29 research outputs found

    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 inglês Internet of Things (IoT), propõe um paradigma de comunicação disruptivo para possibilitar que dispositivos, que podem ser dotados de comportamentos autónomos ou inteligentes, troquem dados entre eles buscando alcançar um objetivo comum. Os cenários de aplicação do IoT são muito variados e podem abranger desde um simples sistema de iluminação para casa até o controle total de uma linha de produção industrial. Na maioria das instalações IoT, as “coisas” são equipadas com um pequeno dispositivo, responsável por realizar as tarefas de comunicação e processamento de dados, que pode sofrer com severas restrições de hardware e energia. Assim, devido às suas características, a rede de comunicação criada por esses dispositivos é geralmente categorizada como uma Low Power and Lossy Network (LLN). A grande variedade de cenários IoT representam uma questão crucial para as LLNs, que devem oferecer suporte aos diferentes requisitos das aplicações, além de manter níveis de qualidade de serviço, do inglês Quality of Service (QoS), adequados. Baseado neste desafio, os protocolos de encaminhamento constituem um aspecto chave na implementação de cenários IoT. Os protocolos de encaminhamento são responsáveis por criar os caminhos entre os dispositivos e permitir suas interações. Assim, o desempenho e as características da rede são altamente dependentes do comportamento destes protocolos. Adicionalmente, com base no protocolo adotado, o suporte a alguns requisitos específicos das aplicações de IoT podem ou não ser fornecidos. Portanto, estes protocolos devem ser projetados para atender as necessidades das aplicações assim como considerando as limitações do hardware no qual serão executados. Procurando atender às 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 às necessidades de diferentes aplicações, apresenta algumas falhas e fraquezas (principalmente relacionadas com a sua alta complexidade e necessidade de memória) que limitam sua adoção em cenários 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 é pago com a falta de suporte adequado para um conjunto de recursos essenciais necessários em muitos ambientes IoT. Assim, inspirado pelas desafiadoras questões ainda em aberto relacionadas com o encaminhamento em redes IoT, esta tese tem como objetivo estudar e propor contribuições para melhor atender os requisitos de rede em cenários IoT. Uma profunda e abrangente revisão do estado da arte sobre os protocolos de encaminhamento adotados em IoT identificou os pontos fortes e limitações das soluções atuais. Com base nas debilidades encontradas, um conjunto de soluções de melhoria é proposto para superar carências existentes e melhorar o desempenho das redes IoT. As novas soluções são propostas para incluir um suporte confiável e eficiente capaz atender às necessidades das aplicações IoT relacionadas com suporte à mobilidade, heterogeneidade dos dispositivos e diferentes padrões de tráfego. Além disso, são introduzidos mecanismos para melhorar o desempenho da rede em cenários IoT que integram dispositivos com diferentes tecnologias de comunicação. Os vários estudos realizados para mensurar o desempenho das soluções propostas mostraram o grande potencial do conjunto de melhorias introduzidas. Quando comparadas com outras abordagens existentes na literatura, as soluções propostas nesta tese demonstraram um aumento do desempenho consistente para métricas relacionadas a qualidade de serviço, uso de memória, eficiência energética e de rede, além de adicionar novas funcionalidades aos protocolos base. Portanto, acredita-se que as melhorias propostas contribuiem para o avanço do estado da arte em soluções de encaminhamento para redes IoT e aumentar a adoção e utilização dos protocolos estudados

    Energy-aware strategy for data forwarding in IoT ecosystem

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    The Internet of Things (IoT) is looming technology rapidly attracting many industries and drawing research attention. Although the scale of IoT-applications is very large, the capabilities of the IoT-devices are limited, especially in terms of energy. However, various research works have been done to alleviate these shortcomings, but the schemes introduced in the literature are complex and difficult to implement in practical scenarios. Therefore, considering the energy consumption of heterogeneous nodes in IoT eco-system, a simple energy-efficient routing technique is proposed. The proposed system has also employed an SDN controller that acts as a centralized manager to control and monitor network services, there by restricting the access of selfish nodes to the network. The proposed system constructs an analytical algorithm that provides reliable data transmission operations and controls energy consumption using a strategic mechanism where the path selection process is performed based on the remaining energy of adjacent nodes located in the direction of the destination node. The proposed energy-efficient data forwarding mechanism is compared with the existing AODV routing technique. The simulation result demonstrates that the protocol is superior to AODV in terms of packet delivery rate, throughput, and end-to-end delay

    MBMQA: A Multicriteria-Aware Routing Approach for the IoT 5G Network Based on D2D Communication

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    With the rapid development of future wireless networks, device-to-device (D2D) technology is widely used as the communication system in the Internet of Things (IoT) fifth generation (5G) network. The IoT 5G network based on D2D communication technology provides pervasive intelligent applications. However, to realize this reliable technology, several issues need to be critically addressed. Firstly, the device’s energy is constrained during its vital operations due to limited battery power; thereby, the connectivity will suffer from link failures when the device’s energy is exhausted. Similarly, the device’s mobility alters the network topology in an arbitrary manner, which affects the stability of established routes. Meanwhile, traffic congestion occurs in the network due to the backlog packet in the queue of devices. This paper presents a Mobility, Battery, and Queue length Multipath-Aware (MBMQA) routing scheme for the IoT 5G network based on D2D communication to cope with these key challenges. The back-pressure algorithm strategy is employed to divert packet flow and illuminate the device selection’s estimated value. Furthermore, a Multiple-Attributes Route Selection (MARS) metric is applied for the optimal route selection with load balancing in the D2D-based IoT 5G network. Overall, the obtained simulation results demonstrate that the proposed MBMQA routing scheme significantly improves the network performance and quality of service (QoS) as compared with the other existing routing schemes

