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2021 Conference article Open Access OPEN

Latency Preserving Self-optimizing Placement at the Edge
Ferrucci L., Mordacchini M., Coppola M., Carlini E., Kavalionak H., Dazzi P.
The Internet is experiencing a fast expansion at its edges. The wide availability of heterogeneous resources at the Edge is pivotal in the definition and extension of traditional Cloud solutions toward supporting the development of new applications. However, the dynamic and distributed nature of these resources poses new challenges for the optimization of the behaviour of the system. New decentralized and self-organizing methods are needed to face the needs of the Edge/Cloud scenario and to optimize the exploitation of Edge resources. In this paper we propose a distributed and adaptive solution that reduces the number of replicas of application services that are executed throughout the system, all the while ensuring that the latency constraints of applications are met, thus allowing to also meet the end users' QoS requirements. Experimental evaluations through simulation show the effectiveness of the proposed approach.Source: FRAME'21 - 1st Workshop on Flexible Resource and Application Management on the Edge, Virtual Event, Sweden, 25/06/2021
DOI: 10.1145/3452369.3463815
Project(s): ACCORDION via OpenAIRE, ACCORDION via OpenAIRE

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


2021 Report Open Access OPEN

ACCORDION D3.1 - Edge infrastructure pool framework report (I)
Psomakelis E., Blasi L., Vailati A., Kavalionak H., Korontanis I., Huici F., Dazzi P.
This deliverable provides the first report summarizing the scientific advancements achieved during the project, by the WP3 tasks. The achievements, risks and challenges are presented both at a high level, presenting the outcome of the WP3 tasks (called ACCORDION Minicloud VIM) as a unified component, and at a lower level, presenting the components that comprise the ACCORDION Minicloud VIM. For each component we can clearly identify the progress through the first year of the project, the challenges and problems encountered and the plans for the second year of the project.Source: ISTI Project report, ACCORDION, D3.1, 2021
Project(s): ACCORDION via OpenAIRE

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


2021 Report Open Access OPEN

ACCORDION D3.2 - Edge infrastructure pool framework implementation (I)
Korontanis I., Psomakelis V., Kavalionak H., Di Girolamo M., Vailati A., Huici F., Dazzi P.
This document is the accompanying report documenting the software components that are released as part of ACCORDION Deliverable D3.2 and explains how to install and use them. The report includes the description of the first implementation provided by ACCORDION for the Edge infrastructure pool framework (or Edge minicloud), developed by the tasks inside WP3. The implemented minicloud model can include only resources located in a single site and typically owned by a single provider. The developed framework, representing one of the key innovations realized by ACCORDION, puts together the different components that altogether implement the functionalities requested to deploy and operate federated miniclouds inside the ACCORDION environment. It allows to locate and assign edge resources to the client applications of ACCORDION, ensuring they are duly registered, tracked, monitored and that the system is able to react whenever needed to ensure the quality of service to users of client applications. The framework implements the architectural guidelines and requirements set by WP2, will be further integrated with the higher (orchestration) layer components developed by WP4 and, once integrated, will run the Pilot use case applications proposed by WP6.Source: ISTI Project report, ACCORDION, D3.2, 2021
Project(s): ACCORDION via OpenAIRE

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


2021 Conference article Open Access OPEN

Impact of network topology on the convergence of decentralized federated learning systems
Kavalionak H., Carlini E., Dazzi P., Ferrucci L., Mordacchini M., Coppola M.
Federated learning is a popular framework that enables harvesting edge resources' computational power to train a machine learning model distributively. However, it is not always feasible or profitable to have a centralized server that controls and synchronizes the training process. In this paper, we consider the problem of training a machine learning model over a network of nodes in a fully decentralized fashion. In particular, we look for empirical evidence on how sensitive is the training process for various network characteristics and communication parameters. We present the outcome of several simulations conducted with different network topologies, datasets, and machine learning models.Source: ISCC 2021 - 26th IEEE Symposium on Computers and Communications, Athens, Greece, 05-08/09/2021
Project(s): TEACHING via OpenAIRE

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


2020 Conference article 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 article 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


