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

Roadmaps to Utopia: Tales of the Smart City

Notions of the Smart City are pervasive in urban development discourses. Various frameworks for the development of smart cities, often conceptualized as roadmaps, make a number of implicit claims about how smart city projects proceed but the legitimacy of those claims is unclear. This paper begins to address this gap in knowledge. We explore the development of a smart transport application, MotionMap, in the context of a £16M smart city programme taking place in Milton Keynes, UK. We examine how the idealized smart city narrative was locally inflected, and discuss the differences between the narrative and the processes and outcomes observed in Milton Keynes. The research shows that the vision of data-driven efficiency outlined in the roadmaps is not universally compelling, and that different approaches to the sensing and optimization of urban flows have potential for empowering or disempowering different actors. Roadmaps tend to emphasize the importance of delivering quick practical results. However, the benefits observed in Milton Keynes did not come from quick technical fixes but from a smart city narrative that reinforced existing city branding, mobilizing a growing network of actors towards the development of a smart region. Further research is needed to investigate this and other smart city developments, the significance of different smart city narratives, and how power relationships are reinforced and constructed through them

Involving Citizen Scientists in Biodiversity Observation

The involvement of non-professionals in scientific research and environmental monitoring, termed Citizen Science (CS), has now become a mainstream approach for collecting data on earth processes, ecosystems and biodiversity. This chapter examines how CS might contribute to ongoing efforts in biodiversity monitoring, enhancing observation and recording of key species and systems in a standardised manner, thereby supporting data relevant to the Essential Biodiversity Variables (EBVs), as well as reaching key constituencies who would benefit Biodiversity Observation Networks (BONs). The design of successful monitoring or observation networks that rely on citizen observers requires a careful balancing of the two primary user groups, namely data users and data contributors (i.e., citizen scientists). To this end, this chapter identifies examples of successful CS programs as well as considering practical issues such as the reliability of the data, participant recruitment and motivation, and the use of emerging technologies