261 research outputs found
Inducing collisions for fast RFID tag identification
No full textEfficient tag reading is one of the major challenges in RFID systems. So far, most of the literature has assumed that interference is intrinsically harmful and must be avoided. For this reason prior work aims at singulating tag transmissions in order to prevent collisions. In this paper we adopt the opposite approach: rather than working against interference, we embrace the collision of radio waves. We propose a new protocol, called TIANC, which uses multiple antennas and analog network coding (ANC) to recover the original tag transmissions. Performance analysis shows that TIANC achieves substantial speed improvement, performing up to 2.3 times faster than previously proposed mechanism
SECY APP: self configuration and easy management for software defined smart homes
No full textIn this paper we address configuration and management issues of smart homes. Current platforms requires the user to deal with several management inconvenience problems, such as increasing devices, operating between devices, and using new devices. From a user perspective, system configuration and management are major issues: ordinary consumers want to use systems performing minimal configuration. To address this issue, we propose a platform, composed of a web application and Software Defined Network (SDN). While the user interacts with an easy-to-use interface on a smart device, the app automatically generates and installs SDN rules. Our platform, besides facilitating configuration and management, results more efficient --- up to 4 times faster --- and reliable --- able to operate even in case of no connection with the cloud --- than current solutions
DRUBER: a trustable decentralized drone-based delivery system
No full textIn the latest years, there has been a growing interest in autonomous drone delivery. This is due to the increasing demand for efficient delivery services, and to the concurrent inability of existing ground based systems to provide guaranteed availability, and delivery time. However, the cost for implementing a centralized drone-based delivery service can only be afforded by large commercial organizations.
To face this issue we propose Druber, a fully distributed service based on a fleet of coordinated drones, belonging to multiple owners. With Druber, delivery of a parcel is provided by several drones, with intermediate pit stops for battery replacement or drone-to-drone parcel handovers. The use of a federated approach eliminates the need of a single company investment and guarantees a quickly deployable, highly scalable, and inexpensive architecture. Nevertheless, it introduces a problem of trust: can users rely on private drone owners? To guarantee a trustable service Druber leverages blockchain features to develop and control the entire delivery chain. Our evaluation shows an impressive advantage of our platform with respect to existing ground based services in terms of service cost and parcel delivery time, at the expense of a negligible delay for the management of blockchain operations
PrIME: Priority-based tag identification in mobile RFID systems
No full textOne of the major challenges in mobile RFID systems is the ability to read tags before they leave the system. So far, only a few works have considered tag mobility, targeting specific application scenarios, such as tags placed on a moving conveyor belt. However, many emerging applications involve mobile entities that are free to move so that the set of tags under the reader range is continuously and significantly changing. Such a mobile scenario poses important issues in terms of reliability and timeliness of the reading process. Not only the reader has to estimate the cardinality of the tag population passing through the system, but it has to also timely identify all tags. In this paper we propose PrIME, a new anti-collision protocol for single reader mobile systems. By means of extensive performance evaluation we show that PrIME is able to identify 100% of mobile tags when they follow a pedestrian mobility model, reducing the tag identification delay by over 90% with respect to the most performing solutions available in the literature
Fast Identification of Mobile RFID Tags
No full textWe consider the problem of efficient and fast identification of mobile tags in RFID networks. So far only a few works have addressed identification of mobile tags, and in very specific scenarios (i.e., tags placed on a moving conveyor). In this paper we address more general scenarios, involving tags that are free to move and may stay in the reader range for very short time (e.g., a few seconds), making their identification a real challenge for the reader. We propose a protocol, called PrIME (for Priority-based tag Identification in Mobile Environments), that is based on a probabilistic model and performs continuous reading cycles during which tags may enter and leave the system at any time. Through extensive ns2-based simulations we show that PrIME is very efficient, as it is able to identify 98-99% of mobile tags and to reduce the identification delay drastically with respect to other protocols
SMARTEEX: a software tool for SMART Environment EXperiments
No full textThe emerging demand for smart building systems has significantly stimulated the research on management platforms for sensors and actuators networks. In the last few years, several solutions have been proposed for this kind of networks, spanning from research to commercial systems.
As there are no really widespread standards, single devices operate based on proprietary protocols, making interoperability a significant issue. To achieve a thorough understanding of the performance of these systems in field experiments are needed.
This paper proposes SMARTEEX, a software tool to test smart building solutions. SMARTEEX is the first proposal that provides a virtual network to test different architectures for smart environments, running experiments with real and/or simulated smart devices. Our performance evaluation demonstrates that using SMARTEEX it is possible to compare for example a cloud-based with a SDN-based architecture
The Tags Are Alright: Robust Large-Scale RFID Clone Detection Through Federated Data-Augmented Radio Fingerprinting
No full textMillions of RFID tags are pervasively used all around the globe to inexpensively identify a wide variety of everyday-use objects. One of the key issues of RFID is that tags cannot use energy-hungry cryptography. For this reason, radio fingerprinting (RFP) is a compelling approach that leverages the unique imperfections in the tag's wireless circuitry to achieve large-scale RFID clone detection. Recent work, however, has unveiled that time-varying channel conditions can significantly decrease the accuracy of the RFP process. We propose the first large-scale investigation into RFP of RFID tags with dynamic channel conditions. Specifically, we perform a massive data collection campaign on a testbed composed by 200 off-the-shelf identical RFID tags and a software-defined radio (SDR) tag reader. We collect data with different tag-reader distances in an over-the-air configuration. To emulate implanted RFID tags, we also collect data with two different kinds of porcine meat inserted between the tag and the reader. We use this rich dataset to train and test several convolutional neural network (CNN)--based classifiers in a variety of channel conditions. Our investigation reveals that training and testing on different channel conditions drastically degrades the classifier's accuracy. For this reason, we propose a novel training framework based on federated machine learning (FML) and data augmentation (DAG) to boost the accuracy. Extensive experimental results indicate that (i) our FML approach improves accuracy by up to 48%; (ii) our DA approach improves the FML performance by up to 31%. To the best of our knowledge, this is the first paper experimentally demonstrating the efficacy of FML and DA on a large device population. We are sharing with the research community our fully-labeled 200-GB RFID waveform dataset, the entirety of our code and trained models
A flexible Cross-Layer Interface for Ad-Hoc Networks: Architectural Design and Implementation Issues
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