2020 Report Open Access OPEN

ACCORDION - D2.2 State of the art report (I)
Korontanis I., Carlini E., Kavalionak H., Dazzi P., Psomakelis V., Blasi L., Nadir Z., Violos J., Toro A., Russo M., Fabregas E. M., Vasios G., Tserpes K., Zadtootaghaj S., Lipa B., Pateraki M., Di Girolamo M.
The present document is the result of the collaborative effort of all ACCORDION partners participating to Task 2.2. The document offers a review of the state of the art for a series of topics strictly related to the work performed in the ACCORDION project. There is actually a strict correlation between the topics analyzed in this document and the Tasks that are part of the three research Work Packages of ACCORDION (WP3, WP4, and WP5). The main part of this document is section 2, in which all the state of the art analysis results have been reported. Section 2 has a subsection for each of the topics researched in the project, which includes: a description of the objectives, a list of outcomes expected from the research work, and an analysis of the state of the art. Section 2.1 (Resource monitoring & characterization) reports on monitoring, characterization and classification of Edge resources, identifying Prometheus, TOSCA and the automatic creation of taxonomies, respectively, as the best solutions for each of the three fields. Section 2.2 (Resource indexing & discovery) focuses on discussing solutions and data structures for organizing data in Resource Discovery Services. Section 2.3 (Edge storage, availability, reliability and performance) presents the advantages and disadvantages of both block and object storage, and then discusses some solutions, identifying OpenStack and MinIO as the most promising ones, even if not completely suitable. Some open research issues are also summarized. Section 2.4 (Pooling Edge resources), after listing some orchestration challenges typical of Edge computing and the techniques to cope with them, reports on several solutions to be considered as possible baselines for the ACCORDION Minicloud. Section 2.5 (??-based network orchestration) first lists the main machine learning techniques, then explores both Federated Learning techniques and further evolutions such as Meta-Learning Framework and Multi-Agent Reinforcement Learning. Section 2.6 (Resilience policies & mechanisms over heterogeneous edge resources) starts by discriminating between reactive and proactive protection strategies and describing some of them. Then other Fault Tolerance approaches are explored both reported in the literature and adopted in common distributed computing frameworks (Openstack, Cloudstack, Kubernetes, Openshift, and Mesos). Finally techniques for movement behaviour and resource utilization prediction are analysed, with a particular focus on the the LSTM model for Neural Networks. The conclusion is that the most promising solution to efficiently adapt the deep learning topologies for the fault tolerance needs is the hyper parameter optimization approach. Section 2.7 (Techniques for secure Edge application development & deployment) offers an analysis of the most common types of security attacks (Distributed Denial-of-Service, Malware Injection, and Authentication-based attacks) and their related countermeasures, along with some threat modelling methods, while DevSecOps methods and tools are also described. Section 2.8 (Privacy preserving mechanisms) starts by analysing Machine Learning techniques with a focus on privacy preserving ones, and then lists a number of works analysing how cookie synchronization techniques adopted for web advertising can expose users to privacy leaks. Section 2.9 (Application model for automatic deployment / migration of components) looks for application description models suitable for ACCORDION, i.e. with a machine-processable syntax, able to represent resource capacity requirements, containerization, and recovery policies. Three available solutions, TOSCA, Juju charms and CAMP, are compared along with the projects that are using them. Furthermore, tools supporting the three above solutions are described, and works researching the interoperability among the solutions are also analysed. Section 2.10 (Modelling and assessing QoE for NextGen applications) reports on different types of objective models that can be used to estimate the Quality of Experience (QoE) perceived by users of multimedia applications, and about the latest ITU-T Recommendations on QoE models and methodologies that can be applied to Next Generation Applications. For the ACCORDION project it has been decided to follow the standardized approach to build models for QoE assessment of ACCORDION applications. Section 2.11 (DevOps tools to automate Edge applications' deployment) sets the context and reports the starting points for the evaluation of Continuous Integration and Continuous Deployment tools. The identified state-of-the art solutions are Jenkins for the CI/CD pipeline and Kubernetes as the runtime deployment environment. Section 2.12 (Collaborative VR), starting from the general requirements for Virtual Reality applications, reports considerations about the still limited power of the available HMDs and discusses the trade-offs conditioning the possibility to offload computation from the end devices to the Edge. Finally Section 2.13 (Resource federation models) describes the main features of the federation model proposed by the H2020 5GeX project and lists the additional constraints and issues raised by an Edge providers' federation, which have to be further investigated. Not all project's research Tasks have a related section in this document about their main topics, yet. Monitoring the State of the Art is an ongoing activity in ACCORDION, and the next version of this document foreseen in M22 will improve the State of the Art analysis by adding further details, covering more topics and reporting on possible new approaches that appeared in the meantime.Source: ISTI Project report, ACCORDION, D2.2, 2020
Project(s): ACCORDION via OpenAIRE

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


2020 Report Open Access OPEN

ACCORDION D2.3 - Architecture design (I)
Tserpes K., Kousiouris G., Xydis S., Korodanis I., Kafatari T., Dazzi P., Carlini E., Kavalionak H., Ferrucci L., Huici F., Fabregas E. M., Kourtellis N., Diego A. F., Violos I., Psomakelis E., Kami?ski M., Lipa B., Loven T., Gonzalez Rozad Y., Toro A., Russo M., Blasi L., Vailati A., Di Girolamo M., Zinelaabidine N., Ledwo? Z., Zadtootaghaj S., Pateraki M., Fotis S., Kallipolitis L., Vantolas S.
This deliverable provides an account of the work done for the specification of the ACCORDION ecosystem architecture, which is mainly comprised of two artefacts: the infrastructure to support the cloud-edge continuum and the platform to manage the resources and the applications hosted in that infrastructure. The main outcomes of the work described in this deliverable are: a) the definition of components that comprise the architecture as well as their interactions, and; b) the assignment of the implementation of those components to specific project Tasks and partners. The deliverable describes the process for reaching to those outcomes, starting with the delineation of the scope of the described artefacts and working down to their specifics. The main approach used is the analysis of the platform use case scenarios. In practice, we analyze the scenarios and extract the required functionality. Then we cluster and map this functionality to components. Finally, we schematically present the interactions of those components using block and sequence diagrams. These outcomes are then validated against the use case requirements, especially those linked to the applications operation itself. This is meant to provide a proof-of-concept that the ACCORDION architecture is able to support the ACCORDION applications.Source: ISTI Project report, ACCORDION, D2.3, 2020
Project(s): ACCORDION via OpenAIRE

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


2018 Conference article 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 | academic.microsoft.com Restricted | link.springer.com Restricted | link.springer.com Restricted | link.springer.com Restricted | CNR ExploRA Restricted | rd.springer.com Restricted


2017 Conference article 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

See at: academic.microsoft.com Restricted | arpi.unipi.it Restricted | dblp.uni-trier.de Restricted | ieeexplore.ieee.org Restricted | CNR ExploRA Restricted | xplorestaging.ieee.org Restricted


2016 Journal 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 | 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 article 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

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2015 Conference article 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

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