10 research outputs found

    Context-aware Cluster Based Device-to-Device Communication to Serve Machine Type Communications

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    Billions of Machine Type Communication (MTC) devices are foreseen to be deployed in next ten years and therefore potentially open a new market for next generation wireless network. However, MTC applications have different characteristics and requirements compared with the services provided by legacy cellular networks. For instance, an MTC device sporadically requires to transmit a small data packet containing information generated by sensors. At the same time, due to the massive deployment of MTC devices, it is inefficient to charge their batteries manually and thus a long battery life is required for MTC devices. In this sense, legacy networks designed to serve human-driven traffics in real time can not support MTC efficiently. In order to improve the availability and battery life of MTC devices, context-aware device-to-device (D2D) communication is exploited in this paper. By applying D2D communication, some MTC users can serve as relays for other MTC users who experience bad channel conditions. Moreover, signaling schemes are also designed to enable the collection of context information and support the proposed D2D communication scheme. Last but not least, a system level simulator is implemented to evaluate the system performance of the proposed technologies and a large performance gain is shown by the numerical results

    An Information-Centric Platform for Social- and Location-Aware IoT Applications in Smart Cities

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    Recent advances in Smart City infrastructures and the Internet of Things represent a significant opportunity to improve people's quality of life. Corresponding research often focuses on Cloud-centric network architectures where sensor devices transfer collected data to the Cloud for processing. However, the formidable traffic generated by countless IoT devices and the need for low-latency services raise the need to move away from centralized architectures and bring the computation closer to the data sources. To this end, this paper discusses SPF, a middleware solution that supports IoT application development, deployment, and management. SPF runs IoT services on capable devices located at the network edge and proposes an information-centric programming model that takes advantage of decentralized computation resources located in the proximity of application users and data sources. SPF also adopts Value-of-Information based methods to prioritize the transmission of essential information

    Smart city and resilient city: Differences and connections

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    Smart city (SC) and resilient city (RC) have been studied and practiced over the years in terms of the increasing urban problems and disasters. However, there is a large overlap between their meanings and relationships. With an increasing concern for both SC and RC in urban development and hazard mitigation, a review was conducted to explore the differences and connections between SC and RC with scientometric analysis. There are far more literatures about SC than RC, and very few papers discuss SC and RC together. The research trend, category, and hotspots from research clusters are illustrated and compared. Major differences are discussed from their objectives, driving force, current research focus, and criticism. The literatures both related to SC and RC are used to explore their connections, which are very limited. The results revealed that the RC's impact on SC are positive from physical, social, and environmental aspects, while SC's impacts on RC could be both positive and negative from the above three aspects. It is indicated that SC and RC are both important for urban planning and can be complementary to each other through proper design and governance, which implies the need for building a resilient smart city (RSC). This article is categorized under: Technologies > Structure Discovery and Clustering Technologies > Visualization

    Energy Efficient IoT Data Collection in Smart Cities Exploiting D2D Communications

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    Fifth Generation (5G) wireless systems are expected to connect an avalanche of “smart” objects disseminated from the largest “Smart City” to the smallest “Smart Home”. In this vision, Long Term Evolution-Advanced (LTE-A) is deemed to play a fundamental role in the Internet of Things (IoT) arena providing a large coherent infrastructure and a wide wireless connectivity to the devices. However, since LTE-A was originally designed to support high data rates and large data size, novel solutions are required to enable an efficient use of radio resources to convey small data packets typically exchanged by IoT applications in “smart” environments. On the other hand, the typically high energy consumption required by cellular communications is a serious obstacle to large scale IoT deployments under cellular connectivity as in the case of Smart City scenarios. Network-assisted Device-to-Device (D2D) communications are considered as a viable solution to reduce the energy consumption for the devices. The particular approach presented in this paper consists in appointing one of the IoT smart devices as a collector of all data from a cluster of objects using D2D links, thus acting as an aggregator toward the eNodeB. By smartly adapting the Modulation and Coding Scheme (MCS) on the communication links, we will show it is possible to maximize the radio resource utilization as a function of the total amount of data to be sent. A further benefit that we will highlight is the possibility to reduce the transmission power when a more robust MCS is adopted. A comprehensive performance evaluation in a wide set of scenarios will testify the achievable gains in terms of energy efficiency and resource utilization in the envisaged D2D-based IoT data collection

    Energy Efficient IoT Data Collection in Smart Cities Exploiting D2D Communications

