Abstract-Wireless community networks (CNs) are large-scale, self-organized and decentralized communication infrastructures built and operated by citizens for citizens. Community network 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 community network clouds. In this paper we present two ways provisioned by Cloudy to integrate the services and improve the users 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 across Europe for the evaluation. Our analysis shows that tuning the vital parameters of this service as neighborhood peer selection strategies, 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.
Abstract-Community networks are IP networks constantly being improved that evolve into large-scale computing platforms. This has resulted from the effort to adapt the cloud computing model towards services that can operate and utilize the resources inside the community network. The network and its infrastructure are contributed by individuals, companies, organizations and are maintained by the community itself. Community cloud devices are often low computing resource devices, such as home gateways, with limited capabilities. Currently, these devices are configured to run community services only. This has become a drawback for further adoption because of contributor's difficulty to also use the donated cloud device for private purposes. We apply container-based virtualization for the problem of resource sharing in low-capacity devices in order to create a multi-purpose execution environment in a single device. Thus, a single device can be configured to deliver to the user and the community a multi-purpose environment, such as personal and public, isolated from one another, while preserving the community cloud services. Our comparative analysis with the current infrastructure in community networks gives evidence that the capability of the devices to run concurrent services is maintained.
Edge cloud computing proposes to support shared services, by using the infrastructure at the network's edge. An important problem is the monitoring and management of services across the edge environment. Therefore, dissemination and gathering of data is not straightforward, differing from the classic cloud infrastructure. In this paper, we consider the environment of community networks for edge cloud computing, in which the monitoring of cloud services is required. We propose a monitoring platform to collect near real-time data about the services offered in the community network using a gossip-enabled network. We analyze and apply this gossip-enabled network to perform service discovery and information sharing, enabling data dissemination among the community. We implemented our solution as a prototype and used it for collecting service monitoring data from the real operational community network cloud, as a feasible deployment of our solution. By means of emulation and simulation we analyze in different scenarios, the behavior of the gossip overlay solution, and obtain average results regarding information propagation and consistency needs, i.e. in high latency situations, data convergence occurs within minutes.
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