Experimental evaluation of a UWB-based cooperative positioning system for pedestrians in GNSS-denied environment

Cooperative positioning (CP) utilises information sharing among multiple nodes to enable positioning in Global Navigation Satellite System (GNSS)-denied environments. This paper reports the performance of a CP system for pedestrians using Ultra-Wide Band (UWB) technology in GNSS-denied environments. This data set was collected as part of a benchmarking measurement campaign carried out at the Ohio State University in October 2017. Pedestrians were equipped with a variety of sensors, including two different UWB systems, on a specially designed helmet serving as a mobile multi-sensor platform for CP. Different users were walking in stop-and-go mode along trajectories with predefined checkpoints and under various challenging environments. In the developed CP network, both Peer-to-Infrastructure (P2I) and Peer-to-Peer (P2P) measurements are used for positioning of the pedestrians. It is realised that the proposed system can achieve decimetre-level accuracies (on average, around 20 cm) in the complete absence of GNSS signals, provided that the measurements from infrastructure nodes are available and the network geometry is good. In the absence of these good conditions, the results show that the average accuracy degrades to meter level. Further, it is experimentally demonstrated that inclusion of P2P cooperative range observations further enhances the positioning accuracy and, in extreme cases when only one infrastructure measurement is available, P2P CP may reduce positioning errors by up to 95%. The complete test setup, the methodology for development, and data collection are discussed in this paper. In the next version of this system, additional observations such as the Wi-Fi, camera, and other signals of opportunity will be included

Using blockchain to create and capture value in the energy sector

The undergoing digital transition of the energy sector refers to the integration of decentralized ledger technologies and data-driven solutions that have the potential to truly revolutionize its ecosystem and business practices. The aim of a decentralized, inter connected and two-way interactive energy grid can be enabled by leveraging blockchain technologies. This research investigates how blockchain technology can create and capture value from data and the new business models applied in Web 3.0 and blockchain-based environments in the energy sector. A qualitative case study research design was conducted for primary data collection and pilot projects by the European Commission were used for secondary data collection. The analysis shows local energy communities as the main blockchain application in this sector, with adjacent applications such as P2P energy trading, smart contract & metering, carbon trading and grid management. The main benefits associated are transparency, integrity, grid automation and renewable energy sources promotion, and obstacles are mainly associated with the contrasting centralized design of the current energy systems. We conclude that value is created and captured through data provenance and transparency, data monetization and tokenization, and data sharing and collaboration in blockchain platforms. New business models include the decentralization and fusion between energy production and consumption, generating a new actor known as the prosumer. Fundamental to a successful implementation of local energy communities that allow energy and asset trading between peers.A transição digital do sector energético baseia-se na integração de tecnologias de registo descentralizadas e de soluções de tratamento de dados que têm o potencial de revolucionar o seu ecossistema. O objetivo de uma rede de energia descentralizada e interconectada em ambos os sentidos, pode ser concretizado através do recurso a tecnologias blockchain. Esta investigação analisa a forma como esta tecnologia pode criar e reter valor a partir de dados e dos novos modelos de negócio associados à Web 3.0 e a ambientes baseados em blockchain neste sector. Para a recolha de dados primários, foi efetuado um caso de estudo qualitativo. Para dados secundários foram analisados os projetos-piloto da Comissão Europeia. A análise demonstra que as comunidades locais de energia são a principal aplicação da blockchain, com aplicações adjacentes como trocas de energia P2P, contratos e contadores inteligentes, comércio de carbono e gestão da rede. Os principais benefícios associados são a transparência, a integridade, a automatização da rede e a promoção das fontes de energia renováveis. Os obstáculos estão principalmente associados à estrutura centralizada dos atuais sistemas energéticos. Concluímos que o valor é criado e capturado através da proveniência, transparência, monetização, tokenização e integração de dados em plataformas blockchain. Os novos modelos de negócio incluem a descentralização e a fusão entre a produção e o consumo de energia, gerando um novo elemento neste sector, o prosumer. Fundamental para uma implementação bem sucedida de comunidades locais de energia que permitam o comércio de energia e de ativos entre pares

Inferring Social Ties in Academic Networks Using Short-Range Wireless Communications

International audienceWiFi base stations are increasingly deployed in both public spaces and private companies, and the increase in their density poses a significant threat to the privacy of connected users. Prior studies have provided evidence that it is possible to infer the social ties of users from their location and co-location traces but they lack one important component: the comparison of the inference accuracy between an internal attacker (e.g., a curious application running on a mobile device) and a realistic external eavesdropper in the same field trial. In this paper, we experimentally show that such an eavesdropper is able to infer the type of social relationships between mobile users better than an internal attacker. Moreover, our results indicate that by exploiting the underlying social community structure of mobile users, the accuracy of the inference attacks doubles. Based on our findings, we propose countermeasures to help users protect their privacy against eavesdroppers

Analysis of scale effects in peer-to-peer networks

In this paper, we study both positive and negative scale effects on the operations of peer-to-peer (P2P) file sharing networks and propose the optimal sizing (number of peers) and grouping (number of directory intermediary) decisions. Using analytical models and simulation, we evaluate various performance metrics to investigate the characteristics of a P2P network. Our results show that increasing network scale has a positive effect on the expected content availability and transmission cost, but a negative effect on the expected provision and search costs. We propose an explicit expression for the overall utility of a content sharing P2P community that incorporates tradeoffs among all of the performance measures. This utility function is maximized numerically to obtain the optimal network size (or scale). We also investigate the impact of various P2P network parameters on the performance measures as well as optimal scaling decisions. Furthermore, we extend the model to examine the grouping decision in networks with symmetric interconnection structures and compare the performance between random- and location-based grouping policies. © 2008 IEEE.published_or_final_versio