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.

In project-based software engineering courses, the collaboration among participants is usually the cornerstone that makes these experiences successful and allows reaching the courses’ instructional goals. Prescribing a collaboration process for these courses is not appropriate, since their workflows are ad hoc framed; i.e., most of their activities are defined on-the-fly by the participants, according to their current context and needs. Therefore, only coordination and awareness mechanisms can be defined at the course design time, in order to support and promote collaboration among participants during these courses. This article presents a qualitative study that identifies and relates these coordination and awareness mechanisms, and embeds them in a set of software ceremonies. Course instructors and instructional designers can take advantage of these results, not only to identify design decision points, but also coordination and awareness mechanisms to promote collaboration in this type of courses.

eReuse is an initiative and action-research project that since 2015 has iterated over research and activism to understand, develop, apply to communities, evaluate and scale-up the circular economy of digital devices. The work, in partnership with diverse organisations, has contributed to the transition towards a circular economy of digital devices that contributes effectively to sustainable development.

The Internet gateway selection problem is becoming very important as the number of Internet-connected devices increases and stresses the limited number of Internet gateway nodes. The gateway nodes often experience frequent performance fluctuations, and the best gateway selection candidate changes frequently with growing network dynamics. We propose GateSelect, a customized selection algorithm for each client node that not only provides the best-effort selection candidate but also ensures the global, balanced distribution of the gateway nodes. We utilize over the counter, lightweight calculations to optimize the client-side selection algorithm by combining classification, short term performance prediction, and randomized selection. We compare our algorithm with several baseline algorithms, and the experiment results show that our proposal provides better performance and balanced distribution of gateway nodes.

Modern large-scale networked services, such as video streaming, are typically deployed at multiple locations in the network to provide redundancy and load balancing. Different techniques are used to provide performance monitoring information so that client nodes can select the best service instance. One of them is collaborative sensing, where clients share measurement results on the observed service performance to build a common ground of knowledge with low overhead. Clients can then use this common ground to select the most suitable service provider. However, collaborative algorithms are susceptible to false measurements sent by malfunctioning or malicious nodes, which decreases the accuracy of the performance sensing process. We propose Sense-Share, a simple light-weight and resilient collaborative sensing framework based on the similarity of the client nodes' perception of service performance. Our experimental evaluation in different topologies shows that service performance sensing using Sense-Share achieves, on average, 94% similarity to non-collaborative brute force performance sensing, tolerating faulty nodes. Furthermore, our approach effectively distributes the service monitoring requests over the service nodes and exploits direct inter-node communication to share measurements, resulting in reduced monitoring overhead.

Internet access has become a requirement to participate in society; however, the majority of the world's population is not yet online. Citizens can self-organize cooperatively to crowdsource community network infrastructures and achieve Internet access. In order to help address that challenge, this paper provides an analysis of a crowdsourced Internet access mechanism: the distributed Web proxy service in one of the largest community networks in the world. Several perspectives were considered in this analysis, e.g., data traffic, networking issues, and proxies responsiveness. The evaluation results show how the current manual proxy choice, based on social clues, becomes a popular service plagued with hot spots and inefficiencies, which opens several opportunities for improving these infrastructures. By taking advantage of it, our research shows that the trade-offs between informed proxy selection and admission control in proxies, could alleviate imbalances and uncertainty, and also improve the service with little additional burden. This represents an explicit and direct mechanism for improving the service provided by these community networks, and a clear benefit for its members.

Citizens develop Wireless Mesh Networks (WMN) in many areas as an alternative or their only way for local interconnection and access to the Internet. This access is often achieved through the use of several shared web proxy gateways. These network infrastructures consist of heterogeneous technologies and combine diverse routing protocols. Network-aware state-of-art proxy selection schemes for WMNs do not work in this heterogeneous environment. We developed a client-side gateway selection mechanism that optimizes the client-gateway selection, agnostic to underlying infrastructure and protocols, requiring no modification of proxies nor the underlying network. The choice is sensitive to network congestion and proxy load, without requiring a minimum number of participating nodes. Extended Vivaldi network coordinates are used to estimate client-proxy network performance. The load of each proxy is estimated passively by collecting the Time-to-First-Byte of HTTP requests, and shared across clients. Our proposal was evaluated experimentally with clients and proxies deployed in guifi.net, the largest community wireless network in the world. Our selection mechanism avoids proxies with heavy load and slow internal network paths, with overhead linear to the number of clients and proxies.

