Wireless Sensor Network (WSN) is composed of sink and sensors. Sensors transmit data to sink through wireless network after collecting data. Because multi-hop routing and forwarding may be required on WSN, sensors closer to sink will consume more energy than other nodes due to hop-by-hop forwarding. In this Thesis, we propose pipelined forwarding for cluster-based WSN to solve these problems. First, we divide a WSN into several clusters such that the distance between sensors and sink is reduced and packet transmission delay can be decreased. However, since reducing the distance can increase the number of clusters significantly, multiple mobile sinks are embedded in the system to increase overall throughput. Second, we change the direction of pipelined forwarding to avoid from running out of energy of some sensors. We derive mathematical equations to analyze and validate the proposed scheme. From the analytical results, we prove that the proposed scheme can decrease packet transmission delay. The results also show that system throughput can be improved by increasing the length of pipeline and the number of mobile sinks. Finally, we demonstrate that the proposed scheme can increase energy throughput more efficiently than conventional non-pipelined forwarding scheme.

The existence of a coordinate system can often improve the routing in a wireless sensor network. While most coordinate systems correspond to the geometrical or geographical coordinates, in recent years researchers had proposed the use of virtual coordinates. Virtual coordinates depend only on the topology of the network as defined by the connectivity of the nodes, without requiring geographical information. The work in this thesis extends the use of virtual coordinates to scenarios where the wireless sensor network has a mobile sink. One reason to use a mobile sink is to distribute the energy consumption more evenly among the sensor nodes and thus extend the life-time of the network. We developed two algorithms, MS-DVCR and CU-DVCR which perform routing towards a mobile sink using virtual coordinates. In contrast to the baseline virtual coordinate routing MS-DVCR limits routing updates triggered by the sink movement to a local area around the sink. In contrast, CU-DVCR limits the route updates to a circular area on the boundary of the local area. We describe the design justification and the implementation of these algorithms. Using a set of experimental studies, we show that MS-DVCR and CU-DVCR achieve a lower energy consumption compared to the baseline virtual coordinate routing without any noticeable impact on routing performance. In addition, CU-DVCR provides a lower energy consumption than MS-DVCR for the case of a fast moving sink.

In relation to the increasing interest in implementing smart cities, deployment of widespread wireless sensor networks (WSNs) has become a current hot topic. Among the application’s greatest challenges, there is still progress to be made concerning energy consumption and quality of service. Consequently, this project aims to explore a series of feasible solutions to improve the WSN energy efficiency for data aggregation by the WSN. This by strategically adjusting the position of the receiving base station and the packet rate of the WSN nodes. Additionally, the low-energy adaptive clustering hierarchy (LEACH) protocol is coupled with the WSN state of charge (SoC). For this thesis, a WSN was defined as a two dimensional area which contains sensor nodes and a mobile sink, i.e. a movable base station. Subsequent to the rigorous analyses of the WSN data clustering principles and system-wide dynamics, two different developing strategies, model-based and data-driven designs, were employed to develop two corresponding control approaches, model predictive control and reinforcement learning, on WSN energy management. To test their performance, a simulation environment was thus developed in Python, including the extended LEACH protocol. The amount of data transmitted by an energy unit is adopted as the index to estimate the control performance. The simulation results show that the model based controller was able to aggregate over 22% more bits than only using the LEACH protocol. Whilst the data driven controller had a worse performance than the LEACH network but showed potential for smaller sized WSNs containing a fewer amount of nodes. Nonetheless, the extension of the LEACH protocol did not give rise to obvious improvement on energy efficiency due to a wide range of differing results. / I samband med det ökande intresset för att implementera så kallade smart cities, har användningen av utbredda trådlösa sensor nätverk (WSN) blivit ett intresseområde. Bland applikationens största utmaningar, finns det fortfarande förbättringar med avseende på energiförbrukning och servicekvalité. Därmed så inriktar sig detta projekt på att utforska en mängd möjliga lösningar för att förbättra energieffektiviteten för dataaggregation inom WSN. Detta gjordes genom att strategiskt justera positionen av den mottagande basstationen samt paketfrekvensen för varje nod. Dessutom påbyggdes low-energy adaptive clustering hierarchy (LEACH) protokollet med WSN:ets laddningstillstånd. För detta examensarbete definierades ett WSN som ett två dimensionellt plan som innehåller sensor noder och en mobil basstation, d.v.s. en basstation som går att flytta. Efter rigorös analys av klustringsmetoder samt dynamiken av ett WSN, utvecklades två kontrollmetoder som bygger på olika kontrollstrategier. Dessa var en modelbaserad MPC kontroller och en datadriven reinforcement learning kontroller som implementerades för att förbättra energieffektiviteten i WSN. För att testa prestandan på dom två kontrollmetoderna, utvecklades en simulations platform baserat på Python, tillsamans med påbyggnaden av LEACH protokollet. Mängden data skickat per energienhet användes som index för att approximera kontrollprestandan. Simuleringsresultaten visar att den modellbaserade kontrollern kunde öka antalet skickade datapacket med 22% jämfört med när LEACH protokollet användes. Medans den datadrivna kontrollern hade en sämre prestanda jämfört med när enbart LEACH protokollet användes men den visade potential för WSN med en mindre storlek. Påbyggnaden av LEACH protokollet gav ingen tydlig ökning med avseende på energieffektiviteten p.g.a. en mängd avvikande resultat.

