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2020 Conference object Open Access OPEN

Edge-Based Video Surveillance with Embedded Devices
Kavalionak H., Gennaro C., Amato G., Vairo C., Perciante C., Meghini C., Falchi F., Rabitti F.
Video surveillance systems have become indispensable tools for the security and organization of public and private areas. In this work, we propose a novel distributed protocol for an edge-based face recogni-tion system that takes advantage of the computational capabilities of the surveillance devices (i.e., cameras) to perform person recognition. The cameras fall back to a centralized server if their hardware capabili-ties are not enough to perform the recognition. We evaluate the proposed algorithm via extensive experiments on a freely available dataset. As a prototype of surveillance embedded devices, we have considered a Rasp-berry PI with the camera module. Using simulations, we show that our algorithm can reduce up to 50% of the load of the server with no negative impact on the quality of the surveillance service.Source: 28th Symposium on Advanced Database Systems (SEBD), pp. 278–285, Villasimius, Sardinia, Italy, 21-24/06/2020

See at: ceur-ws.org Open Access | ISTI Repository Open Access | CNR ExploRA Open Access


2020 Conference object Open Access OPEN

Dynamic Wi-Fi RSSI normalization in unmapped locations
Kavalionak H., Tosato M., Barsocchi P., Nardini F. M.
With the growing availability of open access WLAN networks, we assisted to the increase of marketing services that are based on the data collected from the WLAN access points. The identification of visitors of a commercial venue using WLAN data is one of the issues to create successful marketing products. One of the ways to separate visitors is to analyse the RSSI of the mobile devices signals coming to various access points at the venue. Nevertheless, the indoor signal distortion makes RSSI based methods unreliable. In this work we propose the algorithm for the WLAN based RSSI normalization in uncontrolled environments. Our approach is based on the two steps, where at first based on the collected data we detect the devices whose RSSI can be taken as a basic one. At the second step the algorithm allows based on the previously detected basic RSSI to normalize the received signal from mobile devices. We provide the analysis of a real dataset of WLAN probes collected in several real commercial venues in Italy.Source: EDBT/ICDT 2020 Joint Conference, Copenhagen, Denmark, 30th March - 2nd April, 2020

See at: ceur-ws.org Open Access | CNR ExploRA Open Access


2018 Conference object Open Access OPEN

Toward Decentralised Consensus and Offloading for Area Coverage in a Fleet of Drones
Kavalionak H., Carlini E., Cassarà P., Meghini C.
A precise and dynamic visual coverage of a given area is an essential task in many smart contexts, ranging from civil communities to military applications. Due to the last years advancement in hardware miniaturization and efficiency, area coverage is often performed with a combination of static and moving devices, such as unmanned aerial vehicles (drones). Drones are useful to cope with the highly unpredictability and dynamicity of environments, but require specific and efficient solutions toward and efficient area coverage. In this paper we proposes an initial work toward a drone-based approach for the task of area coverage. In particular, we focus our analysis on the following points: (i) decentralized consensus for movement planning, and (ii) the integration of cloud computing infrastructures and technologies for computation offloading, both for image analysis and movement planning.Source: 9th International Conference on Wireless and Satellite Systems, WiSATS 2017, pp. 96–105, Oxford, United Kingdom, 14-15/09/2017
DOI: 10.1007/978-3-319-76571-6_10

See at: ISTI Repository Open Access | Unknown Repository Restricted | Unknown Repository Restricted | Unknown Repository Restricted | Unknown Repository Restricted | CNR ExploRA Restricted | Unknown Repository Restricted


2017 Conference object Restricted

A prediction-based distributed tracking protocol for video surveillance
Kavalionak H., Carlini E., Lulli A., Gennaro C., Amato G., Meghini C., Ricci L.
Video surveillance is an important security enforcement operation in many contexts, from large public areas to private smart homes and smart buildings. Today's video surveillance systems are much more than mere recording storages, as the advancement in classification and recognition allow for an immediate target recognition without the intervention of human operators. These smart video surveillance systems usually rely on a central server as the main coordination of recognition and tracking, which can represent a performance or economical bottleneck. In this paper, our contribution focuses on a decentralized protocol with the aim of eliminating such bottleneck. Our protocol organizes the distribution of a classification library among the cameras involved, which also participate actively to the target recognition phase. The protocol minimizes the network overhead towards the centralized server while keeping high the speed of recognition making use of a system to predict the movements of the targets. We tested the protocol by means of simulations, exploiting a realistic indoor human mobility model.Source: ICNSC 2017 - IEEE 14th International Conference on Networking, Sensing and Control, pp. 140–145, Calabria, Italy, 16-18 May, 2017
DOI: 10.1109/ICNSC.2017.8000081
DOI: 10.1109/icnsc.2017.8000081

See at: Unknown Repository Restricted | Unknown Repository Restricted | Unknown Repository Restricted | Unknown Repository Restricted | CNR ExploRA Restricted | Unknown Repository Restricted