Collaborative learning activities have shown to be useful to address educational processes in several contexts. Monitoring these activities is mandatory to determine the quality of the collaboration and learning processes. Recent research works propose using Social Network Analysis techniques to understand students' collaboration learning process during these experiences. Aligned with that, this paper proposes the use of the indirect blockmodeling network analytic technique for monitoring the behaviour of different social roles played by students in collaborative learning scenarios. The usefulness of this technique was evaluated through a study that analysed the students' interaction network in a collaborative learning activity. Particularly, we tried to understand the structure of the interaction network during that process. Preliminary results suggest that indirect blockmodeling is highly useful for inferring and analysing the students' social roles, when the behaviour of roles are clearly different among them. This technique can be used as a monitoring service that can be embedded in collaborative learning applications.

Roles and positions are structural components in complex social systems which group actors based on how similarly they are connected to the rest of the actors. Role and position detection methods have been successfully used to evaluate and understand the dynamics of social networks and the behavior of their members. However, actor similarities used to detect positions have been based on pairwise comparisons so far: e.g., structural equivalence states that Alice and Bob are in the same position if they are both connected or not to the same other actors in the network, one by one. In this work we present a new framework to find positions and roles using comparisons between actors and sets of actors instead of just using pairwise comparisons. In this way we enable the usage of many more measures of similarity inside position and role detection methods, e.g., based on distances, community structure, triangles and cliques. As a result, we can identify new types of easily interpretable positions. Additionally, the proposed idea can be adapted to more complex models like hypergraphs or multiplex/multi-relational networks. We have evaluated our work on both synthetic and real data, using several existing and new similarity measures and providing both qualitative and quantitative evidence of the new possibilities enabled by our approach.

Smartphones are powerful sensing devices that can help us capture not only information from the environment, but also the users' activities. Based on that information, mobile systems can identify the user's behavioural patterns and adjust their services to better fit his needs. This paper presents a software infrastructure, named Collaborative Sensing Platform (CoSP), which facilitates the automatic collection and collaborative distribution of the data gathered from smartphone sensors. CoSP also helps to save energy during the sensing and data sharing processes. This platform was evaluated empirically in a laboratory experiment. The preliminary results indicate that this infrastructure is useful not only for data gathering and sharing, but also for reducing the battery consumption involved in the sensing tasks.

Technical communities are social structures that emerge around the interest of individuals to build and deploy their own technology or communication infrastructure, such as wireless community networks. In these communities, the access to shared resources is regulated by incentive mechanisms, which are usually based on the members' contributions. Typically, technical contributions are computed by these mechanisms, ignoring the non-technical activities that members voluntarily perform to keep the community alive, e.g., administration and coordination of the tasks performed by the sub-communities. This article presents a regulation mechanism that rewards not only the contribution of shared resources to the community, but also the participation of the community members in non-technical activities. This proposal was evaluated using simulations, and the obtained results allow researchers and managers of technical communities to build appropriate incentive mechanisms that rewards both, technical and non-technical contributions of their members.

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.

Opportunistic Internet of Things (IoT) extends the concept of opportunistic networking combining human users carrying mobile devices and smart things. It explores the relationships between humans and the opportunistic connection of smart objects. This paper presents a software infrastructure, named Opportunistic IoT Platform (OIoT), which helps developers to create and manage opportunistic IoT communities between smart devices. The platform enables the creation of opportunistic IoT communities that support the AllJoyn communications framework, for IoT devices and applications. Results from a preliminary evaluation of the OIoT platform indicate that this infrastructure is useful to manage and share data across opportunistic IoT communities.

Knowing the position of a device at a given time is fundamental to provide services tailored to the current user location. However, not all devices are able to perform positioning by their own, even when positioning systems are available in the environment where the user is located. This article presents a context-aware positioning model that allows devices participating in mobile ad-hoc networks, to sense their context and exchange positioning information with their peers. Thus, nodes knowing their own position could share it with their neighbors, allowing the latter to perform positioning. We discuss the performance of the model in a simulated mobile outdoor environment, populated with different types of devices. Our experiment shows that nodes without positioning capabilities are able estimate their position, although with reduced accuracy compared to those using a direct positioning strategy, such as GPS.