    No full text
    Fifth Generation (5G) wireless systems are expected to connect an avalanche of “smart” objects disseminated from the largest “Smart City” to the smallest “Smart Home”. In this vision, Long Term Evolution-Advanced (LTE-A) is deemed to play a fundamental role in the Internet of Things (IoT) arena providing a large coherent infrastructure and a wide wireless connectivity to the devices. However, since LTE-A was originally designed to support high data rates and large data size, novel solutions are required to enable an efficient use of radio resources to convey small data packets typically exchanged by IoT applications in “smart” environments. On the other hand, the typically high energy consumption required by cellular communications is a serious obstacle to large scale IoT deployments under cellular connectivity as in the case of Smart City scenarios. Network-assisted Device-to-Device (D2D) communications are considered as a viable solution to reduce the energy consumption for the devices. The particular approach presented in this paper consists in appointing one of the IoT smart devices as a collector of all data from a cluster of objects using D2D links, thus acting as an aggregator toward the eNodeB. By smartly adapting the Modulation and Coding Scheme (MCS) on the communication links, we will show it is possible to maximize the radio resource utilization as a function of the total amount of data to be sent. A further benefit that we will highlight is the possibility to reduce the transmission power when a more robust MCS is adopted. A comprehensive performance evaluation in a wide set of scenarios will testify the achievable gains in terms of energy efficiency and resource utilization in the envisaged D2D-based IoT data collection

    Energy aware optimization for low power radio technologies

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    The explosive growth of IoT is pushing the market towards cheap, very low power devices with a strong focus on miniaturization, for applications such as in-body sensors, personal health monitoring and microrobots. Proposing procedures for energy efficiency in IoT is a difficult task, as it is a rapidly growing market comprised of many and very diverse product categories using technologies that are not stable, evolving at a high pace. The research in this field proposes solutions that go from physical layer optimization up to the network layer, and the sensor network designer has to select the techniques that are best for its application specific architecture and radio technology used. This work is focused on exploring new techniques for enhancing the energy efficiency and user experience of IoT networks. We divide the proposed techniques in frame and chip level optimization techniques, respectively. While the frame level techniques are meant to improve the performance of existing radio technologies, the chip level techniques aim at replacing them with crystal-free architectures. The identified frame level techniques are the use of preamble authentication and packet fragmentation, advisable for Low Power Wide Area Networks (LPWANs), a technology that offers the lowest energy consumption per provided service, but is vulnerable in front of energy exhaustion attacks and does not perform well in dense networks. The use of authenticated preambles between the sensors and gateways becomes a defence mechanism against the battery draining intended by attackers. We show experimentally that this approach is able to reduce with 91% the effect of an exhaustion attack, increasing the device's lifetime from less than 0.24 years to 2.6 years. The experiments were conducted using Loadsensing sensor nodes, commercially used for critical infrastructure control and monitoring. Even if exemplified on LoRaWAN, the use of preamble authentication is extensible to any wireless protocol. The use of packet fragmentation despite the packet fits the frame, is shown to reduce the probability of collisions while the number of users in the duty-cycle restricted network increases. Using custom-made Matlab simulations, important goodput improvement was obtained with fragmentation, with higher impact in slower and denser networks. Using NS3 simulations, we showed that combining packet fragmentation with group NACK can increase the network reliability, while reducing the energy consumed for retransmissions, at the cost of adding small headers to each fragment. It is a strategy that proves to be effective in dense duty-cycle restricted networks only, where the headers overhead is negligible compared to the network traffic. As a chip level technique, we consider using radios for communication that do not use external frequency references such as crystal oscillators. This would enable having all sensor's elements on a single piece of silicon, rendering it even ten times more energy efficient due to the compactness of the chip. The immediate consequence is the loss of communication accuracy and ability to easily switch communication channels. In this sense, we propose a sequence of frequency synchronization algorithms and phases that have to be respected by a crystal-free device so that it can be able to join a network by finding the beacon channel, synthesize all communication channels and then maintain their accuracy against temperature change. The proposed algorithms need no additional network overhead, as they are using the existing network signaling. The evaluation is made in simulations and experimentally on a prototype implementation of an IEEE802.15.4 crystal-free radio. While in simulations we are able to change to another communication channel with very good frequency accuracy, the results obtained experimentally show an initial accuracy slightly above 40ppm, which will be later corrected by the chip to be below 40 ppm.El crecimiento significativo de la IoT está empujando al mercado hacia el desarrollo de dispositivos de bajo coste, de muy bajo consumo energético y con un fuerte enfoque en la miniaturización, para aplicaciones que requieran sensores corporales, monitoreo de salud personal y micro-robots. La investigación en el campo de la eficiencia energética en la IoT propone soluciones que van desde la optimización de la capa física hasta la capa de red. Este trabajo se centra en explorar nuevas técnicas para mejorar la eficiencia energética y la experiencia del usuario de las redes IoT. Dividimos las técnicas propuestas en técnicas de optimización de nivel de trama de red y chip, respectivamente. Si bien las técnicas de nivel de trama están destinadas a mejorar el rendimiento de las tecnologías de radio existentes, las técnicas de nivel de chip tienen como objetivo reemplazarlas por arquitecturas que no requieren de cristales. Las técnicas de nivel de trama desarrolladas en este trabajo son el uso de autenticación de preámbulos y fragmentación de paquetes, aconsejables para redes LPWAN, una tecnología que ofrece un menor consumo de energía por servicio prestado, pero es vulnerable frente a los ataques de agotamiento de energía y no escalan frente la densificación. El uso de preámbulos autenticados entre los sensores y las pasarelas de enlace se convierte en un mecanismo de defensa contra el agotamiento del batería previsto por los atacantes. Demostramos experimentalmente que este enfoque puede reducir con un 91% el efecto de un ataque de agotamiento, aumentando la vida útil del dispositivo de menos de 0.24 años a 2.6 años. Los experimentos se llevaron a cabo utilizando nodos sensores de detección de carga, utilizados comercialmente para el control y monitoreo de infrastructura crítica. Aunque la técnica se ejemplifica en el estándar LoRaWAN, el uso de autenticación de preámbulo es extensible a cualquier protocolo inalámbrico. En esta tesis se muestra también que el uso de la fragmentación de paquetes a pesar de que el paquete se ajuste a la trama, reduce la probabilidad de colisiones mientras aumenta el número de usuarios en una red con restricciones de ciclos de transmisión. Mediante el uso de simulaciones en Matlab, se obtiene una mejora importante en el rendimiento de la red con la fragmentación, con un mayor impacto en redes más lentas y densas. Usando simulaciones NS3, demostramos que combinar la fragmentación de paquetes con el NACK en grupo se puede aumentar la confiabilidad de la red, al tiempo que se reduce la energía consumida para las retransmisiones, a costa de agregar pequeños encabezados a cada fragmento. Como técnica de nivel de chip, consideramos el uso de radios para la comunicación que no usan referencias de frecuencia externas como los osciladores basados en un cristal. Esto permitiría tener todos los elementos del sensor en una sola pieza de silicio, lo que lo hace incluso diez veces más eficiente energéticamente debido a la integración del chip. La consecuencia inmediata, en el uso de osciladores digitales en vez de cristales, es la pérdida de precisión de la comunicación y la capacidad de cambiar fácilmente los canales de comunicación. En este sentido, proponemos una secuencia de algoritmos y fases de sincronización de frecuencia que deben ser respetados por un dispositivo sin cristales para que pueda unirse a una red al encontrar el canal de baliza, sintetizar todos los canales de comunicación y luego mantener su precisión contra el cambio de temperatura. Los algoritmos propuestos no necesitan una sobrecarga de red adicional, ya que están utilizando la señalización de red existente. La evaluación se realiza en simulaciones y experimentalmente en una implementación prototipo de una radio sin cristal IEEE802.15.4. Los resultados obtenidos experimentalmente muestran una precisión inicial ligeramente superior a 40 ppm, que luego será corregida por el chip para que sea inferior a 40 ppm.Postprint (published version

