388 research outputs found

    Analytical Hierarchy Process Multi-Metric Objective Function for RPL

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    IPv6 Routing Protocol for Low Power and Lossy Networks (RPL), is based on building an acyclic graph where an Objective Function (OF) is responsible for selecting the preferred parent during Destination Oriented Directed Acyclic Graph (DODAG) construction. In this paper, we propose a new multi-metric OF based on Analytical Hierarchy Processes decision masking algorithm. AHP-OF, combines a set of routing metrics aiming to provide the best routing decision for RPL to satisfy the different application requirements for LLN s such as reliable applications, real time applications and highly available applications. Here we focus on the theoretical aspect of AHP-OF, and finally we evaluate the performance of AHP-OF compared to other OFs using Cooja simulator

    A Cloud Based Disaster Management System

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    The combination of wireless sensor networks (WSNs) and 3D virtual environments opens a new paradigm for their use in natural disaster management applications. It is important to have a realistic virtual environment based on datasets received from WSNs to prepare a backup rescue scenario with an acceptable response time. This paper describes a complete cloud-based system that collects data from wireless sensor nodes deployed in real environments and then builds a 3D environment in near real-time to reflect the incident detected by sensors (fire, gas leaking, etc.). The system’s purpose is to be used as a training environment for a rescue team to develop various rescue plans before they are applied in real emergency situations. The proposed cloud architecture combines 3D data streaming and sensor data collection to build an efficient network infrastructure that meets the strict network latency requirements for 3D mobile disaster applications. As compared to other existing systems, the proposed system is truly complete. First, it collects data from sensor nodes and then transfers it using an enhanced Routing Protocol for Low-Power and Lossy Networks (RLP). A 3D modular visualizer with a dynamic game engine was also developed in the cloud for near-real time 3D rendering. This is an advantage for highly-complex rendering algorithms and less powerful devices. An Extensible Markup Language (XML) atomic action concept was used to inject 3D scene modifications into the game engine without stopping or restarting the engine. Finally, a multi-objective multiple traveling salesman problem (AHP-MTSP) algorithm is proposed to generate an efficient rescue plan by assigning robots and multiple unmanned aerial vehicles to disaster target locations, while minimizing a set of predefined objectives that depend on the situation. The results demonstrate that immediate feedback obtained from the reconstructed 3D environment can help to investigate what–if scenarios, allowing for the preparation of effective rescue plans with an appropriate management effort.info:eu-repo/semantics/publishedVersio

    Optimization Based Hybrid Congestion Alleviation for 6LoWPAN Networks

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    The IPv6 over Low-Power Wireless Personal Area Network (6LoWPAN) protocol stack is a key part of the Internet of Things (IoT) where the 6LoWPAN motes will account for the majority of the IoT ‘things’. In 6LoWPAN networks, heavy network traffic causes congestion which significantly effects the network performance and the quality of service (QoS) metrics. Generally, two main strategies are used to control and alleviate congestion in 6LoWPAN networks: resource control and traffic control. All the existing work of congestion control in 6LoWPAN networks use one of these. In this paper, we propose a novel congestion control algorithm called optimization based hybrid congestion alleviation (OHCA) which combines both strategies into a hybrid solution. OHCA utilizes the positive aspects of each strategy and efficiently uses the network resources. The proposed algorithm uses a multi-attribute optimization methodology called grey relational analysis for resource control by combining three routing metrics (buffer occupancy, expected transmission count and queuing delay) and forwarding packets through non-congested parents. Also, OHCA uses optimization theory and Network Utility Maximization (NUM) framework to achieve traffic control when the non-congested parent is not available where the optimal nodes’ sending rate are computed by using Lagrange multipliers and KKT conditions. The proposed algorithm is aware of node priorities and application priorities to support the IoT application requirements where the applications’ sending rate allocation is modelled as a constrained optimization problem. OHCA has been tested and evaluated through simulation by using Contiki OS and compared with comparative algorithms. Simulation results show that OHCA improves performance in the presence of congestion by an overall average of 28.36%, 28.02%, 48.07%, 31.97% and 90.35% in terms of throughput, weighted fairness index, end-to-end delay, energy consumption and buffer dropped packets as compared to DCCC6 and QU-RPL

    Performance analysis of Routing Protocol for Low power and Lossy Networks (RPL) in large scale networks

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    With growing needs to better understand our environments, the Internet-of-Things (IoT) is gaining importance among information and communication technologies. IoT will enable billions of intelligent devices and networks, such as wireless sensor networks (WSNs), to be connected and integrated with computer networks. In order to support large scale networks, IETF has defined the Routing Protocol for Low power and Lossy Networks (RPL) to facilitate the multi-hop connectivity. In this paper, we provide an in-depth review of current research activities. Specifically, the large scale simulation development and performance evaluation under various objective functions and routing metrics are pioneering works in RPL study. The results are expected to serve as a reference for evaluating the effectiveness of routing solutions in large scale IoT use cases

