Recently, LoRa mesh networks have appeared as a communication technology for Internet of Things (IoT) devices. Through node-to-node communication, novel distributed IoT applications that extend beyond the capabilities of the LoRaWAN architecture can be enabled. However, current technologies for LoRa networks do not provide mechanisms for large and reliable data transfers between IoT nodes. This paper presents a service for such data transfers in LoRa mesh network applications, along with the protocol and formats used for inter-node communication. We explain the design choices and detail the implementation decisions to ensure that this service is practically usable. To this end, the service was integrated into the LoRaMesher library and is available as an open-source operational implementation. In experiments with ten real nodes and two network topologies, we observe that the service effectively achieves a large and reliable message delivery in an environment of concurrent transmissions and packet losses. In contrast, the cost of reliability for large data transfers is an increased number of messages and a higher delivery time. With the integration of the service into the LoRaMesher technology, developers now have a library that provides a reliable and large payload service for LoRa mesh network applications, eliminating the need to develop such capacity as a specific application-level solution.

Recently, LoRa mesh networks have gained increasing interest as a communication layer for sending data between IoT nodes. However, the network service of the firmware on the microcontroller-based nodes is typically limited to sending and receiving LoRa packets through the LoRa radio. Therefore, the packet processing by the node has to be done using an application-specific implementation. In this article, we present the design and implementation of a middleware that facilitates the development and operation of multiple distributed applications on LoRa mesh network nodes. The components we propose leverage the routing capacity of a LoRa mesh network enabled by the LoRaMesher library and provide a service for applications to send and receive messages from each other. Running several applications concurrently is also supported. We experiment with the middleware implemented in the node firmware with distributed applications that span from the LoRa mesh network to the Internet over MQTT. Our results show the support of bidirectional application-level communication, which can be used to build cross-network distributed applications that integrate services on LoRa mesh network nodes.

Due to the fact that large swathes on Earth still lack broadband communication coverage, especially in remote/rural areas and developing countries, there have been several attempts, starting from 3GPP Release 17, to lay out the architectural amendments needed for the integration of terrestrial networks with their non-terrestrial counterparts. Such attempts have led to recent projects regarding such integration that consider either 5G/5G-Advanced networks or more revolutionary approaches for the forthcoming 6G networks. In this manuscript, we give an overview of the architectural framework, technical innovations, and considered use cases of the Horizon Europe ETHER project.

LoRa has become popular in the Internet of Things (IoT) domain as a Low Power, Wide Area Network (LPWAN) radio technology providing low-power and long-range communication. In a typical IoT application, the LoRaWAN architecture is applied, where LoRa end nodes communicate their data to a gateway, which then over the Internet sends these data to a cloud-based service for further processing. However, LoRa can also be used standalone for the communication between LoRa nodes forming a mesh network. In this demo paper we present a library called LoRaMesher, which runs on LoRa nodes and forms a mesh network among these nodes. By implementing a distance vector routing protocol, LoRaMesher enables two nodes to communicate data packets with each other while the other nodes in the mesh network operate as routers. LoRaMesher can open the possibility for new distributed applications hosted only on such tiny IoT nodes.

The Guifi.net community network has evolved during the past 15 years into a telecommunications infrastructure that offers Internet access to more than 80.000 people. The monitoring system currently in place for this network is lagging behind the growth of the infrastructure, requiring manual intervention and counting several single points of failure. In this paper we present REDEMON, a resilient decentralized monitoring system, hosted on distributed and interconnected edge devices, for a reliable, eventually-consistent monitoring of the Guifi.net network, leveraging CRDT-based data structures implemented on AntidoteDB. We developed the REDEMON system as a prototype featuring resilience, decentralization and automation, in order to replace the legacy monitoring system. To assess the system, this prototype was deployed on resource-constraint edge nodes in the Guifi.net production network and evaluated under realistic conditions. The decentralized assignment mechanism successfully achieves setting the minimum number of monitoring servers per network device that satisfies the established system requirements. Besides, by concentrating the workload on the minimum required number of servers running at their maximum capacity, the remaining devices can idle away, reducing the consumption footprint of the system. With regard to computing resources, we measure a moderate CPU and RAM usage by the monitoring system on low-capacity devices, while we observe that a considerable network traffic is required for achieving a resilient and consistent data storage layer. This resilient and decentralized architecture could lay the basis for other edge applications in the cloud computing domain that need to coordinate over distributed and consistent shared data.

