if the amount of harvested energy is not sufficient, solar-powered dedicated transmitters could be employed. In this way, we can achieve a favorable outcome by having both a zero-energy network operation and convenience in the charging of the wireless devices. Still, extensive investigation should be done in order to ensure that the communication performance is not affected. To that end, in this thesis, we study the communication performance in large-scale networks using tools from stochastic geometry. The networks that we study comprise wireless devices that are able to harvest the energy of RF signals. In the first part of the thesis, we present the effects of wireless energy harvesting from the transmissions of the cooperative network on the coverage probability and the network lifetime. In the second part of the thesis, we first employ batteryless nodes that are powered by dedicated RF energy transmitters to study the connectivity probability. Then, we assume that the dedicated transmitters are powered by solar energy to study the connectivity in a clustered network and investigate, for the first time, the reliability of zero-energy networks. Finally, we conclude the thesis by providing insightful research challenges for future works.Innegablemente, el progreso en las redes inalámbricas durante las últimas dos décadas es extraordinario. Sin embargo, la creciente tendencia al alza en el número de dispositivos inalámbricos que abarcarán todos los ámbitos de nuestra vida cotidiana, como la automatización de edificios, la gestión del tráfico, la atención sanitaria, etc., introducirá varias cuestiones en términos de comunicación y suministro de energía que se debe tener en cuenta con antelación. Respecto a los problemas de comunicación, es imprescindible asegurar el correcto funcionamiento de la vasta colección de nodos, especialmente para las aplicaciones vitales. Dos métricas bien conocidas que pueden caracterizar suficientemente la fiabilidad de la red son la probabilidad de cobertura y la de conectividad, que se derivan teniendo en cuenta la topología de la red, las condiciones del canal entre cada par transmisor-receptor y la interferencia de otros nodos. Sin embargo, considerar todos esos factores no es sencillo. Últimamente, la geometría estocástica ha llegado a la prominencia como un metodo de análisis, que es una herramienta matemática para estudiar el rendimiento promedio de la red sobre muchas realizaciones espaciales, teniendo en cuenta todos los factores mencionados. Además, la otra cuestión crucial para los despliegues de alta densidad de las redes futuras es su suministro de energía. La carga o el intercambio de baterías para los dispositivos inalámbricos es inconveniente y daña el medio ambiente, especialmente si tenemos en cuenta el enorme número de nodos utilizados. Por lo tanto, se deben encontrar nuevas soluciones utilizando fuentes de energía renovables para reducir el consumo de electricidad. La recolección de energía inalámbrica es un método conveniente y respetuoso con el medio ambiente para prolongar la vida útil de las redes recolectando la energía de las señales de radiofrecuencia (RF) y convirtiéndola en electricidad de corriente continua mediante un hardware especializado. La energía de RF podría ser obtenida a partir de señales generadas en la misma o en otras redes. Sin embargo, si la cantidad de energía obtenida no es suficiente, podrían emplearse transmisores de energía inalambricos que la obtuvieran mediante paneles fotovoltaicos. De esta manera, podemos lograr un resultado favorable teniendo tanto una operación de red de energía cero como una conveniencia en la carga de los dispositivos inalámbricos. Por lo tanto, una investigación exhaustiva debe hacerse con el fin de garantizar que el rendimiento de la comunicación no se ve afectada. En esta tesis se estudia el rendimiento de la comunicación en redes de gran escala utilizando técnicas de geometría estocástica. Las redes que se estudian comprenden dispositivos inalámbricos capaces de recoger la energía de las señales RF. En la primera parte de la tesis, presentamos los efectos de la recolección de energía inalámbrica de las transmisiones de la red cooperativa sobre la probabilidad de cobertura y la vida útil de la red. En la segunda parte de la tesis, primero empleamos nodos sin baterías que son alimentados por transmisores de energía de RF para estudiar la probabilidad de conectividad. A continuación, asumimos que los transmisores dedicados son alimentados por energía solar para estudiar la conectividad en una red agrupada (clustered network) e investigar, por primera vez, la fiabilidad de las redes de energía cero. Finalmente, concluimos la tesis aportando nuevas lineas de investigación para trabajos futurosAward-winningPostprint (published version

Topology design and cross-layer optimization for wireless body sensor networks

Wireless Body Sensor Networks play a crucial role in digital health care nowadays. Due to the size limitation on the sensor nodes and the life critical characteristics of the signals, there are stringent requirements on network’s reliability and energy efficiency. In this article, we propose a mathematical optimization problem that jointly considers network topology design and cross-layer optimization in WBSNs. We introduce multilevel primal and dual decomposition methods and manage to solve the proposed non-convex mixed-integer optimization problem. A solution with fast convergence rate based on binary search is provided. Simulation results have been supplemented to show that our proposed method yields much better performance than existing solutions

Spectral efficiency optimization with distributed beamforming in UWB based implant body area networks

Copyright © 2014 ICST. In this paper, a distributed beamforming problem is investigated based on spectral efficiency (SE) optimization for ultra-wideband (UWB) based implant body area networks (IBANs). We consider a relay network consisting of one implant source, several wearable relays, and one body network coordinator under the assumption that the individual relay power is constrained due to the Federal Communications Commission (FCC) regulations for UWB signals. Taking into account realistic wireless channels and relay locations, the SE optimization problem is mathematically formulated and solved by using convex optimization. Simulation results show that the proposed beamforming scheme is superior to other transmission schemes. Moreover, our numerical examples reveal that the relay location has a significant impact on the beamforming performance and the proposed beamforming scheme provides an efficient way to prolong the lifetime of the implant node

Energy Harvesting Cooperative Networks: Is the Max-Min Criterion Still Diversity-Optimal?

This paper considers a general energy harvesting cooperative network with M source-destination (SD) pairs and one relay, where the relay schedules only m user pairs for transmissions. For the special case of m = 1, the addressed scheduling problem is equivalent to relay selection for the scenario with one SD pair and M relays. In conventional cooperative networks, the max-min selection criterion has been recognized as a diversity-optimal strategy for relay selection and user scheduling. The main contribution of this paper is to show that the use of the max-min criterion will result in loss of diversity gains in energy harvesting cooperative networks. Particularly when only a single user is scheduled, analytical results are developed to demonstrate that the diversity gain achieved by the max-min criterion is only (M+1)/2, much less than the maximal diversity gain M. The max-min criterion suffers this diversity loss because it does not reflect the fact that the source-relay channels are more important than the relay-destination channels in energy harvesting networks. Motivated by this fact, a few user scheduling approaches tailored to energy harvesting networks are developed and their performance is analyzed. Simulation results are provided to demonstrate the accuracy of the developed analytical results and facilitate the performance comparison.Comment: 30 pages, 7 figure