[1] M De Lauro, G Giunta, and R Montella. Marine gis development: mapping the bay of naples. Sea Technology, 40(6):53–+, 1999.

[2] G Barone, P D’Ambra, D di Serafino, G Giunta, R Montella, A Murli, and A Riccio. An operational mesoscale air quality model for the campania region. Annali Istituto Universitario Navale, pages 179–189, 2000.

[3] G Giunta, R Montella, Patrizio Mariani, and A Riccio. Modeling and computational issues for air/water quality problems: A grid computing approach. Il nuovo cimento C, 28(2):215–224, 2005.

[4] Giulio Giunta, Patrizio Mariani, Raffaele Montella, and Angelo Riccio. ppom: A nested, scalable, parallel and fortran 90 implementation of the princeton ocean model. Environmental Modelling & Software, 22(1):117– 122, 2007.

[5] Raffaele Montella, Diana Di Luccio, Pasquale Troiano, Angelo Riccio, Al- ison Brizius, and Ian Foster. Wacomm: A parallel water quality com- munity model for pollutant transport and dispersion operational predic- tions. In 2016 12th International Conference on Signal-Image Technology & Internet-Based Systems (SITIS), pages 717–724. IEEE, 2016.

[6] Diana Di Luccio, Ardelio Galletti, Livia Marcellino, Angelo Riccio, Raf- faele Montella, and Alison Brizius. Some remarks about a community open source lagrangian pollutant transport and dispersion model. Procedia com- puter science, 113:490–495, 2017.

[7] Ardelio Galletti, Raffaele Montella, Livia Marcellino, Angelo Riccio, Diana Di Luccio, Alison Brizius, and Ian T Foster. Numerical and implemen- tation issues in food quality modeling for human diseases prevention. In HEALTHINF, pages 526–534, 2017.

[8] Giuliano Laccetti, Marco Lapegna, Valeria Mele, and Raffaele Montella. Relaxing the correctness conditions on concurrent data structures for mul- ticore cpus. a numerical case study. In International Conference on Parallel Processing and Applied Mathematics, pages 25–36. Springer, 2017.

[9] Guido Benassai, Diana Di Luccio, Maurizio Migliaccio, V Cordone, Gior- gio Budillon, and Raffaele Montella. High resolution remote sensing data for environmental modelling: Some case studies. In 2017 IEEE 3rd In- ternational Forum on Research and Technologies for Society and Industry (RTSI), pages 1–5. IEEE, 2017.

[10] Guido Benassai, Pietro Aucelli, Giorgio Budillon, Massimo De Stefano, Diana Di Luccio, Gianluigi Di Paola, Raffaele Montella, Luigi Mucerino, Mario Sica, and Micla Pennetta. Rip current evidence by hydrodynamic simulations, bathymetric surveys and uav observation. Natural Hazards and Earth System Sciences, 17(9):1493–1503, 2017.

[11] Giuliano Laccetti, Marco Lapegna, and Raffaele Montella. A scalable uni- fied model for dynamic data structures in message passing (clusters) and shared memory (multicore cpus) computing environments. In 2018 18th IEEE/ACM International Symposium on Cluster, Cloud and Grid Com- puting (CCGRID), pages 599–608. IEEE, 2018.

[12] Diana Di Luccio, Guido Benassai, Gianluigi Di Paola, Carmen Maria Rosskopf, Luigi Mucerino, Raffaele Montella, and Pasquale Contestabile. Monitoring and modelling coastal vulnerability and mitigation proposal for an archaeological site (kaulonia, southern italy). Sustainability, 10(6):2017, 2018.

[13] Guido Benassai, Diana Di Luccio, Luigi Mucerino, Gianluigi Di Paola, Car- men Maria Rosskopf, Giovanni Pugliano, Umberto Robustelli, and Raffaele Montella. Shoreline rotation analysis of embayed beaches in the central thyrrenian sea. In 2018 IEEE International Workshop on Metrology for the Sea; Learning to Measure Sea Health Parameters (MetroSea), pages 7–12. IEEE, 2018.

[14] E Chianese, A Galletti, G Giunta, TC Landi, L Marcellino, R Montella, and A Riccio. Spatiotemporally resolved ambient particulate matter con- centration by fusing observational data and ensemble chemical transport model simulations. Ecological Modelling, 385:173–181, 2018.

[15] Diana Di Luccio, Guido Benassai, Giorgio Budillon, Luigi Mucerino, Raf- faele Montella, and Eugenio Pugliese Carratelli. Wave run-up prediction and observation in a micro-tidal beach. Natural Hazards and Earth System Sciences, 18(11):2841–2857, 2018.

[16] Diana Di Luccio, Guido Benassai, Gianluigi Di Paola, Luigi Mucerino, Andrea Buono, Carmen Maria Rosskopf, Ferdinando Nunziata, Maurizio Migliaccio, Angelo Urciuoli, and Raffaele Montella. Shoreline rotation anal- ysis of embayed beaches by means of in situ and remote surveys. Sustain- ability, 11(3):725, 2019.

[17] Giovanni Pugliano, Umberto Robustelli, Diana Di Luccio, Luigi Mucerino, Guido Benassai, and Raffaele Montella. Statistical deviations in shoreline detection obtained with direct and remote observations. Journal of Marine Science and Engineering, 7(5):137, 2019.

[18] D. Di Luccio, G. Benassai, M. de Stefano, and R. Montella. Evidences of atmospheric pressure drop and sea level alteration in the ligurian sea. pages 22–27, 2020. cited By 0; Conference of 2019 IMEKO TC19 International Workshop on Metrology for the Sea: Learning to Measure Sea Health Pa- rameters, MetroSea 2019 ; Conference Date: 3 October 2019 Through 5 October 2019; Conference Code:157295.