This work presents a technological analysis of guifi.net, a free, neutral, and open-access community network. Guifi.net consists of more than 27,000 operational nodes, which makes it the world’s largest community network in terms of the number of nodes and coverage area. This paper describes the characteristics of the network, the link level topology, its growth over a decade, and its resilience in terms of availability and reachability of network nodes. Our study is based on open data published by guifi.net regarding its nodes and wireless links , monitoring information, community database, and its web portal. The data includes historical information that covers the lifetime of the network. The scale and diversity of the network requires a separate analysis of the subsets of the entire dataset by area or by separating the core from the leaf nodes . This shows some degree of diversity in local characteristics caused by several demographic, geographic, technological, and network design factors. We focus on the following aspects: technological network diversity, topology characteristics, evolution of the network over time, analysis of robustness, and its effect on networking service availability. In addition, we analyse how the community, the technology used, the geographical region where the network is deployed, and its self-organised structure shape the network properties and determine its strengths and weaknesses. The study demonstrates that the guifi.net community network is diverse in technological choices for hardware, link protocols, and channels and uses a combination of routing protocols yet provides a common private IP network. The graph topology follows a power-law distribution for links in regions up to a few thousand k m 2 , limited to the scope of wireless links . Network growth has two aspects: a geographic growth of the network core using long distance links with wireless or fibre, and the local growth in density with leaf low-cost leaf nodes . The resilience of the network derived from the nodes’ uptime and the structure of the graph varies across different regions with more fragile leafs than core nodes and diverse degrees of graph resilience to random failures or coordinated attacks, such as natural causes, depending on the network planning, structure, and maturity. The guifi.net community network results from a loosely coupled and decentralised organic growth that exhibits large local differences, diverse growth, and maturity under a common community license and social network.

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.

This article presents a study on the nodes positioning confidence in mobile collaborative scenarios. The confidence of nodes positioning is an indicator that allows providing appropriate services and information to mobile users. In mobile ad-hoc networks, nodes with positioning capabilities could share their position with their neighbors in order to allow these latter to determine their own location collaboratively and increasing their positioning confidence. We study the fluctuation of this confidence in mobile scenarios populated by nodes with and without positioning capabilities. We analyze the effect of changing the maximum communication range of the nodes, the amount of nodes with positioning capabilities present in the environment. We also studied the impact that produces the degree of nodes mobility. The findings of this study are presented and discussed.

Community networks have emerged under the mottos of “break the strings that are limiting you”, “don't buy the network, be the network” or “a free net for everyone is possible”. Such networks create a measurable social impact as they provide to the community the right and opportunity of communication. As any other network that mixes wired and wireless links, the routing protocol must face several challenges that arise from the unreliable nature of the wireless medium. Link quality tracking helps the routing layer to select links that maximize the delivery rate and minimize traffic congestion. Moreover, link quality prediction has proved to be a technique that surpasses link quality tracking by foreseeing which links are more likely to change its quality. In this work, we focus on link quality prediction by means of a time series analysis. We apply this prediction technique in the routing layer of large-scale, distributed and decentralized networks. We demonstrate that this type of prediction achieves about a success probability of about 98% in both the short and long term.

Community Cloud computing is a new trend on cloud computing that aims to build service infrastructures upon Wireless Community Networks taking advantage of underused community physical resources. Service allocation protocols are a key design challenge that all cloud systems must properly address to optimize resource utilization. They are specially important when cloud services require a Quality of Service (QoS) and network stability or performance (delay, jitter, minimum bandwidth) cannot be guaranteed a-priory. This work presents a study that tries to understand how to address cloud service deployments in such scenario. In particular, we start proposing an allocation algorithm to find optimal solutions when there is a central authority that coordinates the process. These solutions optimize the communication cost in two ways: (1) minimizing the service overlay diameter and, (2) minimizing the coordination cost along the network. Based on the study of the algorithm and the experimental simulations, we study the variables that outcome optimal service allocations to the detriment of other solutions. We verify these findings using data mining techniques. Researchers can take advantage of the simulation results and our observations to design more reliable distributed algorithms able to dynamically self-adapt to network changes.

The widespread availability of smartphones with wireless communication and geo-positioning capabilities has open new opportunities to services for casual passersby, e.g. the delivery of advertising when they visit a certain area. Typically such messages are delivered to cellular phones, consuming thus part of the energy of these devices. Since these devices are constrained in battery-energy, disseminating messages using little energy represents a challenge for designers of this type of solutions. This paper presents a study based on simulations that intends to identify good strategies to irradiate messages collaboratively, minimizing the energy consumption in the devices involved in the information exchange. The simulation results show that the best irradiation strategy will depend on the number of devices in the area to be irradiated. Moreover, such a strategy will have more influence if the devices are dispersed. These findings should help designers of mobile collaborative applications based on messages irradiation, to identify the best dissemination strategy depending on the current network context.