    Congestion Control for 6LoWPAN Wireless Sensor Networks: Toward the Internet of Things

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    The Internet of Things (IoT) is the next big challenge for the research community. The IPv6 over low power wireless personal area network (6LoWPAN) protocol stack is considered a key part of the IoT. Due to power, bandwidth, memory and processing resources limitation, heavy network traffic in 6LoWPAN networks causes congestion which significantly degrades network performance and impacts on the quality of service (QoS) aspects. This thesis addresses the congestion control issue in 6LoWPAN networks. In addition, the related literature is examined to define the set of current issues and to define the set of objectives based upon this. An analytical model of congestion for 6LoWPAN networks is proposed using Markov chain and queuing theory. The derived model calculates the buffer loss probability and the number of received packets at the final destination in the presence of congestion. Simulation results show that the analytical modelling of congestion has a good agreement with simulation. Next, the impact of congestion on 6LoWPAN networks is explored through simulations and real experiments where an extensive analysis is carried out with different scenarios and parameters. Analysis results show that when congestion occurs, the majority of packets are lost due to buffer overflow as compared to channel loss. Therefore, it is important to consider buffer occupancy in protocol design to improve network performance. Based on the analysis conclusion, a new IPv6 Routing Protocol for Low-Power and Lossy Network (RPL) routing metric called Buffer Occupancy is proposed that reduces the number of lost packets due to buffer overflow when congestion occurs. Also, a new RPL objective function called Congestion-Aware Objective Function (CA-OF) is presented. The proposed objective function works efficiently and improves the network performance by selecting less congested paths. However, sometimes the non-congested paths are not available and adapting the sending rates of source nodes is important to mitigate the congestion. Accordingly, the congestion problem is formulated as a non-cooperative game framework where the nodes (players) behave uncooperatively and demand high data rate in a selfish way. Based on this framework, a novel and simple congestion control mechanism called Game Theory based Congestion Control Framework (GTCCF) is proposed to adapt the sending rates of nodes and therefore, congestion can be solved. The existence and uniqueness of Nash equilibrium in the designed game is proved and the optimal game solution is computed by using Lagrange multipliers and Karush-Kuhn-Tucker (KKT) conditions. GTCCF is aware of node priorities and application priorities to support the IoT application requirements. On the other hand, combining and utilizing the resource control strategy (i.e. finding non-congested paths) and the traffic control strategy (i.e. adapting sending rate of nodes) into a hybrid scheme is important to efficiently utilize the network resources. Based on this, a novel congestion control algorithm called Optimization based Hybrid Congestion Alleviation (OHCA) is proposed. The proposed algorithm combines traffic control and resource control strategies into a hybrid solution by using the Network Utility Maximization (NUM) framework and a multi-attribute optimization methodology respectively. Also, the proposed algorithm is aware of node priorities and application priorities to support the IoT application requirements

    A study into prolonging Wireless Sensor Network lifetime during disaster scenarios

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    A Wireless Sensor Network (WSN) has wide potential for many applications. It can be employed for normal monitoring applications, for example, the monitoring of environmental conditions such as temperature, humidity, light intensity and pressure. A WSN is deployed in an area to sense these environmental conditions and send information about them to a sink. In certain locations, disasters such as forest fires, floods, volcanic eruptions and earth-quakes can happen in the monitoring area. During the disaster, the events being monitored have the potential to destroy the sensing devices; for example, they can be sunk in a flood, burnt in a fire, damaged in harmful chemicals, and burnt in volcano lava etc. There is an opportunity to exploit the energy of these nodes before they are totally destroyed to save the energy of the other nodes in the safe area. This can prolong WSN lifetime during the critical phase. In order to investigate this idea, this research proposes a new routing protocol called Maximise Unsafe Path (MUP) routing using Ipv6 over Low power Wireless Personal Area Networks (6LoWPAN). The routing protocol aims to exploit the energy of the nodes that are going to be destroyed soon due to the environment, by concentrating packets through these nodes. MUP adapts with the environmental conditions. This is achieved by classifying four different levels of threat based on the sensor reading information and neighbour node condition, and represents this as the node health status, which is included as one parameter in the routing decision. High priority is given to a node in an unsafe condition compared to another node in a safer condition. MUP does not allow packet routing through a node that is almost failed in order to avoid packet loss when the node fails. To avoid the energy wastage caused by selecting a route that requires a higher energy cost to deliver a packet to the sink, MUP always forwards packets through a node that has the minimum total path cost. MUP is designed as an extension of RPL, an Internet Engineering Task Force (IETF) standard routing protocol in a WSN, and is implemented in the Contiki Operating System (OS). The performance of MUP is evaluated using simulations and test-bed experiments. The results demonstrate that MUP provides a longer network lifetime during a critical phase of typically about 20\% when compared to RPL, but with a trade-off lower packet delivery ratio and end-to-end delay performances. This network lifetime improvement is crucial for the WSN to operate for as long as possible to detect and monitor the environment during a critical phase in order to save human life, minimise loss of property and save wildlife