Community networks are decentralized communication networks built and operated by citizens, for citizens. We consider service discovery for clouds in such community networks. The currently employed solutions for service discovery are static and are not able to follow the dynamics in cloud service provision. We propose a novel service discovery mechanism based on the common Linux tool Avahi combined with TincVPN, in which the VPN allows Avahi to reach nodes beyond the local link. The concept of the micro-cloud is introduced which contains the nodes reached with the extended broadcast domain of Avahi. We evaluate the performance of the proposed service discovery mechanism in a real community cloud deployment consisting of 25 geographically distributed nodes. In experiments with different settings and number of services, we measure the number of services discovered as a function of the discovery time. Our results show that while a client eventually discovers all the services, a significant time is needed to achieve a complete service discovery. The proposed mechanism therefore seems appropriate for the case of community clouds with many replicas of a sought service, where the fast discovery of just a few providers satisfies the requirements of a client. By applying standard Linux tools, an advantage of our solution is that it is by default available on most Linux distribution, which allows our solution to be easily used for real deployments.

Wireless community networks (CNs) are large-scale, self-organized and decentralized communication infrastructures built and operated by citizens for citizens. CN cloud infrastructures have been recently introduced to run services inside the network, without the need to consume them from the Internet. We have developed a Linux-based distribution code-named Cloudy, which fosters the service deployment and automation in CN clouds. In this paper, we present two ways provisioned by Cloudy to integrate the services and improve the user QoS in these clouds. First, we present a distributed service discovery mechanism that helps users with service quality metrics to choose the best service from a pool of instances. Second, we experiment with a live video streaming service deployed in CN environments, using more than 50 real CN nodes distributed across Europe for the evaluation. Our analysis shows that, tuning the vital parameters of this service as neighborhood peer selection strategy and source node dispersion strategy, improves the video streaming QoS in the CNs. Our results indicate that both ways help the user to experience improved service performance. Automated service selection, needed once the number of micro service providers becomes larger, is the next step that can be built upon our results.

This demo paper presents Cloudy, a Debian-based distribution to build and deploy clouds in community networks. The demonstration covers the following aspects: Installation of Cloudy, the Cloudy GUI for usage and administration by end users, demonstration of Cloudy nodes and services deployed in the Guifi community network.

This paper describes an operational geographically distributed and heterogeneous cloud infrastructure with services and applications deployed in the Guifi community network. The presented cloud is a particular case of a community cloud, developed according to the specific needs and conditions of community networks. We describe the concept of this community cloud, explain our technical choices for building it, and our experience with the deployment of this cloud. We review our solutions and experience on offering the different service models of cloud computing (IaaS, PaaS and SaaS) in community networks. The deployed cloud infrastructure aims to provide stable and attractive cloud services in order to encourage community network user to use, keep and extend it with new services and applications.

Community-Lab is an open, distributed infrastructure for researchers to carry out experiments within wireless community networks. Community networks are an emergent model of infrastructures built with off-the-shelf communication equipment that aims to satisfy a community's demand for Internet access and ICT services. Community-Lab consists of more than 100 nodes that are integrated in existing community networks, thus giving researchers access to community networks and allowing them to conduct experimental evaluation of routing protocols, services and applications deployed there. Community networks have now the opportunity to extend the collaborative network building to the next level, that is, building collaborative services implemented as community clouds, built, operated and maintained by the community, that run on community-owned heterogeneous resources, and offer cloud-based services that are of the community's interest. This demo paper focuses on demonstrating the cloud extension of Community-Lab, enabling now community cloud experiments. By means of selected applications, we show how Community-Lab has been extended with distributed clouds, where different devices such as server, desktop PCs, low-resource embedded PCs and IoT boards are brought together forming a heterogeneous distributed cloud environment for researchers to experiment in community networks.