The Fog Makes Sense: Enabling Social Sensing Services With Limited Internet Connectivity

Social sensing services use humans as sensor carriers, sensor operators and sensors themselves in order to provide situation-awareness to applications. This promises to provide a multitude of benefits to the users, for example in the management of natural disasters or in community empowerment. However, current social sensing services depend on Internet connectivity since the services are deployed on central Cloud platforms. In many circumstances, Internet connectivity is constrained, for instance when a natural disaster causes Internet outages or when people do not have Internet access due to economical reasons. In this paper, we propose the emerging Fog Computing infrastructure to become a key-enabler of social sensing services in situations of constrained Internet connectivity. To this end, we develop a generic architecture and API of Fog-enabled social sensing services. We exemplify the usage of the proposed social sensing architecture on a number of concrete use cases from two different scenarios.Comment: Ruben Mayer, Harshit Gupta, Enrique Saurez, and Umakishore Ramachandran. 2017. The Fog Makes Sense: Enabling Social Sensing Services With Limited Internet Connectivity. In Proceedings of The 2nd International Workshop on Social Sensing, Pittsburgh, PA, USA, April 21 2017 (SocialSens'17), 6 page

A module placement scheme for fog-based smart farming applications

As in Industry 4.0 era, the impact of the internet of things (IoT) on the advancement of the agricultural sector is constantly increasing. IoT enables automation, precision, and efficiency in traditional farming methods, opening up new possibilities for agricultural advancement. Furthermore, many IoT-based smart farming systems are designed based on fog and edge architecture. Fog computing provides computing, storage, and networking services to latency-sensitive applications (such as Agribots-agricultural robots-drones, and IoT-based healthcare monitoring systems), instead of sending data to the cloud. However, due to the limited computing and storage resources of fog nodes used in smart farming, designing a modules placement scheme for resources management is a major challenge for fog based smart farming applications. In this paper, our proposed module placement algorithm aims to achieve efficient resource utilization of fog nodes and reduce application delay and network usage in Fog-based smart farming applications. To evaluate the efficacy of our proposal, the simulation was done using iFogSim. Results show that the proposed approach is able to achieve significant reductions in latency and network usage

Mecanismos de rede para swarms de drones em ambientes de monitorização aquática

With the development of intelligent platforms for environment sensing, drones present themselves as a fundamental resource capable of responding to the widest range of applications. Monitoring aquatic sensing environments is one such application and the communication between them becomes a key aspect for both navigation and sensing tasks. Testing an aquatic environment with a high number of Unmanned Surface Vehicles (USVs) is very costly, requiring a lot of time and resources. Therefore, simulation platforms become elements of great importance . In this dissertation a simulator is developed containing a modular architecture, based on a delay tolerant network, being capable of simulating aquatic environments as similar as possible to real aquatic environments. In addition to the developed simulator, this dissertation presents methods and strategies of cluster formation, allowing the aquatic drones to select, in a distributed way, the gateways of each cluster that will be responsible for forwarding collected data towards the gateway on land. Two gateway selection methods were implemented, one focused on the energy of aquatic drones, and one considering different metrics such as link quality, centrality and energy. The proposed methods were evaluated across several cases and scenarios, with clusters built and changed in a dynamic way, and it was observed that the election of gateways with a method based on several metrics, together with appropriated control strategy, provides a better outcome of the network behaviour throughout the aquatic monitoring tasks.Com o desenvolvimento de plataformas inteligentes que permitem monitorizar vários ambientes, os drones apresentam-se como um recurso fundamental capaz de responder às mais vastas aplicações. A monitorização de meios aquáticos com recurso a drones é uma destas aplicações e a comunicação entre os mesmos torna-se um aspeto fundamental, tanto em tarefas de navegação como em tarefas de sensorização. Testar um ambiente aquático com um elevado número de drones aquáticos é muito caro, requer muito tempo e vários recursos, por isso, plataformas de simulação tornam-se elementos de grande importância. Nesta dissertação é desenvolvido um simulador, com uma arquitetura modular, tendo por base uma rede tolerante a atrasos, sendo capaz de simular ambientes aquáticos o mais semelhante possível a ambientes aquáticos reais. Para além do simulador desenvolvido, esta dissertação propõe métodos e estratégias de formação de clusters de drones, permitindo que os drones aquáticos elejam, de uma forma distribuída, os gateways de cada cluster que serão responsáveis por encaminhar os dados recolhidos pelos drones em direção à estação em terra. Foram implementados dois métodos de eleição de gateway, um focado na energia dos drones aquáticos, e outro capaz de considerar diferentes métricas, tais como a qualidade de ligação, a centralidade e a energia. Os métodos propostos foram avaliados através de vários cenários em que os clusters são construídos e alterados de forma dinâmica, e foi observado que a escolha de gateways com um método baseado em várias métricas, e juntamente com uma estratégia de controlo apropriada, proporciona um melhor comportamento da rede ao longo das tarefas de monitorização aquática.Mestrado em Engenharia Eletrónica e Telecomunicaçõe

Towards opportunistic UAV relaying for smart cities

With recent advances in cooperation among mobile computer systems, Unmanned Aerial Vehicles (UAVs) can be expected to be operated in large numbers and become a part of daily life for a variety of use cases. UAVs are already envi- sioned to act as mobile base stations, e.g., for situations with high node densities and strong communication requirements. However, UAVs are typically imagined to be provided specifically for this purpose. In this work, we study the effects of exploiting randomly passing UAVs at an urban intersection for the communication between vehicles on the ground. We show that a UAV, while following its pri- mary mission, can support cooperative driving vehicles in a purely opportunistic fashion by collecting periodic wireless broadcasts from vehicles and propagating all collected information periodically in an aggregated format. Using simulations, we show that such an opportunistic UAV relaying approach can lead to an improvement of approx. 6 percentage points (% points) in terms of perception of other vehicles

Hybrid LoRa-IEEE 802.11s Opportunistic Mesh Networking for Flexible UAV Swarming

Unmanned Aerial Vehicles (UAVs) and small drones are nowadays being widely used in heterogeneous use cases: aerial photography, precise agriculture, inspections, environmental data collection, search-and-rescue operations, surveillance applications, and more. When designing UAV swarm-based applications, a key "ingredient" to make them effective is the communication system (possible involving multiple protocols) shared by flying drones and terrestrial base stations. When compared to ground communication systems for swarms of terrestrial vehicles, one of the main advantages of UAV-based communications is the presence of direct Line-of-Sight (LOS) links between flying UAVs operating at an altitude of tens of meters, often ensuring direct visibility among themselves and even with some ground Base Transceiver Stations (BTSs). Therefore, the adoption of proper networking strategies for UAV swarms allows users to exchange data at distances (significantly) longer than in ground applications. In this paper, we propose a hybrid communication architecture for UAV swarms, leveraging heterogeneous radio mesh networking based on long-range communication protocols—such as LoRa and LoRaWAN—and IEEE 802.11s protocols. We then discuss its strengths, constraints, viable implementation, and relevant reference use cases