    Analytical study and computational modeling of statistical methods for data mining

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    Today, there is tremendous increase of the information available on electronic form. Day by day it is increasing massively. There are enough opportunities for research to retrieve knowledge from the data available in this information. Data mining and app

    Valuing biodiversity: Decision support for biosecurity response

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    This thesis develops a Decision Support System (DSS) to improve biosecurity response decisions affecting indigenous biodiversity. The key elements of the DSS are a synthesis of three components of non-market valuation: choice modelling, a systematic database of values and benefit transfer, with risk simulation to account for uncertainty. The innovative framework is demonstrated in a manual developed for Biosecurity New Zealand analysts for use during the early days of an incursion when time is severely constrained and uncertainty abounds. Theoretical approaches to decision making for environmental resource allocation decisions are reviewed with particular reference to decision support tools including non-market valuation, stated preference techniques, database development and benefit transfer. More complex and time consuming tools such as deliberative support and mediated modelling are also discussed. A framework is developed to quantify biodiversity values for use in Cost Benefit Analysis (CBA). The framework incorporates advanced choice modelling techniques demonstrated through four case studies, a systematic database of biodiversity values and transfer of these values using univariate benefit transfer with theoretical adjustment. The uncertainty in the values captured in the panel version of the Random Parameters Logit (RPL) model is integrated into CBA using risk simulation which utilises the means, standard deviations and correlation coefficients of risky variables to quantify the probability of achieving a positive Net Present Value of different response options. The DSS developed in this thesis has wider application in routine management of pests and diseases and in other resource allocation decisions by public agencies which impact on indigenous biodiversity

