16 research outputs found

    Development of a wireless sensor network for agricultural monitoring for Internet of Things (IoT)

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    Monitoring of the agricultural environment has become an important area of control and protection which provides real-time system and control communication with the physical world. This thesis focuses on Development ofa wireless Sensor Network for agricultural monitoring for Internet of things (IoT) to monitor environmental condition. Among the various technologies for Agriculture monitoring, Wireless Sensor Networks (WSNs) are perceived as an amazing one to gather and process information in the agricultural area with low-cost and low-energy consumption. WSN is capable of providing processed field data in real time from sensors which are physically distributed in the field. Agriculture and farming are one of the industries which have a late occupied their regards for WSNs, looking for this financially acute innovation to improve its production and upgrade agribusiness yield standard. Wireless Sensor Networks (WSNs) have pulled in a lot consideration in recent years.The proposed system uses WSN sensors to capture and track information pertaining to crop growth condition outside and inside greenhouses. 6LowPAN network protocol is used for low power consumption and for transmitting and receiving of data packets.This thesis introduces the agricultural monitoring system's hardware design, system architecture, and software process control. Agriculture monitoring system set-up is based on Contiki OS while device testing is carried out using real-time farm information and historical dat

    Energy-Efficient Message Bundling with Delay and Synchronization Constraints in Wireless Sensor Networks

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    In a wireless sensor network (WSN), reducing the energy consumption of battery-powered sensor nodes is key to extending their operating duration before battery replacement is required. Message bundling can save on the energy consumption of sensor nodes by reducing the number of message transmissions. However, bundling a large number of messages could increase not only the end-to-end delays and message transmission intervals, but also the packet error rate (PER). End-to-end delays are critical in delay-sensitive applications, such as factory monitoring and disaster prevention. Message transmission intervals affect time synchronization accuracy when bundling includes synchronization messages, while an increased PER results in more message retransmissions and, thereby, consumes more energy. To address these issues, this paper proposes an optimal message bundling scheme based on an objective function for the total energy consumption of a WSN, which also takes into account the effects of packet retransmissions and, thereby, strikes the optimal balance between the number of bundled messages and the number of retransmissions given a link quality. The proposed optimal bundling is formulated as an integer nonlinear programming problem and solved using a self-adaptive global-best harmony search (SGHS) algorithm. The experimental results, based on the Cooja emulator of Contiki-NG, demonstrate that the proposed optimal bundling scheme saves up to 51.8% and 8.8% of the total energy consumption with respect to the baseline of no bundling and the state-of-the-art integer linear programming model, respectively

    Modeling the processing delays of Internet of Things nodes in the ns3 network simulator

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    As arquiteturas de hardware dos dispositivos orientados para a Internet of Things (IoT), ou Internet das Coisas, pressupõem a existência de restrições energéticas. O hardware e o software destes dispositivos são, por isso, projetados por forma a minimizar o consumo energético e, frequentemente, a capacidade de processamento e memória destes dispositivos são bastante limitados. Como consequência os tempos de execução de processos ou funções de código podem ter valores médios e variações elevados. Estas restrições têm um impacto grande, e até agora pouco estudado, no desempenho das redes de comunicações de objetos. Torna-se por isso importante estudar e modelizar o desempenho das funções de comunicações destes dispositivos. Nesta tese pretende-se fazer este estudo e desenvolver um módulo de software para o simulador de redes ns-3 que simule os tempos de processamento das funções de comunicação de múltiplas combinações de plataforma hardware/sistemas operativos reais

    Secure Authenticated Key Exchange for Enhancing the Security of Routing Protocol for Low-Power and Lossy Networks

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    The current Routing Protocol for Low Power and Lossy Networks (RPL) standard provides three security modes Unsecured Mode (UM), Preinstalled Secure Mode (PSM), and Authenticated Secure Mode (ASM). The PSM and ASM are designed to prevent external routing attacks and specific replay attacks through an optional replay protection mechanism. RPL\u27s PSM mode does not support key replacement when a malicious party obtains the key via differential cryptanalysis since it considers the key to be provided to nodes during the configuration of the network. This thesis presents an approach to implementing a secure authenticated key exchange mechanism for RPL, which ensures the integrity and authentication of the received key while providing tamper-proof data communication for IoTs in insecure circumstances. Moreover, the proposed approach allows the key to be updated regularly, preventing an attacker from obtaining the key through differential cryptanalysis. However, it is observed that the proposed solution imposes an increase in the cost of communication, computation, power consumption, and memory usage for the network nodes

    Leveraging Reinforcement Learning for Adaptive Monitoring of Low-Power IoT Networks

