Davide Vega

Topology patterns of a community network: Guifi.net

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.

Cloud-Based Extension for Community-Lab

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 communitys 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 communitys 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.

Sharing hardware resources in heterogeneous computer-supported collaboration scenarios

There currently are many mobile computing devices with various properties and capabilities. These devices may need to collaborate among them to allow nomad workers to perform a common activity. Unfortunately software developers in charge of creating infrastructures or applications allowing these devices to cooperate among them, do not count with clear guidelines to design such software components; particularly when these components must work in a scenario involving heterogeneous devices. This paper presents a study that tries to understand how to address collaboration among heterogeneous mobile devices, by exploring several variables affecting the process. In particular, this study explores various strategies to borrow CPU slots from peer mobile computing devices and return the favor back later on. The study outcomes indicate there is a short list of computing and network variables affecting the collaboration capability of the mobile devices. These findings have been verified using data mining techniques. Based on these findings and the lessons learned, the article presents a simulation method of computing scenarios that can help developers to determine which computing configuration would be suitable to be used in each particular work scenario. Software designers can take advantage of this simulation method and the design guidelines reported in this paper in order to develop applications able to work appropriately in heterogeneous computing scenarios.

Exploring local service allocation in community networks

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.

Effort-based incentives for resource sharing in collaborative volunteer applications

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.

Towards Network-Aware Service Placement in Community Network Micro-Clouds

Cloud services in community networks have been enabled by micro-cloud providers. They form community network micro-clouds CNMCs, which grow organically, i.e. without being planned and optimized beforehand. Services running in community networks face specific challenges intrinsic to these infrastructures, such as the limited capacity of nodes and links, their dynamics and geographic distribution. CNMCs are used to deploy distributed applications, such as streaming and storage services, which transfer significant amounts of data between the nodes on which they run. Currently there is no support given to users for enabling them to chose better or the best option for specific service deployments. This paper looks at the next step in community network cloud service deployments, by taking network characteristics into account when deciding placement of service instances. We propose a service placement algorithm PASP that minimizes the service overlay diameter, while fulfilling service specific criteria. First, we characterize with simulations the potential performance gains of our approach. Secondly, we apply our algorithm to deploy a distributed storage service currently used in Guifi.net, and evaluate it in the real production network, assessing the performance and effects of our algorithm. We find that our PASP algorithm reduces the client reading times by an average of 16i¾ź% with a max. improvement of 31i¾ź% compared to the currently used organic placement scheme. Our results show how the choice of an appropriate set of nodes, taken from a larger resource pool, can influence service performance significantly.

Analysis of the Social Effort in Multiplex Participatory Networks

Community networks are participatory connectivity solutions for citizens where all the resources are owned, managed and controlled by the participants. As a natural evolution, in recent years some initiatives have flourished to provide higher level services based on volunteer computing and resource sharing paradigms. A fundamental aspect of these paradigms is user participation. In this work, we apply some social mining techniques aiming to identify the roles of the individuals in the social network behind a community network, here Guifi.net, and to measure the participatory involvement in the community network from 2003 to 2014. We observed that community network participants generally dedicate their time and effort to a single participatory forum, generating several types of community structures. We analyzed such structures using a multiplex network formed by mailing list in Guifi.net and a relationship graph built pairwise of users that share a physical wireless link. We were able to distinguish between non-hierarchical participatory forums, where almost all users are part of the same big community and two-tier participatory forums leaded by a small number of users that act as social bridges between their members. Finally, by testing the impact of community leaders in all participatory layers, we profiled the utility of the members’ effort to the whole wireless community network.

Community home gateways for P2P clouds

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.

Characterizing the effects of sharing hardware resources in mobile collaboration scenarios

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.

Role and position detection in networks: reloaded

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.