    Social, Private, and Trusted Wearable Technology under Cloud-Aided Intermittent Wireless Connectivity

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    There has been an unprecedented increase in the use of smart devices globally, together with novel forms of communication, computing, and control technologies that have paved the way for a new category of devices, known as high-end wearables. While massive deployments of these objects may improve the lives of people, unauthorized access to the said private equipment and its connectivity is potentially dangerous. Hence, communication enablers together with highly-secure human authentication mechanisms have to be designed.In addition, it is important to understand how human beings, as the primary users, interact with wearable devices on a day-to-day basis; usage should be comfortable, seamless, user-friendly, and mindful of urban dynamics. Usually the connectivity between wearables and the cloud is executed through the user’s more power independent gateway: this will usually be a smartphone, which may have potentially unreliable infrastructure connectivity. In response to these unique challenges, this thesis advocates for the adoption of direct, secure, proximity-based communication enablers enhanced with multi-factor authentication (hereafter refereed to MFA) that can integrate/interact with wearable technology. Their intelligent combination together with the connection establishment automation relying on the device/user social relations would allow to reliably grant or deny access in cases of both stable and intermittent connectivity to the trusted authority running in the cloud.The introduction will list the main communication paradigms, applications, conventional network architectures, and any relevant wearable-specific challenges. Next, the work examines the improved architecture and security enablers for clusterization between wearable gateways with a proximity-based communication as a baseline. Relying on this architecture, the author then elaborates on the social ties potentially overlaying the direct connectivity management in cases of both reliable and unreliable connection to the trusted cloud. The author discusses that social-aware cooperation and trust relations between users and/or the devices themselves are beneficial for the architecture under proposal. Next, the author introduces a protocol suite that enables temporary delegation of personal device use dependent on different connectivity conditions to the cloud.After these discussions, the wearable technology is analyzed as a biometric and behavior data provider for enabling MFA. The conventional approaches of the authentication factor combination strategies are compared with the ‘intelligent’ method proposed further. The assessment finds significant advantages to the developed solution over existing ones.On the practical side, the performance evaluation of existing cryptographic primitives, as part of the experimental work, shows the possibility of developing the experimental methods further on modern wearable devices.In summary, the set of enablers developed here for wearable technology connectivity is aimed at enriching people’s everyday lives in a secure and usable way, in cases when communication to the cloud is not consistently available
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