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    International audienceLow-power Internet of Things (IoT) networks are widely deployed in various environments with resource constrained devices, making their states monitoring particularly challenging. In this paper, we propose an adaptive monitoring mechanism for low-power IoT devices, by using a reinforcement learning (RL) method to automatically adapt the polling frequencies of the collected attributes. Our goal is to minimize the number of monitoring packets while keeping accurate and timely detection of threshold crossings associated to supervised attributes. We study the various RL parameter settings under different monitoring attribute behaviors using OpenAi Gym simulator. We implement the RL based adaptive polling in Contiki OS and we evaluate its performance using Cooja simulator. Our results show that our approach converges to optimal polling frequencies and outperforms static periodic notification-based methods by reducing the number of monitoring packets, with a percentage of correctly detected threshold crossings exceeding 80%

    The Downside of Software-Defined Networking in Wireless Network

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    Mobile traffic volumes have grown exponentially because of the increase in services and applications. Traditional networks are complex to manage because the forwarding, control, and management planes are all bundled together and, thus, administrators are supposed to deploy high-level policies, as each vendor has its own configuration methods. Software-Defined Networking (SDN) is considered the future paradigm of communication networks. It decouples control logic from its underlying hardware, thereby promoting logically centralized network control and making the network more programmable and easy to configure. Low-power wireless technologies are moving toward a multitenant and multiapplication Internet of Things (IoT), which requires an architecture with scalable, reliable, and configured solutions. However, employing an SDN-based centralized architecture in the environment of a low-power wireless IoT network introduces significant challenges, such as difficult-to-control traffic, unreliable links, network contention, and high associated overheads that can significantly affect the performance of the network. This paper is a contribution toward a performance evaluation for the use of SDN in wireless networking by evaluating the latency, packet drop ratio (PDR), data extraction rate (DER), and overheads. The results show that SDN adds a high percentage of overheads to the network, which is about 43% of the 57% user packets, and the DER drops when the number of mesh nodes are increased, in addition to the high loss that was observed for packets that traveled over more hops

    MANAGING THE EFFECTS OF WIRELESS SENSORS ON VEHICLE AD HOC NETWORK (VANET) SAFETY

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    This paper proposes to conduct research on the vehicular ad hoc networks (VANET) area of Intelligent Transportation Systems (ITS) with a focus on investigating safety methods that will significantly reduce passenger vehicle collisions which ultimately will help to save lives and reduce property losses. Key areas of this ITS research will include highway infrastructure or wireless sensor networks (WSN) to the cloud (web service) and the cloud (web service) to highway infrastructure or wireless sensor network (WSN). In turn, the cloud (web service) will communicate with passenger vehicles as components of a highway infrastructure (WSN) to vehicle (I2V) systems and a vehicle to highway infrastructure (V2I) systems. In turn, the cloud (web service) will communicate with passenger vehicles as components of a vehicle to highway infrastructure (V2I) system and a highway infrastructure to vehicle (I2V) system. Active circuit emulation will be used as an analysis tool for this research. The cloud web service in this case, will be a database that will be connected through an IEEE802.11 broadband (Wi-Fi) gateway via a border router or a network capable application processor (NCAP) to hardware and software wireless sensor networks or a simulated wireless network. The highway infrastructure portion of this design will be the IEEE1451 standard-based wireless sensor network called wireless transducer interface modules (WTIM). These WTIMs will be responsible for disseminating information from their multitude of sensors to vehicles and/or to the cloud via NCAP routers

    Latency Optimization in Smart Meter Networks

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    In this thesis, we consider the problem of smart meter networks with data collection to a central point within acceptable delay and least consumed energy. In smart metering applications, transferring and collecting data within delay constraints is crucial. IoT devices are usually resource-constrained and need reliable and energy-efficient routing protocol. Furthermore, meters deployed in lossy networks often lead to packet loss and congestion. In smart grid communication, low latency and low energy consumption are usually the main system targets. Considering these constraints, we propose an enhancement in RPL to ensure link reliability and low latency. The proposed new additive composite metric is Delay-Aware RPL (DA-RPL). Moreover, we propose a repeaters’ placement algorithm to meet the latency requirements. The performance of a realistic RF network is simulated and evaluated. On top of the routing solution, new asynchronous ordered transmission algorithms of UDP data packets are proposed to further enhance the overall network latency performance and mitigate the whole system congestion and interference. Experimental results show that the performance of DA-RPL is promising in terms of end-to-end delay and energy consumption. Furthermore, the ordered asynchronous transmission of data packets resulted in significant latency reduction using just a single routing metric
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