Collaborative and volunteer applications need to implement incentive mechanisms to regulate resource sharing and encourage network nodes to contribute for reaching a certain goal. Typically, these incentive mechanisms assign resources to network node requests, based on the total amount of resources contributed by the requesting participant. This approach assumes that participants contributing more should also get back more resources from the collaborative environment. This assumption turns the system unfair to those participants with scarce resources, because they have just few resources to share. This paper proposes the use of an incentive strategy based on the contribution percentage of each node; i.e. an effort-based approach. This proposal is evaluated and compared to contribution-based strategies. The obtained results show that the proposed effort-based approach not only benefits participants that have scarce resources, but also it is able to satisfy the requests of the powerful nodes.

We present the community home gateway, a computer system attached to a wireless community network router, able to host platform and application services. Different to current home gateways and other low-end systems, the community home gateway offers resource virtualization, and can thus be used as a cloud resource. Furthermore, it removes the lack of a home gateway system that is open for service contributions and therefore constitutes an important step towards building P2P clouds with low-end devices.

Energy consumption is a main research issue in wireless sensor networks; and particularly in those where nodes collaborate to reach a goal. This article explores the energy consumption in mobile devices participating in a human-based wireless sensor network. Specifically, the paper proposes the use of a message predictor to help detect and reduce the number of unnecessary control packets delivered by the nodes as a way to keep updated the network topology. In order to evaluate this proposal, the Optimized Link State Routing protocol was modified to add a message predictor between the routing and the network layers. Eleven simulations were performed using a particular setting. The preliminary results indicate the use of the message predictor can help reduce considerably the nodes energy consumption without affecting the routing capability of the protocol. Although these results are still preliminary, they are highly encouraging.

This paper presents a measurement study of the topology and its effect on usage of Guifi.net, a large-scale community network. It focuses on the main issues faced by community network and lessons to consider for its future growth in order to preserve its scalability, stability and openness. The results show the network topology as an a typical high density Scale-Free network with critical points of failure and poor gateway selection or placement. In addition we have found paths with a large number of hops i.e. large diameter of the graph, and specifically long paths between leaf nodes and web proxies. The usage analysis using a widespread web proxy service confirms that these topological properties have an impact on the user experience.

Advances in wireless communication systems and mobile devices allow nomad users to participate in mobile collaborative activities. However the availability of hardware resources in the mobile devices participating in the collaboration process enhances or jeopardizes such activity. This paper studies how the network topology and the hardware resources distributed into a mobile network influence the collaboration activities among the participants. Several simulations were done to try to understand this issue. The obtained results show that in mobile collaboration scenarios involving a high number of resources-constraint mobile devices (e.g. handhelds), the maximum cooperation among node is obtained in a small world network topology. The results also show that another factor that encourages cooperation among nodes is the network size.

Mobile collaborative applications are usually deployed in work scenarios where the existence of fixed communication infrastructure is hard to predict. For that reason, these applications use Mobile Ad hoc Networks (MANETs) to support communication between mobile users. The complexity involved in such communication infrastructures make that developers avoid developing software for mobile work scenarios. However, it is possible to provide a reusable abstraction of such communication mechanisms, in order to avoid that developers have to deal with low-level programming. This article presents HLMP API, which is an application programming interface that provides access to a HLMP implementation. This API is organized as a fully distributed mobile communication infrastructure, able to run on MANETs. This infrastructure provides an important set of services, which are required to support mobile collaboration. The reuse of these services allows developers to reduce the complexity, times and cost of these development projects.

We propose an approach for predicting group formations, to address the problem of automating the incorporation of group awareness into CSCL applications. Contextual information can enable the construction of applications that effectively assist the group members to automatically communicate in synchronous and collocated collaborative learning activities. We used data traces collected from the study of students' behavior to train and test an intelligent system. Results have shown that context-information can be effectively used as a basis for a middleware for a dynamic group management. Inferring group membership is technically viable and can be used in real world settings.

Wireless communication and mobile computing technologies have brought new opportunities and challenges to the CSCW area. Traditional CSCW solutions concerning communication and coordination support are not applicable to mobile collaboration scenarios. Therefore, new reusable solutions have to be proposed in order to ease the development of mobile collaborative applications. This paper presents a set of design patterns to support communication and coordination in mobile ad-hoc scenarios. These two aspects are the basis to support mobile collaboration.

Collaborative tools based on the Web/Internet infrastructure such as E-mail, discussion groups, video/audio conferencing and virtual campuses have been proposed and implemented in many distance learning scenarios. Grids as Internet-wide resource infrastructures that enable access to large resource pools should permit new applications and learning activities. We propose ULabGrid as a new architecture that enables educators to design collaborative, distant laboratories for undergraduate students using the Grid infrastructure. We describe here the prototype that is being developed and present the results of our efforts to date.