    Performance Assessment of Routing Protocols for IoT/6LoWPAN Networks

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    The Internet of Things (IoT) proposes a disruptive communication paradigm that allows smart objects to exchange data among themselves to reach a common goal. IoT application scenarios are multiple and can range from a simple smart home lighting system to fully controlled automated manufacturing chains. In the majority of IoT deployments, things are equipped with small devices that can suffer from severe hardware and energy restrictions that are responsible for performing data processing and wireless communication tasks. Thus, due to their features, communication networks that are used by these devices are generally categorized as Low Power and Lossy Networks (LLNs). The considerable variation in IoT applications represents a critical issue to LLN networks, which should offer support to different requirements as well as keeping reasonable quality-of-service (QoS) levels. Based on this challenge, routing protocols represent a key issue in IoT scenarios deployment. Routing protocols are responsible for creating paths among devices and their interactions. Hence, network performance and features are highly dependent on protocol behavior. Also, based on the adopted protocol, the support for some specific requirements of IoT applications may or may not be provided. Thus, a routing protocol should be projected to attend the needs of the applications considering the limitations of the device that will execute them. Looking to attend the demand of routing protocols for LLNs and, consequently, for IoT networks, the Internet Engineering Task Force (IETF) has designed and standardized the IPv6 Routing Protocol for Low Power and Lossy Networks (RPL). This protocol, although being robust and offering features to fulfill the need of several applications, still presents several faults and weaknesses (mainly related to its high complexity and memory requirement), which limits its adoption in IoT scenarios. An alternative to RPL, the Lightweight On-demand Ad Hoc Distancevector Routing Protocol – Next Generation (LOADng) has emerged as a less complicated routing solution for LLNs. However, the cost of its simplicity is paid for with the absence of adequate support for a critical set of features required for many IoT environments. Thus, based on the challenging open issues related to routing in IoT networks, this thesis aims to study and propose contributions to better attend the network requirements of IoT scenarios. A comprehensive survey, reviewing state-of-the-art routing protocols adopted for IoT, identified the strengths and weaknesses of current solutions available in the literature. Based on the identified limitations, a set of improvements is designed to overcome these issues and enhance IoT network performance. The novel solutions are proposed to include reliable and efficient support to attend the needs of IoT applications, such as mobility, heterogeneity, and different traffic patterns. Moreover, mechanisms to improve the network performance in IoT scenarios, which integrate devices with different communication technologies, are introduced. The studies conducted to assess the performance of the proposed solutions showed the high potential of the proposed solutions. When the approaches presented in this thesis were compared with others available in the literature, they presented very promising results considering the metrics related to the Quality of Service (QoS), network and energy efficiency, and memory usage as well as adding new features to the base protocols. Hence, it is believed that the proposed improvements contribute to the state-of-the-art of routing solutions for IoT networks, increasing the performance and adoption of enhanced protocols.A Internet das Coisas, do inglĂȘs Internet of Things (IoT), propĂ”e um paradigma de comunicação disruptivo para possibilitar que dispositivos, que podem ser dotados de comportamentos autĂłnomos ou inteligentes, troquem dados entre eles buscando alcançar um objetivo comum. Os cenĂĄrios de aplicação do IoT sĂŁo muito variados e podem abranger desde um simples sistema de iluminação para casa atĂ© o controle total de uma linha de produção industrial. Na maioria das instalaçÔes IoT, as “coisas” sĂŁo equipadas com um pequeno dispositivo, responsĂĄvel por realizar as tarefas de comunicação e processamento de dados, que pode sofrer com severas restriçÔes de hardware e energia. Assim, devido Ă s suas caracterĂ­sticas, a rede de comunicação criada por esses dispositivos Ă© geralmente categorizada como uma Low Power and Lossy Network (LLN). A grande variedade de cenĂĄrios IoT representam uma questĂŁo crucial para as LLNs, que devem oferecer suporte aos diferentes requisitos das aplicaçÔes, alĂ©m de manter nĂ­veis de qualidade de serviço, do inglĂȘs Quality of Service (QoS), adequados. Baseado neste desafio, os protocolos de encaminhamento constituem um aspecto chave na implementação de cenĂĄrios IoT. Os protocolos de encaminhamento sĂŁo responsĂĄveis por criar os caminhos entre os dispositivos e permitir suas interaçÔes. Assim, o desempenho e as caracterĂ­sticas da rede sĂŁo altamente dependentes do comportamento destes protocolos. Adicionalmente, com base no protocolo adotado, o suporte a alguns requisitos especĂ­ficos das aplicaçÔes de IoT podem ou nĂŁo ser fornecidos. Portanto, estes protocolos devem ser projetados para atender as necessidades das aplicaçÔes assim como considerando as limitaçÔes do hardware no qual serĂŁo executados. Procurando atender Ă s necessidades dos protocolos de encaminhamento em LLNs e, consequentemente, das redes IoT, a Internet Engineering Task Force (IETF) desenvolveu e padronizou o IPv6 Routing Protocol for Low Power and Lossy Networks (RPL). O protocolo, embora seja robusto e ofereça recursos para atender Ă s necessidades de diferentes aplicaçÔes, apresenta algumas falhas e fraquezas (principalmente relacionadas com a sua alta complexidade e necessidade de memĂłria) que limitam sua adoção em cenĂĄrios IoT. Em alternativa ao RPL, o Lightweight On-demand Ad hoc Distance-vector Routing Protocol – Next Generation (LOADng) emergiu como uma solução de encaminhamento menos complexa para as LLNs. Contudo, o preço da simplicidade Ă© pago com a falta de suporte adequado para um conjunto de recursos essenciais necessĂĄrios em muitos ambientes IoT. Assim, inspirado pelas desafiadoras questĂ”es ainda em aberto relacionadas com o encaminhamento em redes IoT, esta tese tem como objetivo estudar e propor contribuiçÔes para melhor atender os requisitos de rede em cenĂĄrios IoT. Uma profunda e abrangente revisĂŁo do estado da arte sobre os protocolos de encaminhamento adotados em IoT identificou os pontos fortes e limitaçÔes das soluçÔes atuais. Com base nas debilidades encontradas, um conjunto de soluçÔes de melhoria Ă© proposto para superar carĂȘncias existentes e melhorar o desempenho das redes IoT. As novas soluçÔes sĂŁo propostas para incluir um suporte confiĂĄvel e eficiente capaz atender Ă s necessidades das aplicaçÔes IoT relacionadas com suporte Ă  mobilidade, heterogeneidade dos dispositivos e diferentes padrĂ”es de trĂĄfego. AlĂ©m disso, sĂŁo introduzidos mecanismos para melhorar o desempenho da rede em cenĂĄrios IoT que integram dispositivos com diferentes tecnologias de comunicação. Os vĂĄrios estudos realizados para mensurar o desempenho das soluçÔes propostas mostraram o grande potencial do conjunto de melhorias introduzidas. Quando comparadas com outras abordagens existentes na literatura, as soluçÔes propostas nesta tese demonstraram um aumento do desempenho consistente para mĂ©tricas relacionadas a qualidade de serviço, uso de memĂłria, eficiĂȘncia energĂ©tica e de rede, alĂ©m de adicionar novas funcionalidades aos protocolos base. Portanto, acredita-se que as melhorias propostas contribuiem para o avanço do estado da arte em soluçÔes de encaminhamento para redes IoT e aumentar a adoção e utilização dos protocolos estudados
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