The Internet of Things (IoT) has become ubiquitous due to its flexibility, ease-of-use, and reduced cost. As a consequence, the industry is adopting these systems in its transformation into Industry 4.0. However, the strict Quality of Service (QoS) requirements of the industry are not met with the default best-effort provisions of the IoT. Most industrial applications require strict guarantees in terms of end-to-end network reliability and latency. For instance, consecutive packet losses can lead to communication disruptions in supply chain systems. Therefore, adaptations are being made to fulfil these requirements with the IEEE Std 802.15.4-2015 Time slotted Channel Hopping (TSCH) link-layer standard and the IPv6 Routing Protocol for Low-Power and Lossy Networks (RPL) standard at the Internet Engineering Task Force (IETF). However, even by employing such industrial protocols, it is still difficult to achieve the expected QoS levels. Considering that RPL constructs and maintains a single-path from a source to a destination if there are potential issues on this path (e.g., queue overflow, variable wireless link quality) packets may suffer unexpected delays and even drops. If we consider a multi-path implementation where each node can replicate a packet into several paths, the transmission reliability improves since each packet copy is used to forward the packet information. However, uncontrolled replication can lead to network flooding, resulting in excessive power consumption.

In this tutorial, I will present several routing algorithms and protocols that improves network reliability and availability. I will start first with the Packet Automatic Repeat reQuest, Replication and Elimination, and Overhearing (PAREO) functions. Then, I will continue with two N-Disjoint algorithms and three Common Ancestor (CA) algorithms that select the most suitable upward relay nodes. Finally, I will conclude with the latest and the most efficient On-Demand Selection (ODeSe), multi-path routing algorithm. Note that the PAREO functions and the CA algorithms are work-in-progress drafts at the IETF standardisation organisation.

Mission Critical Services (MCS) are characterized by stringent requirements due to the criticality of the mission being performed. MCS can rely on different types of services, which include voice communications, video, data flows from sensors, location devices, among others. Service Function Chaining (SFC) enables the delivery of end-to-end services with distinct functions that can have multiple dependencies and different security requirements. SFCs consider the order on which functions must be executed/traversed and the components on which such functions are deployed, for instance if deployed at edge or cloud nodes. SFCs are commonly deployed using approaches that explicit the composition, the order of functions, but do not provide mechanisms to dynamically adapt the composition of services (e.g. add new function to a deployed service). Mission Critical applications have heterogeneous requirements. For instance, services in vehicular networks to support autonomous driving, monitoring critical infrastructures like smart grids, require low latency, high levels of security. On a safety perspective, Mission Critical Push To Talk Services in Smart Cities also require fast/flexible setup of groups, while the data services, require aggregation points due to the high data volumes. Thus, diverse MCS services can share a set of service functions (e.g., security) but the specificities associate with each service function must be considered. In this regard, Service Function Chaining for MCS needs to support adaptive composition and migration of service functions due to aspects such as availability of nodes and location updates. Indeed, the placement and chaining of service functions must be performed in a way that maximizes resilience, minimizes end-to-end latency, while considering constraints related to resource availability and trust in nodes and service functions.

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In this session the audience will learn how to configure and use recently developed hardware and software for participating in amateur radio APRS™ (Amateur Packet/Position Reporting System) communication networks; How to use APRS to communicate with nearby correspondents without Internet or telephone connections; How to use APRS and similar amateur radio services in a community to save human lives and properties; How to contribute to weather observation (amateur radio meteorology) by participating in APRS; How to create a local AMUNET (AMateur radio University NETwork) and expand visibility of an academic institution.

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