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 atypical 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

Poster: TrueNets, a Topology Generator for Realistic Network Analysis

The availability of realistic topology generators is a key component in the study of network performance. This work describes a new approach for realistic generation of topologies, named TrueNets, that uses open data provided by public administrations and crowd-sensing efforts for populated areas, maps, altitude of land and buildings; TrueNets estimates link performance with classical propagation models and produces annotated topologies of networks that can actually exist in the selected areas, thus providing not only an abstract tool for performance evaluation, but also a design tool for planning. We use TrueNets to model distributed mesh networks and we show that the generated topologies differ substantially from state-of-the-art synthetic generators

Design trade-offs of crowdsourced web access in community networks

© 2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes,creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.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 ineffi- ciencies, 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.Peer ReviewedPostprint (author's final draft

Analysis of guifi.net's topology: extension of results

Report de recerca del Departament d'Arquitectura de ComputadorsThis report extends the analysis carried out in a previous work [1] about the topology of guifi.net wireless community network. The main objective is validating the topology generator proposed in [1] for guifi.net like topologies by considering a larger number of zones. The numerical results obtained in this report are in line with those obtained before, confirming the topology generator. Additionally, new results are presented, as the link ength distribution.Preprin

Alternative networks: toward global access to the Internet for all

It is often said that the Internet is ubiquitous in our daily lives, but this holds true only for those who can easily access it. In fact, billions of people are still digitally disconnected, as bringing connectivity to certain zones does not make a good business case. The only solution for these unsatisfied potential users is to directly undertake the building of the infrastructure required to obtaining access to the Internet, typically forming groups in order to share the corresponding cost. This article presents a global classification and a summary of the main characteristics of different Alternative Network deployments that have arisen in recent years with an aim to provide Internet services in places where mainstream network deployments do not exist or are not adequate solutions. The Global Access to the Internet for All Research Group of the Internet Research Task Force, where all authors actively participate, is interested in documenting these emerging deployments. As an outcome of this work, a classification has converged by consensus, where five criteria have been identified and, based on them, four different types of Alternative Networks have been identified and described with real-world examples. Such a classification is useful for a deeper understanding of the common characteristics behind existing and emerging Alternative Networks

guifi.net, a crowdsourced network infrastructure held in common

The expression “crowdsourced computer networks” refers to a network infrastructure built by citizens and organisations who pool their resources and coordinate their efforts to make these networks happen. “Community networks” are a subset of crowdsourced networks that are structured to be open, free, and neutral. In these communities the infrastructure is established by the participants and is managed as a common resource. Many crowdsourcing experiences have flourished in community networks. This paper discusses the case of guifi.net, a success case of a community network daily used by thousands of participants, focusing on its principles and the crowdsourcing processes and tools developed within the community, and the role they play in the ecosystem that is guifi.net; the current status of its implementation; its measurable local impact; and the lessons learned in more than a decade.Peer ReviewedPostprint (author's final draft

Alternative Network Deployments: Taxonomy, Characterization, Technologies, and Architectures

This document presents a taxonomy of a set of "Alternative Network Deployments" that emerged in the last decade with the aim of bringing Internet connectivity to people or providing a local communication infrastructure to serve various complementary needs and objectives. They employ architectures and topologies different from those of mainstream networks and rely on alternative governance and business models. The document also surveys the technologies deployed in these networks, and their differing architectural characteristics, including a set of definitions and shared properties. The classification considers models such as Community Networks, Wireless Internet Service Providers (WISPs), networks owned by individuals but leased out to network operators who use them as a low-cost medium to reach the underserved population, networks that provide connectivity by sharing wireless resources of the users, and rural utility cooperatives

Towards scalable Community Networks topologies

Community Networks (CNs) are grassroots bottom-up initiatives that build local infrastructures, normally using Wi-Fi technology, to bring broadband networking in areas with inadequate offer of traditional infrastructures such as ADSL, FTTx or wide-band cellular (LTE, 5G). Albeit they normally operate as access networks to the Internet, CNs are ad-hoc networks that evolve based on local requirements and constraints, often including additional local services on top of Internet access. These networks grow in highly decentralized manner that radically deviates from the top-down network planning practiced in commercial mobile networks, depending, on the one hand, on the willingness of people to participate, and, on the other hand, on the feasibility of wireless links connecting the houses of potential participants with each other. In this paper, we present a novel methodology and its implementation into an automated tool, which enables the exercise of (light) centralized control to the dynamic and otherwise spontaneous CN growth process. The goal of the methodology is influencing the choices to connect a new node to the CN so that it can grow with more balance and to a larger size. Input to our methodology are open source resources about the physical terrain of the CN deployment area, such as Open Street Map and very detailed (less than 1 m resolution) LIDAR-based data about buildings layout and height, as well as technical descriptions and pricing data about off-the-shelf networking devices that are made available by manufacturers. Data related to demographics can be easily added to refine the environment description. With these data at hand, the tool can estimate the technical and economic feasibility of adding new nodes to the CN and actively assist new CN users in selecting proper equipment and CN node(s) to connect with to improve the CN scalability. We test our methodology in four different areas representing standard territorial characterization categories: urban, suburban, intermediate, and rural. In all four cases our tool shows that CNs scale to much larger size using the assisted, network-aware methodology when compared with de facto practices. Results also show that the CNs deployed with the assisted methodology are more balanced and have a lower per-node cost for the same per-node guaranteed bandwidth. Moreover, this is achieved with fewer devices per node, which means that the network is cheaper to build and easier to maintain.Peer ReviewedPostprint (author's final draft

Imola: A decentralised learning-driven protocol for multi-hop White-Fi

In this paper we tackle the digital exclusion problem in developing and remote locations by proposing Imola, an inexpensive learning-driven access mechanism for multi-hop wireless networks that operate across TV white-spaces (TVWS). Stations running Imola only rely on passively acquired neighbourhood information to achieve scheduled-like operation in a decentralised way, without explicit synchronisation. Our design overcomes pathological circumstances such as hidden and exposed terminals that arise due to carrier sensing and are exceptionally problematic in low frequency bands. We present a prototype implementation of our proposal and conduct experiments in a real test bed, which confirms the practical feasibility of deploying our solution in mesh networks that build upon the IEEE 802.11af standard. Finally, the extensive system level simulations we perform demonstrate that Imola achieves up to 4x\u97 more throughput than the channel access protocol defined by the standard and reduces frame loss rate by up to 100%

Evaluation of mesh routing protocols for wireless community networks

In recent years, we have witnessed the exponential growth of wireless community networks as a response to the clear necessity of Internet access for participation in society. For wireless mesh networks that can scale up to thousands of nodes, which are owned and managed in a decentralized way, it is imperative for their survival to provide the network with self-management mechanisms that reduce the requirements of human intervention and technological knowledge in the operation of a community network. In this paper, we focus on one important self-management mechanism, routing, and we study the scalability, performance, and stability of three proactive mesh routing protocols: BMX6, OLSR, and Babel. We study different metrics on an emulation framework and on the W-ILab.T testbed at iMinds, making the most of the two worlds. Emulation allows us to have more control over the topology and more systematically repeat the experiments, whereas a testbed provides a realistic wireless medium and more reliable measurements, especially in terms of interference and CPU consumption. Results show the relative merits, costs, and limitations of the three protocols.Peer ReviewedPostprint (author's final draft