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.

Community networks (CNs) have gained momentum in the last few years with the increasing number of spontaneously deployed WiFi hotspots and home networks. These networks, owned and managed by volunteers, offer various services to their members and to the public. While Internet access is the most popular service, the provision of services of local interest within the network is enabled by the emerging technology of CN micro-clouds. By putting services closer to users, micro-clouds pursue not only

Nowadays there are inexpensive WiFi devices that have fostered the deployment of wireless communities. Well known routing protocols used in the Internet do not fit well to time varying characteristic of wireless networks. This has motivated an intensive research on routing protocols for wireless mesh networks. At this time there are a number of mature and stable implementations that are being deployed in production networks. In this paper we focus on the experimental evaluation of a production Wireless Mesh network being deployed in a testbed at Universitat Politècnica de Catalunya (UPC) and a quarter of the city of Barcelona, Spain. To our best knowledge, this is the first paper where a production community wireless network using 802.11an is analyzed.

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 powerlaw distribution for links in regions up to a few thousand Km 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.

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In this paper it is analyzed the topology of Guifi.net Wireless Community Network (WCN). WCN have emerged in recent years organized and deployed by the cooperation of its own customers. WCN keep parallelisms with the construction of the Internet, and seems logical to look for common characteristics among them. More specifically, it is investigated whether there are topology patterns of Guifi.net, and to what extend they share the power-law properties that have been found to obey many topology parameters of the Internet. The paper also proposes a topology generator algorithm that it is able to reproduce specific graph properties that have been obtained for Guifi.net.

Opportunistic Routing (OR) has been investigated in recent years as a way to increase the performance of multihop wireless networks by exploiting its broadcast nature. In contrast to traditional routing, where traffic is sent along pre-determined paths, in OR an ordered set of candidates is selected for each next-hop. Upon each transmission, the candidates coordinate such that the most priority one receiving the packet actually forwards it. Most of the research in OR has been addressed to investigate candidate selection algorithms. In this paper we propose a discrete time Markov chain to assess the improvement that may be achieved using opportunistic routing. We use our model to compare a selected group of candidate selection algorithms that have been proposed in the literature. Our main conclusion is that optimality is obtained at a high computational cost, with a performance gain very similar to that of much simpler but non optimal algorithms. Therefore, we conclude that fast and simple OR candidate selection algorithms may be preferable in dynamic networks, where the candidates sets are likely to be updated frequently.

Abstract-Community networks (CNs) have gained momentum in the last few years with the increasing number of spontaneously deployed WiFi hotspots and home networks. These networks, owned and managed by volunteers, offer various services to their members and to the public. To reduce the complexity of service deployment, community micro-clouds have recently emerged as a promising enabler for the delivery of cloud services to community users. By putting services closer to consumers, micro-clouds pursue not only a better service performance, but also a low entry barrier for the deployment of mainstream Internet services within the CN. Unfortunately, the provisioning of the services is not so simple. Due to the large and irregular topology, high software and hardware diversity of CNs, it requires of a "careful" placement of micro-clouds and services over the network.To achieve this, this paper proposes to leverage state information about the network to inform service placement decisions, and to do so through a fast heuristic algorithm, which is vital to quickly react to changing conditions. To evaluate its performance, we compare our heuristic with one based on random placement in Guifi.net, the biggest CN worldwide. Our experimental results show that our heuristic consistently outperforms random placement by 211% in terms of bandwidth gain. We quantify the benefits of our heuristic on a real live video-streaming service, and demonstrate that video chunk losses decrease significantly, attaining a 37% decrease in the loss packet rate. Further, using a popular Web 2.0 service, we demonstrate that the client response times decrease up to an order of magnitude when using our heuristic.