Alternate marking-based network telemetry for industrial WSNs

For continuous, persistent and problem-free operation of Industrial Wireless Sensor Networks (IWSN), it is critical to have visibility and awareness into what is happening on the network at any one time. Especially, for the use cases with strong needs for deterministic and real-time network services with latency and reliability guarantees, it is vital to monitor network devices continuously to guarantee their functioning, detect and isolate relevant problems and verify if all system requirements are being met simultaneously. In this context, this article investigates a light-weight telemetry solution for IWSNs, which enables the collection of accurate and continuous flowbased telemetry information, while adding no overhead on the monitored packets. The proposed monitoring solution adopts the recent Alternate Marking Performance Monitoring (AMPM) concept and mainly targets measuring end-to-end and hopby-hop reliability and delay performance in critical application flows. Besides, the technical capabilities and characteristics of the proposed solution are evaluated via a real-life implementation and practical experiments, validating its suitability for IWSNs

In-band network telemetry in industrial wireless sensor networks

With the emergence of the Internet of Things (IoT) and Industry 4.0 concepts, industrial applications are going through a tremendous change that is imposing increasingly diverse and demanding network dynamics and requirements with a wider and more fine-grained scale. Therefore, there is a growing need for more flexible and reconfigurable industrial networking solutions complemented with powerful monitoring and management functionalities. In this sense, this paper presents a novel efficient network monitoring and telemetry solution for Industrial Wireless Sensor Networks mainly focusing on the 6TiSCH Network stack, a complete protocol stack for ultra-reliable ultra-low-power wireless mesh networks. The proposed monitoring solution creates a flexible and powerful in-band network telemetry design with minimized resource consumption and communication overhead while supporting a wide range of monitoring operations and strategies for dealing with various network scenarios and use cases. Besides, the technical capabilities and characteristics of the proposed solution are evaluated via a real-life implementation, practical and theoretical analysis. These experiments demonstrate that in-band telemetry can provide ultra-efficient network monitoring operations without any effect on the network behavior and performance, validating its suitability for Industrial Wireless Sensor Networks

Why (and How) Networks Should Run Themselves

The proliferation of networked devices, systems, and applications that we depend on every day makes managing networks more important than ever. The increasing security, availability, and performance demands of these applications suggest that these increasingly difficult network management problems be solved in real time, across a complex web of interacting protocols and systems. Alas, just as the importance of network management has increased, the network has grown so complex that it is seemingly unmanageable. In this new era, network management requires a fundamentally new approach. Instead of optimizations based on closed-form analysis of individual protocols, network operators need data-driven, machine-learning-based models of end-to-end and application performance based on high-level policy goals and a holistic view of the underlying components. Instead of anomaly detection algorithms that operate on offline analysis of network traces, operators need classification and detection algorithms that can make real-time, closed-loop decisions. Networks should learn to drive themselves. This paper explores this concept, discussing how we might attain this ambitious goal by more closely coupling measurement with real-time control and by relying on learning for inference and prediction about a networked application or system, as opposed to closed-form analysis of individual protocols

Formation coordination and network management of UAV networks using particle swarm optimization and software-defined networking

In recent years, with the growth in the use of Unmanned Aerial Vehicles (UAVs), UAV-based systems have become popular in both military and civil applications. The lack of reliable communication infrastructure in these scenarios has motivated the use of UAVs to establish a network as flying nodes, also known as UAV networks. However, the high mobility degree of flying and terrestrial users may be responsible for constant changes in nodes’ positioning, which makes it more challenging to guarantee their communication during the operational time. In this context, this work presents a framework solution for formation coordination and network management of UAVs, which aims to establish and maintain a set of relays units in order to provide a constant, reliable and efficient communication link among user nodes - which are performing individual or collaborative missions on its turn. Such a framework relies on a set of formation coordination algorithms - including the Particle Swarm Optimization (PSO) evolutionary algorithm -, and also considers the use of Software-defined Networking-based (SDN) communication protocol for network management. For coordination proposes, a novel particle selection criteria is proposed, which aims to guarantee network manageability of UAV formations, therefore being able to guarantee service persistence in case of nodes’ failure occurrence, as well as to provide required network performance, as a consequence. Simulations performed in OMNeT++ show the efficiency of the proposed solution and prove a promising direction of the solution for accomplishing its purposes.Em regiões de confrontos militares, em cenários pós-catástrofes naturais e, inclusive, em grandes áreas de cultivo agrícola, é comum a ausência de uma infra-estrutura préestabelecida de comunicação entre usuários durante a execução de uma ou mais operações eventuais. Nestes casos, Veículos Aéreos Não Tripulados (VANTs) podem ser vistos como uma alternativa para o estabelecimento de uma rede temporária durante essas missões. Para algumas aplicações, a alta mobilidade destes usuários podem trazem grandes desafios para o gerenciamento autônomo de uma estrutura de comunicação aérea, como a organização espacial dos nós roteadores e as políticas de encaminhamento de pacotes adotadas durante a operação. Tendo isso em vista, esse trabalho apresenta o estudo de uma solução que visa o estabelecimento e manutenção das conexões entre os usuários - nos quais executam tarefas individuais ou colaborativas -, através do uso de algoritmos de coordenação de formação - no qual inclui o algoritmo evolucionário Otimização por Enxame de Partículas -, e, também, de conceitos relacionados a Rede Definidas por Software para o gerenciamento da rede. Ainda, é proposto um novo critério de seleção das partículas do algoritmo evolucionário, visando garantir gerenciabilidade das topologias formadas e, consequentemente, a persistência do serviço em caso de falha dos nós roteadores, assim como o cumprimento de especificações desejadas para o desempenho da rede. Simulações em OMNeT++ mostraram a eficácia da proposta e sustentam o modelo proposto a fim de atingir seus objetivos

On the Deployment of Healthcare Applications over Fog Computing Infrastructure

Fog computing is considered as the most promising enhancement of the traditional cloud computing paradigm in order to handle potential issues introduced by the emerging Interned of Things (IoT) framework at the network edge. The heterogeneous nature, the extensive distribution and the hefty number of deployed IoT nodes will disrupt existing functional models, creating confusion. However, IoT will facilitate the rise of new applications, with automated healthcare monitoring platforms being amongst them. This paper presents the pillars of design for such applications, along with the evaluation of a working prototype that collects ECG traces from a tailor-made device and utilizes the patient's smartphone as a Fog gateway for securely sharing them to other authorized entities. This prototype will allow patients to share information to their physicians, monitor their health status independently and notify the authorities rapidly in emergency situations. Historical data will also be available for further analysis, towards identifying patterns that may improve medical diagnoses in the foreseeable future