Performance Assessment of Routing Protocols for IoT/6LoWPAN Networks

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

Development of a Personal Area Network for biomedical measurements for Internet of Things (IoT)

Internet of Things is a set of ever growing technologies and specialized devices that are increasingly influential in our everyday lives. IoT is all about connecting the physical and the digital worlds in one enabling the collection of real world data and the automation of processes. IoT turns your typical device into an smart, programmable one, more capable of interacting with humans and thus enabling users to better understand their surroundings through the data collected. This data collected by the IoT devices can then be used on all kinds of contemporary services and applications. This project aims to implement an IoT application for biomedical measurements, consisting of a WSN(Wireless Sensor Network), where three sensor nodes will collect physical world measurements. This collected information will be transmitted to a routing device, that further send the information to the internet, where the user will be able to access the data in real time through a web browser and schedule some events. In order to carry out the described scenario, a Raspberry Pi and four Zolertia Z1, three working as sensor nodes and one working as a routing node were used. The Z1 mote is powered by a low power MSP430 class microcontroller. Contiki was the operating system chosen to run the sensor nodes. In this scenario, Raspberry Pi plays the role of a router, enabling the connection of the WSN network and the internet. To send the information from the nodes, a high-speed program was developed, aiming to beat the default restrictions that Contiki OS imposes on high-speed networks. The transport protocol chosen is UDP. On the receiving end, an UDP server and a python script were developed with the intent to send the collected data to our ASP.NET web server and mySQL database. Finally connectivity tests and network speed tests of the deployed system are presented

Towards Proactive Mobility-Aware Fog Computing

Paljude värkvõrk- ja ärirakenduste tavapäraseks osaks on sõltuvus kaugete pilveteenuste poolt pakutavast andmetöötlusvõimekusest. Arvestatav hulk seesugustest rakendustest koguvad andmeid mitmetelt ümbritsevatelt heterogeensetelt seadmetelt, et pakkuda reaalajal põhinevaid teenuseid oma kasutajatele. Taolise lahenduse negatiivseks küljeks on aga kõrge viiteaeg, mis muutub eriti problemaatiliseks, kui vastava rakenduse efektiivne töö on väleda vastuse saamisega otseses sõltuvuses. Taolise olukorra puhul on viiteaja vähendamiseks välja pakutud uduandmetöötlusel põhinev arhitektuur, mis kujutab endast arvutusmahukate andmetöötlusühikute jaotamist andmeallikate ja lõppkasutajatele lähedal asuvatele arvutusseadmetele. Vaatamata sellele, et uduandmetöötlusel põhinev arhitektuur on paljutõotav, toob see kaasa uusi väljakutseid seoses kvaliteetse uduandmetöötlusteenuse pakkumisega mobiilsetele kasutajatele. Käesolev magistritöö käsitleb proaktiivset lähenemist uduandmetöötlusele, kasutades selleks lähedalasuvatel kasutajatel baseeruvat mobiilset ad hoc võrgustikku, mis võimaldab uduteenusetuvastust ja juurdepääsu ilma pilveteenuse abi kasutamata. Proaktiivset lähenemist kasutatakse nii teenusetuvastuse ja arvutuse migratsiooni kui ka otsese uduteenuse pakkumise käigus, kiirendades arvutusühikute jaotusprotsessi ning parendadades arvutuste jaotust vastavalt käitusaegsele kontekstiinfole (nt. arvutusseadmete hetkevõimekus). Lisaks uuriti uduarvutuse rakendusviisi mobiilses sotsiaal–silmusvõrgustikus, tehes andmeedastuseks optimaalseima valiku vastavalt kuluefektiivsuse indeksile. Lähtudes katsetest nii päris seadmete kui simulaatoritega, viidi läbi käesoleva magistritöö komponentide kontseptuaalsete prototüüpide testhindamine.A common approach for many Internet of Things (IoT) and business applications is to rely on distant Cloud services for the processing of data. Several of these applications collect data from a multitude of proximity-based ubiquitous resources to provide various real-time services for their users. However, this has the downside of resulting in explicit latency of the result, being especially problematic when the application requires a rapid response in the edge network. Therefore, researchers have proposed the Fog computing architecture that distributes the computational data processing tasks to the edge network nodes located in the vicinity of the data sources and end-users, to reduce the latency. Although the Fog computing architecture is promising, it still faces challenges in many areas, especially when dealing with support for mobile users. Utilizing Fog for real-time mobile applications faces the new challenge of ensuring the seamless accessibility of Fog services on the move. Further, Fog computing also faces a challenge in mobility when the tasks originate from mobile ubiquitous applications in which the data sources are moving objects. In this thesis, a proactive approach for Fog computing is proposed, which supports proactive Fog service discovery and process migration using Mobile Ad hoc Social Network in proximity, enabling Fog-assisted ubiquitous service provisioning in proximity without distant Cloud services. Moreover, a proactive approach is also applied for the Fog service provisioning itself, in order to hasten the task distribution process in Mobile Fog use cases and provide an optimization scheme based on runtime context information. In addition, a case study regarding the usage of Fog Computing for the enhancement of Mobile Mesh Social Network was presented, along with a resource-aware Cost-Performance Index scheme to assist choosing the approach to be used for transmission of data. The proposed elements have been evaluated by utilizing a combination of real devices and simulators in order to provide proof-of-concept

Delay Contributing Factors and Strategies Towards Its Minimization in IoT

Internet of Things (IoT) refers to various interconnected devices, typically supplied with limited computational and communication resources. Most of the devices are designed to operate with limited memory and processing capability, low bandwidth, short range and other characteristics of low cost hardware. The resulting networks are exposed to traffic loss and prone to other vulnerabilities. One of the major concerns is to ensure that the network communication among these deployed devices remains at required level of Quality of Service (QoS) of different IoT applications. The purpose of this paper is to highlight delay contributing factors in Low Power and Lossy Networks (LLNs) since providing low end-to-end delay is a crucial issue in IoT environment especially for mission critical applications. Various research efforts in relevance to this aspect are then presente

Toward energy and resource efficient Internet-of-Things: a design principle combining computation, communications and protocols

Advances in future computing and communications to support IoT are becoming more important as the need to better utilize resources and make them energy-efficient grows. As a result, it is predicted that intelligent devices and networks, including WSNs, will become the new interfaces to support future IoT applications. However, many open challenges remain, which are mostly due to the resource constraints imposed by various hardware platforms and complex characteristics of applications wishing to make use of IoT systems. Thus, it becomes critically important to study how the current approaches incorporating both computing and communications in this area can be improved, and at the same time better understand the opportunities for the research community to utilize the proposed approaches. To this end, this article presents an overview of our latest research results in sensor edge computing and lightweight communication protocols as well as their potential applications

LCT: A Lightweight Cross-domain Trust Model for the Mobile Distributed Environment

In the mobile distributed environment, an entity may move across domains with great frequency. How to utilize the trust information in the previous domains and quickly establish trust relationships with others in the current domain remains a challenging issue. The classic trust models do not support cross-domain and the existing cross-domain trust models are not in a fully distributed way

A study into prolonging Wireless Sensor Network lifetime during disaster scenarios

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