    On Design, Evaluation and Enhancement of IP-Based Routing Solutions for Low Power and Lossy Networks

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    In early 2008, a new IETF Working Group (WG), namely ROLL, was chartered to investigate the suitability of existing IP routing protocols for Low Power Lossy Networks (LLNs), which at the time were suffering compatibility issues due to the pervasive use of proprietary protocols. Given the vision of the Internet of Things (IoT) and the role LLNs would play in the future Internet, the IETF set out to standardize an IPv6 based routing solution for such networks. After surveying existing protocols and determining their unsuitability, the WG started designing a new distance vector protocol called RPL (recently standardized in IETF RFC 6550) to fulfill their charter. Joining the WG efforts, we developed a very detailed RPL simulator and using link and traffic traces for existing networks, contributed with a performance study of the protocol with respect to several metrics of interest, such as path quality, end-to-end delay, control plane overhead, ability to cope with instability, etc. This work was standardized as IETF Informational RFC 6687.This detailed study uncovered performance issues for networks of very large scale. In this thesis, we provide an overview of RPL, summarize our findings from the performance study, analysis and comparison with a reactive lightweight protocol and suggest modifications to the protocol that yield significant performance improvements with respect to control overhead and memory consumption in very large scale networks. For future work, we propose a routing technique, named Hybrid Intelligent Path Computation (HIPC), along with modifications to the original RPL protocol standard, that outperforms solely distributed or centralized routing techniques. Finally, we also show how one can facilitate Quality of Service (QoS), load balancing and traffic engineering provision in the IoT without incurring any extra control overhead in number of packets other than that already consumed by the proposed IETF standard, using a combination of centralized and distributed computation.Ph.D., Computer Science -- Drexel University, 201

    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

    A Multi-Constraints Routing Scheme for MANET-assisted IoT in Smart Cities

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    The fifth-generation mobile network (5G) provides extreme throughput and extremely low latency, which enables the Internet of Things (IoT) era and a series of smart IoT ecosystems. The widespread equipping of Device-to-Device (D2D) modules for vehiculars allows transmitting directly between devices without relying on central devices such as access points or base stations. This is the foundation for the shaping of mobile ad hoc communications, so-called MANETs. The combination of MANETs and IoT technology has led to the development of MANET-assisted IoT applications, which offer unprecedented capabilities. However, due to the mobility of network nodes, routing is one of the main challenges in these networks. To address this problem, we propose a multi-constraints routing schema to enhance the performance of MANET-assisted IoT systems. Our simulation experiments show that the proposed solution significantly outperforms traditional routing solutions in terms of performance such as latency, packet delivery ratio, and throughput

    Impacts of Mobility Models on RPL-Based Mobile IoT Infrastructures: An Evaluative Comparison and Survey

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    With the widespread use of IoT applications and the increasing trend in the number of connected smart devices, the concept of routing has become very challenging. In this regard, the IPv6 Routing Protocol for Low-power and Lossy Networks (PRL) was standardized to be adopted in IoT networks. Nevertheless, while mobile IoT domains have gained significant popularity in recent years, since RPL was fundamentally designed for stationary IoT applications, it could not well adjust with the dynamic fluctuations in mobile applications. While there have been a number of studies on tuning RPL for mobile IoT applications, but still there is a high demand for more efforts to reach a standard version of this protocol for such applications. Accordingly, in this survey, we try to conduct a precise and comprehensive experimental study on the impact of various mobility models on the performance of a mobility-aware RPL to help this process. In this regard, a complete and scrutinized survey of the mobility models has been presented to be able to fairly justify and compare the outcome results. A significant set of evaluations has been conducted via precise IoT simulation tools to monitor and compare the performance of the network and its IoT devices in mobile RPL-based IoT applications under the presence of different mobility models from different perspectives including power consumption, reliability, latency, and control packet overhead. This will pave the way for researchers in both academia and industry to be able to compare the impact of various mobility models on the functionality of RPL, and consequently to design and implement application-specific and even a standard version of this protocol, which is capable of being employed in mobile IoT applications

    Clustering Arabic Tweets for Sentiment Analysis

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    The focus of this study is to evaluate the impact of linguistic preprocessing and similarity functions for clustering Arabic Twitter tweets. The experiments apply an optimized version of the standard K-Means algorithm to assign tweets into positive and negative categories. The results show that root-based stemming has a significant advantage over light stemming in all settings. The Averaged Kullback-Leibler Divergence similarity function clearly outperforms the Cosine, Pearson Correlation, Jaccard Coefficient and Euclidean functions. The combination of the Averaged Kullback-Leibler Divergence and root-based stemming achieved the highest purity of 0.764 while the second-best purity was 0.719. These results are of importance as it is contrary to normal-sized documents where, in many information retrieval applications, light stemming performs better than root-based stemming and the Cosine function is commonly used

    Clustering Arabic Tweets for Sentiment Analysis

    Get PDF
    The focus of this study is to evaluate the impact of linguistic preprocessing and similarity functions for clustering Arabic Twitter tweets. The experiments apply an optimized version of the standard K-Means algorithm to assign tweets into positive and negative categories. The results show that root-based stemming has a significant advantage over light stemming in all settings. The Averaged Kullback-Leibler Divergence similarity function clearly outperforms the Cosine, Pearson Correlation, Jaccard Coefficient and Euclidean functions. The combination of the Averaged Kullback-Leibler Divergence and root-based stemming achieved the highest purity of 0.764 while the second-best purity was 0.719. These results are of importance as it is contrary to normal-sized documents where, in many information retrieval applications, light stemming performs better than root-based stemming and the Cosine function is commonly used
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