2016 Article Restricted

Making puzzles green and useful for adaptive identity management in large-scale distributed systems
Cordeiro W. L. D. C., Santos F. R., Barcelos M. P., Gaspary L. P., Kavalionak H., Guerrieri A., Montresor A.
Various online systems offer a lightweight process for creating accounts (e.g., confirming an e-mail address), so that users can easily join them. With minimum effort, however, an attacker can subvert this process, obtain a multitude of fake accounts, and use them for malicious purposes. Puzzle-based solutions have been proposed to limit the spread of fake accounts, by establishing a price (in terms of computing resources) per identity requested. Although effective, they do not distinguish between requests coming from presumably legitimate users and potential attackers, and also lead to a significant waste of energy and computing power. In this paper, we build on adaptive puzzles and complement them with waiting time to introduce a green design for lightweight, long-term identity management; it balances the complexity of assigned puzzles based on the reputation of the origin (source) of identity requests, and reduces energy consumption caused by puzzle-solving. We also take advantage of lessons learned from massive distributed computing to come up with a design that makes puzzle-processing useful. Based on a set of experiments, we show that our solution provides significant energy savings and makes puzzle-solving a useful task, while not compromising effectiveness in limiting the spread of fake accounts.Source: Computer networks (1999) 95 (2016): 97–114. doi:10.1016/j.comnet.2015.12.005
DOI: 10.1016/j.comnet.2015.12.005

See at: Computer Networks Restricted | Computer Networks Restricted | Computer Networks Restricted | Computer Networks Restricted | Computer Networks Restricted | Computer Networks Restricted | CNR ExploRA Restricted | Computer Networks Restricted


2016 Report Open Access OPEN

ProgettISTI 2016
Banterle F., Barsocchi P., Candela L., Carlini E., Carrara F., Cassarà P., Ciancia V., Cintia P., Dellepiane M., Esuli A., Gabrielli L., Germanese D., Girardi M., Girolami M., Kavalionak H., Lonetti F., Lulli A., Moreo Fernandez A., Moroni D., Nardini F. M., Monteiro De Lira V. C., Palumbo F., Pappalardo L., Pascali M. A., Reggianini M., Righi M., Rinzivillo S., Russo D., Siotto E., Villa A.
ProgettISTI research project grant is an award for members of the Institute of Information Science and Technologies (ISTI) to provide support for innovative, original and multidisciplinary projects of high quality and potential. The choice of theme and the design of the research are entirely up to the applicants yet (i) the theme must fall under the ISTI research topics, (ii) the proposers of each project must be of diverse laboratories of the Institute and must contribute different expertise to the project idea, and (iii) project proposals should have a duration of 12 months. This report documents the procedure, the proposals and the results of the 2016 edition of the award. In this edition, ten project proposals have been submitted and three of them have been awarded.Source: ISTI Technical reports, 2016

See at: ISTI Repository Open Access | CNR ExploRA Open Access


2016 Conference object Restricted

NATCloud: Cloud-assisted NAT-traversal service
Kavalionak H., Payberah A. H., Dowling J., Montresor A.
Although over the last decade large efforts have been done to design efficient peer-to-peer (P2P) protocols, very few of them have taken into account the problem of firewalls and network address translators (NAT). Most of the existing P2P systems do not work properly when a high percentage of nodes are behind NAT. While a few P2P systems tackled the NAT problem, all of them employ third party nodes to establish a connection towards nodes behind NAT, and these may become bottlenecks, menacing the health of the entire system. A possible solution to this problem is to rent ex- tra resources from the cloud. This paper presents NATCLOUD, a cloud-assisted NAT-traversal service, where rented cloud resources are added on demand to the overlay, as third party nodes, to help other nodes to make connections to nodes behind NAT. We show the feasibility of integrating our approach with existing gossip-based peer sampling services and evaluate our solution by simulations, conducting extensive experiments under different network conditions.Source: 31st Annual ACM Symposium on Applied Computing, SAC 2016, pp. 508–513, Pisa, Italy, 04-08/04/2016
DOI: 10.1145/2851613.2851640

See at: Unknown Repository Restricted | Unknown Repository Restricted | Unknown Repository Restricted | dl.acm.org Restricted | Unknown Repository Restricted | Unknown Repository Restricted | Unknown Repository Restricted | CNR ExploRA Restricted | Unknown Repository Restricted | Unknown Repository Restricted


2015 Conference object Restricted

DICE: A distributed protocol for camera-aided video surveillance
Kavalionak H., Gennaro C., Amato G., Meghini C.
Video surveillance systems have become an indispensable tool for the security and organization of public and private areas. Most of the current commercial video surveillance systems rely on a classical client/server architecture to perform person and object recognition. In order to support the more complex and advanced video surveillance systems proposed in the last years, companies are required to invest resources in order to maintain the servers dedicated to the recognition tasks. In this work we propose a novel distributed protocol that exploits the computational capabilities of the surveillance devices (i.e. cameras) to perform the recognition of the person. The cameras fall back to a centralized server if their hardware capabilities are not enough to perform the recognition. By means of simulations, we show that our algorithm is able to reduce up to 50% the load of the server with no negative impact on the quality of the surveillance service.Source: IEEE International Conference on Computer and Information Technology; Ubiquitous Computing and Communications; Dependable, Autonomic and Secure Computing; Pervasive Intelligence and Computing, pp. 477–484, Liverpool, UK, 26-28/10/2015
DOI: 10.1109/CIT/IUCC/DASC/PICOM.2015.68
DOI: 10.1109/cit/iucc/dasc/picom.2015.68

See at: Unknown Repository Restricted | Unknown Repository Restricted | Unknown Repository Restricted | ieeexplore.ieee.org Restricted | CNR ExploRA Restricted | Unknown Repository Restricted