Made available in DSpace on 2016-06-02T19:06:10Z (GMT). No. of bitstreams: 1 5631.pdf: 1787133 bytes, checksum: c363525148fa6a5fe71608e7a8ffcf4c (MD5) Previous issue date: 2012-09-28 / Universidade Federal de Sao Carlos / The Wireless Sensor Networks (WSNs) and Mobile Wireless Sensor Networks (MWSNs) are being increasingly used by different applications, such as monitoring of animals, monitoring of vital signs, environmental monitoring, surveillance and protection of critical infrastructure, leaking gas, among many others. Some of these applications are already making use of mobile sensor nodes, such as underwater monitoring, precision agriculture, among many others. Due to restricted resources of sensor nodes, especially in relation to energy consumption, the development for solutions based on WSN and MWSN becomes limited. The use of mobile sensor nodes, which typically has more computational resources, power and communication, can help to reduce the energy consumption of fixed nodes, increasing the lifetime of the network. Networks that use mobile sensor nodes (fixed and mobile) with different types of hardware are called Wireless Sensor Networks Heterogeneous Mobile. This paper presents the RAHMoN (Routing Algorithm for Heterogeneous Mobile Networks), which makes use of data aggregation technique to reduce the traffic transmissions on the network, hierarchy of nodes (clustering), and use of sensor nodes (fixed and mobile) that collaborate to deliver data to a sink node at high speed. In RAHMoN, the network is configured using the techniques of inundation (flooding) and inundation reverse (reverse flooding) to collect the fixed position of sensor nodes and form an adjacency matrix. This matrix helps to build routes for data delivery to the sink and is stored in the mobile sensor nodes. Results show that our solution can guarantee a high packages delivery rate, low latency and reduce the delay of packet delivery. The solution was compared with the WHISPER, present in the literature and also focused on the delivery of data to sink node at high speed. / As Redes de sensores sem Fio (RSSFs) e Redes de Sensores Sem Fio Móveis (RSSFMs) estão sendo cada vez mais utilizadas por diferentes aplicações, tais como: monitoramento de animais, monitoramento de sinais vitais, monitoramento ambiental, vigilância e proteção de infraestruturas críticas, vazamento de gás, dentre inúmeras outras. Algumas dessas aplicações já fazem uso de nós sensores móveis. Devido aos recursos restritos dos nós sensores, principalmente em relação ao consumo energético, o desenvolvimento de soluções baseadas em RSSF e RSSFM torna-se limitado. O uso de nós sensores móveis, que tipicamente têm mais recursos computacionais, de energia e de comunicação, pode ajudar a reduzir o consumo de energia dos nós fixos, aumentando o tempo de vida da rede. Redes que utilizam nós sensores (fixos e móveis) com diferentes tipos de hardware são denominadas Redes de Sensores Sem Fio Móvel Heterogênea. Neste trabalho é apresentado o RAHMoN (Routing Algorithm for Heterogeneous Mobile Networks), que faz uso da técnica de agregação de dados para reduzir o tráfego de transmissões na rede, da hierarquização de nós (clustering), da utilização de nós sensores (fixos e móveis) e de um sink em alta velocidade. No RAHMoN, a rede é configurada utilizando flooding e flooding reverse para coletar a posição dos nós sensores fixos e formar uma matriz de adjacência. Essa matriz auxilia na construção de rotas durante a entrega dos dados para o sink e será armazenada nos nós sensores móveis. Resultados de avaliação mostram que a nossa solução consegue garantir uma alta taxa de entrega de pacotes, diminuir a latência e reduzir o atraso de entrega dos pacotes. A solução foi comparada com o WHISPER, presente na literatura e também voltado à entrega de dados para o nó sink em alta velocidade.

