References of "Capponi, Andrea 50024102"
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See detailEnergy Efficient Data Collection in Opportunistic Mobile Crowdsensing Architectures for Smart Cities
Capponi, Andrea UL; Fiandrino, Claudio UL; Kliazovich, Dzmitry UL et al

in 3rd IEEE INFOCOM Workshop on Smart Cites and Urban Computing (2017, May)

Smart cities employ latest information and communication technologies to enhance services for citizens. Sensing is essential to monitor current status of infrastructures and the environment. In Mobile ... [more ▼]

Smart cities employ latest information and communication technologies to enhance services for citizens. Sensing is essential to monitor current status of infrastructures and the environment. In Mobile Crowdsensing (MCS), citizens participate in the sensing process contributing data with their mobile devices such as smartphones, tablets and wearables. To be effective, MCS systems require a large number of users to contribute data. While several studies focus on developing efficient incentive mechanisms to foster user participation, data collection policies still require investigation. In this paper, we propose a novel distributed and energy-efficient framework for data collection in opportunistic MCS architectures. Opportunistic sensing systems require minimal intervention from the user side as sensing decisions are application- or device-driven. The proposed framework minimizes the cost of both sensing and reporting, while maximizing the utility of data collection and, as a result, the quality of contributed information. We evaluate performance of the framework with simulations, performed in a real urban environment and with a large number of participants. The simulation results verify cost-effectiveness of the framework and assess efficiency of the data generation process. [less ▲]

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See detailCrowdSenSim: a Simulation Platform for Mobile Crowdsensing in Realistic Urban Environments
Fiandrino, Claudio UL; Capponi, Andrea UL; Cacciatore, Giuseppe UL et al

in IEEE Access (2017)

Smart cities take advantage of recent ICT developments to provide added value to existing public services and improve quality of life for the citizens. The Internet of Things (IoT) paradigm makes the ... [more ▼]

Smart cities take advantage of recent ICT developments to provide added value to existing public services and improve quality of life for the citizens. The Internet of Things (IoT) paradigm makes the Internet more pervasive where objects equipped with computing, storage and sensing capabilities are interconnected with communication technologies. Because of the widespread diffusion of IoT devices, applying the IoT paradigm to smart cities is an excellent solution to build sustainable Information and Communication Technology (ICT) platforms. Having citizens involved in the process through mobile crowdsensing (MCS) techniques augments capabilities of these ICT platforms without additional costs. For proper operation, MCS systems require the contribution from a large number of participants. Simulations are therefore a candidate tool to assess the performance of MCS systems. In this paper, we illustrate the design of CrowdSenSim, a simulator for mobile crowdsensing. CrowdSenSim is designed specifically for realistic urban environments and smart cities services. We demonstrate the effectiveness of CrowdSenSim for the most popular MCS sensing paradigms (participatory and opportunistic) and we present its applicability using a smart public street lighting scenario. [less ▲]

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See detailA Cost-Effective Distributed Framework for Data Collection in Cloud-based Mobile Crowd Sensing Architectures
Capponi, Andrea UL; Fiandrino, Claudio UL; Kliazovich, Dzmitry UL et al

in IEEE Transactions on Sustainable Computing (2017)

Mobile crowd sensing received significant attention in the recent years and has become a popular paradigm for sensing. It operates relying on the rich set of built-in sensors equipped in mobile devices ... [more ▼]

Mobile crowd sensing received significant attention in the recent years and has become a popular paradigm for sensing. It operates relying on the rich set of built-in sensors equipped in mobile devices, such as smartphones, tablets and wearable devices. To be effective, mobile crowd sensing systems require a large number of users to contribute data. While several studies focus on developing efficient incentive mechanisms to foster user participation, data collection policies still require investigation. In this paper, we propose a novel distributed and sustainable framework for gathering information in cloud-based mobile crowd sensing systems with opportunistic reporting. The proposed framework minimizes cost of both sensing and reporting, while maximizing the utility of data collection and, as a result, the quality of contributed information. Analytical and simulation results provide performance evaluation for the proposed framework by providing a fine-grained analysis of the energy consumed. The simulations, performed in a real urban environment and with a large number of participants, aim at verifying the performance and scalability of the proposed approach on a large scale under different user arrival patterns. [less ▲]

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See detailAssessing Performance of Internet of Things-based Mobile Crowdsensing Systems for Sensing as a Service Applications in Smart Cities
Capponi, Andrea UL; Fiandrino, Claudio UL; Franck, Christian UL et al

in 8th IEEE International Conference on Cloud Computing Technology and Science (CloudCom) (2016, December)

The Internet of Things (IoT) paradigm makes the Internet more pervasive. IoT devices are objects equipped with computing, storage and sensing capabilities and they are interconnected with communication ... [more ▼]

The Internet of Things (IoT) paradigm makes the Internet more pervasive. IoT devices are objects equipped with computing, storage and sensing capabilities and they are interconnected with communication technologies. Smart cities exploit the most advanced information technologies to improve public services. For being effective, smart cities require a massive amount of data, typically gathered from sensors. The application of the IoT paradigm to smart cities is an excellent solution to build sustainable Information and Communication Technology (ICT) platforms and to produce a large amount of data following Sensing as a Service (S^2aaS) business models. Having citizens involved in the process through mobile crowdsensing (MCS) techniques unleashes potential benefits as MCS augments the capabilities of existing sensing platforms. To this date, it remains an open challenge to quantify the costs the users sustain to contribute data with IoT devices such as the energy from the batteries and the amount of data generated at city-level. In this paper, we analyze existing solutions, we provide guidelines to design a large-scale urban level simulator and we present preliminary results from a prototype. [less ▲]

Detailed reference viewed: 132 (23 UL)