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        iPOJO-based Middleware Solutions for Self-Reconfiguration and Self-Optimization

        ( Paolo Bellavista ),( Antonio Corradi ),( Damiano Fontana ),( Stefano Monti ) 한국인터넷정보학회 2011 KSII Transactions on Internet and Information Syst Vol.5 No.8

        In recent years, ubiquitous and pervasive scenarios have emerged as a complex ecosystem where differentiated software/hardware components interoperate wirelessly and seamlessly. The goal is to enable users to continuously access services and contents, and to always get the best out of their current environment and available resources. In such dynamic and flexible scenarios, the need emerges for flexible and general solutions for continuous runtime self-reconfiguration and self-optimization of ubiquitous support software systems. This paper proposes a fully reconfigurable middleware approach that aims at reconfiguring complex software systems made up of heterogeneous off-the-shelf components from both functional and non-functional perspectives. Our middleware can also extend already existing and non-reconfigurable middleware/applications in an easy and flexible way, with no need to re-design them. The proposed design principles have been practically applied to the implementation of a runtime self-reconfigurable middleware called Off-The-Shelf Ready To Go (OTS-RTG), implemented on top of iPOJO. The reported experimental results both exhibit a limited overhead and show the wide applicability of the proposed solution to many application scenarios, including complex, industrial, Enterprise Service Bus-based ones.

      • The MUM Middleware to Counteract IEEE 802.11 Performance Anomaly in Context-aware Multimedia Provisioning

        Paolo Bellavista,Antonio Corradi,Luca Foschini 보안공학연구지원센터 2007 International Journal of Multimedia and Ubiquitous Vol.2 No.2

        Multimedia provisioning over Wi-Fi networks is a complex task that should consider also novel issues stemming from the specific behavior of IEEE 802.11 protocols. In particular, we claim the need for visibility of context data about the IEEE 802.11 performance anomaly, i.e., the situation where even a single node located at the borders of the coverage area of a Wi-Fi access point produces a relevant degradation in the connectivity quality of all other nodes in the area. The paper proposes a novel application-level middleware that counteracts IEEE 802.11 anomaly without imposing any modification in standard Wi-Fi protocols, thus permitting to maintain the current wide base of installed equipment. Our middleware portably detects anomaly situations via decentralized standard mechanisms available at clients; anomaly awareness is used to promptly react with application-level management operations (flow quality downscaling and traffic shaping) that both preserve the goodput at nodes in well-covered areas and minimize quality degradations at clients generating the anomaly. The reported experimental results point out the feasibility of application-level middleware approaches also in the challenging multimedia area.

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        Measuring the Impact of COVID-19 Restrictions on Mobility: A Real Case Study from Italy

        Claudia Cavallaro,Armir Bujari,Luca Foschini,Giuseppe Di Modica,Paolo Bellavista 한국통신학회 2021 Journal of communications and networks Vol.23 No.5

        When COVID-19 first struck the provinces of NorthernItaly in early 2020 (especially in Lombardy and in Emilia-Romagna), the conditions there made it a perfect storm. Thevirus outbreak spread with an unusual violence (in the periodfrom late February to April 2020), with a catastrophic toll interms of human deaths. Taken by surprise, Italy mandated acomplete nation-wide lockdown, successively resorting to ministerialdecrees alleviating and postponing the restrictions. Now more than ever, there is an increased awareness onICT used to combat the pandemic. In this article, we presenta quantitative analysis evidencing the impact of restrictions onmobility. To this end, we rely on a vehicular mobility datasetconfined in the downtown area of Bologna, Italy. Pursuingthe objective, we propose a modified version of a state-of-theartdata mining algorithm, allowing us to efficiently identifyand quantify mobility flows. The proposal, if combined withadditional data sources, could allow for a fine-grained and timelydecision making, combating the pandemic.

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