Made available in DSpace on 2015-04-11T14:02:47Z (GMT). No. of bitstreams: 1 Andre Ricardo Melo Araujo.pdf: 3722790 bytes, checksum: 1876d821e1e927795304f1c1ee7bbb67 (MD5) Previous issue date: 2013-03-01 / FAPEAM - Fundação de Amparo à Pesquisa do Estado do Amazonas / Wireless Sensor Network (WSN) is a special kind of ad hoc networks composed of devices capable of processing, storing, sensing the environment, and transmitting data via wireless communication interface. The sensor nodes have several limitations, among them the capacity of energy because to the reduced size. For this reason, many searches have been done with a view to improving the energy consumption of sensor nodes. This work aims to address the Problem of Coverage, Clustering and Routing with Mobile Sink (PCAR-SM, in portuguese Problema de Cobertura, Agrupamento e Roteamento com Sorvedouro Móvel) in WSN with mobile sink consisting of: given a set of sensor nodes and a monitoring area, develop algorithms to find the best subset of sensor nodes to cover the monitoring area, group them in a smaller number of clusters and find the shortest route to mobile sink navigate. The PCAR-SM is a strategy used to reduce the energy consumption of sensor nodes, data collisions, interference and redundant data in networks with high concentration of sensor nodes per area. The purpose of this paper is to solve each problem separately and together, in order to evaluate the impact of each problem on the other. The Coverage Problem has been solved with two metaheuristics: an Genetic Algorithm (GA) and a Greedy Randomized Adaptive Search Procedure (GRASP) algorithm. In the latter we used two representations of solution: (a) representation by sensor, where each element of the solution vector represents a sensor node that must be switched on or off; (b) representation by demand, where each element of the solution vector represents a demand point will indicate which sensor node cover it. The AG uses only the representation by demand. The computational results for Coverage Problem used the benchmark of Beasley s OR Library and it was possible seen that the GRASP with representation by demand achieved better results than the GA and the GRASP with representation by sensor when the optimization criterion is to minimize the total cost of each sensor node used in the solution. For Clustering Problem was created approach of virtual grids. In this approach, we divide the area into grids and clusters are formed by a set of adjacent grids (maximum 5 grids in group) forming a cross schematic. The aim of the problem is to minimize the number of clusters in the area. With this approach, we can model the Clustering Problem as a Set Cover Problem (SCP) without overlapping (an element does not belong to more than one set), which was treated by a greedy heuristic called Greedy Clustering Algorithm (GCA). The virtual grids proved to be a good solution because it is simple to identify a node which grid it belongs. Its simplicity also makes it a appropriate method for a distributed version. The Routing Problem of sink was modeled as the Travelling Salesman Problem (TSP), where the mobile sink part of a corner of the monitoring area, runs through the area visiting all clusters and returns to the starting point. For this, we propose two greedy approaches based on nearest neighbor, the Routing Greedy Algorithm - Center (RGA-C) and Routing Greedy Algorithm - Border (RGA-B). The route of the sink was also solved by a heuristic based on algorithm Centralized Spatial Partitioning (CSP). In CSP approach, the route is fixed and reminds the movement of a snake. The results show that fixed route produces a path with smaller size compared to the greedy heuristic for TSP. We analyze also the PCAR-SM, creating heuristic strategies. The union of the Clustering Problem and Routing Problem proved more beneficial in relation to the size of the sink s route. The union of Coverage Problem and Clustering Problem only proved beneficial when the communication radius was about 3,9 times greater than the sensing radius. Our results show that solve problems together allows some changes in the algorithms will lead to better results. / As Redes de Sensores Sem Fio (RSSFs) são um tipo especial de redes ad hoc constituídas por dispositivos capazes de processar, armazenar, sensoriar o ambiente e transmitir dados via interface de comunicação sem fio, denominados nós sensores. Os nós sensores possuem várias limitações, dentre elas, a capacidade de energia devido ao tamanho reduzido. Por isto, muitas pesquisas foram feitas tendo em vista a melhoria no consumo de energia dos nós sensores. Este trabalho tem como objetivo tratar o Problema de Cobertura, Agrupamento e Roteamento com Sorvedouro Móvel (PCAR-SM) em RSSF com nó sorvedouro móvel, que consiste em: dado um conjunto de nós sensores e uma área de monitoramento, desenvolver algoritmos para encontrar o melhor subconjunto de nós sensores que cubra a área de monitoramento, juntá-los no menor número de grupos possíveis e encontrar a menor rota para um nó sorvedouro móvel percorrer. O PCAR-SM é uma estratégia utilizada para diminuir o consumo de energia dos nós sensores, a colisão de dados, as interferências e os dados redundantes em redes com alta concentração de nós sensores por área. A proposta deste trabalho é resolver cada problema separadamente e em conjunto, de modo a avaliar o impacto de cada problema na solução do outro. O Problema de Cobertura foi resolvido com duas metaheurísticas: um Algoritmo Genético (AG) e um algoritmo Greedy Randomized Adaptive Search Procedure (GRASP). Neste último foram utilizadas duas representações de solução: (a) representação por sensor, onde cada elemento do vetor de solução representa um nó sensor que estará ligado ou desligado; (b) representação por demanda, onde cada elemento do vetor de solução representa um ponto de demanda no qual indicará qual o nó sensor o cobre. O AG utiliza apenas a representação por demanda. Os resultados computacionais para o Problema de Cobertura utilizaram o benchmark da Beasley s OR Library e foi possível constatar que o GRASP com representação por demanda obteve melhores resultados que o AG e o GRASP com representação por sensor quando o critério de otimização é minimizar a soma total dos custos de cada nó sensor utilizado na solução. Para o Problema de Agrupamento foi criada uma abordagem de grades virtuais. Nesta abordagem dividimos a área em grades e os grupos são formados por um conjunto de grades adjacentes (no máximo 5 grades) formando um esquema de cruz. O objetivo do problema é minimizar o número de grupos na área. A partir desta abordagem, pode-se modelar o Problema de Agrupamento como um Problema de Cobertura de Conjuntos (PCC) sem sobreposição (um elemento não pertence a mais de um conjunto), que foi tratada por uma heurística gulosa denominada Greedy Clustering Algorithm (GCA). Os grades virtuais provou ser uma boa solução por ser simples para um nó identificar a qual grade ele pertence. Sua simplicidade ainda o torna uma método adequado para uma versão distribuída. O Problema de Roteamento do nó sorvedouro foi modelado como o Problema do Caixeiro Viajante (PCV), onde o nó sorvedouro móvel parte de um canto da área de monitoramento, percorre a área visitando todos os grupos e retorna ao ponto inicial. Para isto, propomos duas abordagens gulosas baseadas no vizinho mais próximo, o Routing Greedy Algorithm - Center (RGA-C) e o Routing Greedy Algorithm - Border (RGA-B). A rota do nó sorvedouro também foi resolvida por uma heurística baseada no algoritmo Centralized Spatial Partitioning (CSP). Na abordagem CSP, a rota é fixa e lembra o movimento de uma cobra. Os resultados mostram que a rota fixa gera um percurso com tamanho menor em comparação com as heurísticas gulosas para o PCV. Analisamos, ainda, o PCAR-SM, criando estratégias heurísticas. Aunião dos Problema de Agrupamento e Roteamento, provou ser mais benéfica em relação ao tamanho da rota do nó sorvedouro, já a união do Problema de Cobertura com o Problema de Agrupamento só mostrou ser benéfica quando o raio de comunicação era aproximadamente 3, 9 vezes maior que o raio de sensoriamento. Nossos resultados, mostram que resolver os problemas em conjunto permite que algumas mudanças nos algoritmos levem a melhores resultados.

Sensor nodes in a wireless sensor network (WSN) have a small, non-rechargeable power supply. Each message transmission or reception depletes a sensor node’s energy. Many WSN applications are ad-hoc deployments where a sensor node is only aware of its immediate neighbours. The lack of a predefined route path and the need to restrict the amount of communication that occurs within the application area impose constraints on WSNs not prevalent in other types of networks. An area of active research has been how to notify the central sink (or monitoring hub) about an event in real-time by utilising the minimum number of messages to route a message from a source node to the destination sink node. In this thesis, strategies to limit communication within a WSN application area, while ensuring that events are reported on and responded to in real-time, is presented. A solution based on modelling a WSN as a small world network and then transmitting an initialisation message (IM) on network start-up to create multiple route paths from any sensor node to one or more sinks is proposed. The reason for modelling a WSN as a small world network is to reduce the number of nodes required to re-transmit a message from a source sensor node to a sink. The purpose of sending an IM at network start-up is to ensure that communication within the WSN is minimised. When routing a message to a static sink, the nodes closest to the static sink receive a disproportionate number of messages, resulting in their energy being consumed earlier. The use of mobile sinks has been proposed but to our knowledge no studies have been undertaken on the paths these mobile sinks should follow. An algorithm to determine the optimum path for mobile sinks to follow in a WSN application area is described. The purpose of an optimum path is to allow more equitable usage of all nodes to transfer an event message to a mobile sink. The idea of using multiple static sinks placed at specific points in the small world model is broadened to include using multiple mobile sinks called actors to move within a WSN application area and respond to an event in real-time. Current coordination solutions to determine which actor(s) must respond to the event result in excessive message communication and limit the real-time response to an event. An info gap decision theory (IGDT) model to coordinate which actor or set of actors should respond to the event is described. A comparison of the small world routing (SWR) model against routing using flooding and gossiping shows that the SWR model significantly reduces the number of messages transmitted within the network. An analysis of the number of IMs transmitted and received at individual node level shows that prudent selection of the hop count (number of additional nodes required to route a message to sink) to a sink node will result in a reduced number of messages transmitted and received per node within the network. The use of the IGDT model results in a robust decision on the actor(s) chosen to respond to an event even when uncertainty about the location and available energy of other actor(s) exists. / Thesis (PhD(Eng))--University of Pretoria, 2012. / Electrical, Electronic and Computer Engineering / unrestricted