D Di Luccio, G Benassai, L Mucerino, R Montella, F Conversano, G Pugliano, U Robustelli, and G Budillon. Characterization of beach run- up patterns in bagnoli bay during abbaco project. Chemistry and Ecology, 36(6):619–636, 2020.

[20] Marco Aldinucci, Giovanni Agosta, Antonio Andreini, Claudio A Ardagna, Andrea Bartolini, Alessandro Cilardo, Biagio Cosenza, Marco Danelutto, Roberto Esposito, William Fornaciari, et al. The italian research on hpc key technologies across eurohpc. In Proceedings of the 18th ACM International Conference on Computing Frontiers, pages 178–184, 2021.

[21] Giuliano Laccetti, Marco Lapegna, and Raffaele Montella. Toward a high- performance clustering algorithm for securing edge computing environ- ments. In 2022 22nd IEEE International Symposium on Cluster, Cloud and Internet Computing (CCGrid), pages 820–825. IEEE, 2022.

[22] Pasquale De Luca, Diana Di Luccio, Ardelio Galletti, Giulio Giunta, Livia Marcellino, and Raffaele Montella. Towards a gpu parallel software for envi- ronmental data fitting. In Proceedings of the 15th International Conference on PErvasive Technologies Related to Assistive Environments, pages 469– 472, 2022.

[23] Raffaele Montella. Development of a gt4-based resource broker service: an application to on-demand weather and marine forecasting. In International Conference on Grid and Pervasive Computing, pages 204–217. Springer, 2007.

[24] Raffaele Montella, Giulio Giunta, and Giuliano Laccetti. A grid computing based virtual laboratory for environmental simulations. In International Conference on Parallel Processing and Applied Mathematics, pages 951– 960. Springer, 2007.

[25] Raffaele Montella, Giuseppe Agrillo, Daniele Mastrangelo, and Milena Menna. A globus toolkit 4 based instrument service for environmental data acquisition and distribution. In Proceedings of the third international workshop on Use of P2P, grid and agents for the development of content networks, pages 21–28, 2008.

[26] Raffaele Montella, Giulio Giunta, and Angelo Riccio. An integrated classad- latent semantic indexing matchmaking algorithm for globus toolkit based computing grids. In International Conference on Parallel Processing and Applied Mathematics, pages 942–950. Springer, 2007.

[27] Raffaele Montella, Giulio Giunta, and Angelo Riccio. Using grid com- puting based components in on demand environmental data delivery. In Proceedings of the second workshop on Use of P2P, GRID and agents for the development of content networks, pages 81–86, 2007.

[28] Giulio Giunta, Giuliano Laccetti, and Raffaele Montella. Five dimension environmental data resource brokering on computational grids and scientific clouds. In 2008 IEEE Asia-Pacific Services Computing Conference, pages 81–88. IEEE, 2008.

[29] Raffaele Montella and Ian Foster. Using hybrid grid/cloud computing tech- nologies for environmental data elastic storage, processing, and provision- ing. In Handbook of Cloud Computing, pages 595–618. Springer, 2010.

[30] Raffaele Montella, Giulio Giunta, and Giuliano Laccetti. Multidimensional environmental data resource brokering on computational grids and scientific clouds. In Handbook of Cloud Computing, pages 475–492. Springer, 2010.

[31] Raffaele Montella, Livia Marcellino, Ardelio Galletti, Diana Di Luccio, Sokol Kosta, Giuliano Laccetti, and Giulio Giunta. Marine bathymetry pro- cessing through gpgpu virtualization in high performance cloud computing. Concurrency and Computation: Practice and Experience, 30(24):e4895, 2018.

[32] Kenneth K Azumah, Lene T Sørensen, Raffaele Montella, and Sokol Kosta. Process mining-constrained scheduling in the hybrid cloud. Concurrency and Computation: Practice and Experience, 33(4):e6025, 2021.

[33] Giulio Giunta, Raffaele Montella, Giuseppe Agrillo, and Giuseppe Coviello. A gpgpu transparent virtualization component for high performance com- puting clouds. In European Conference on Parallel Processing, pages 379– 391. Springer, 2010.

[34] Francisco Giunta, Raffaele Montella, Giuliano Laccetti, Florin Isaila, and F Blas. A gpu accelerated high performance cloud computing infrastructure for grid computing based virtual environmental laboratory. Advances in Grid Computing, pages 121–146, 2011.

[35] Raffaele Montella, Giuseppe Coviello, Giulio Giunta, Giuliano Laccetti, Florin Isaila, and Javier Garcia Blas. A general-purpose virtualization service for hpc on cloud computing: an application to gpus. In International Conference on Parallel Processing and Applied Mathematics, pages 740– 749. Springer, 2011.

[36] Roberto Di Lauro, Flora Giannone, Luigia Ambrosio, and Raffaele Mon- tella. Virtualizing general purpose gpus for high performance cloud comput- ing: an application to a fluid simulator. In 2012 IEEE 10th International Symposium on Parallel and Distributed Processing with Applications, pages 863–864. IEEE, 2012.

[37] Roberto Di Lauro, Francesca Lucarelli, and Raffaele Montella. Siaas- sensing instrument as a service using cloud computing to turn physical instrument into ubiquitous service. In 2012 IEEE 10th International Sym- posium on Parallel and Distributed Processing with Applications, pages 861–862. IEEE, 2012.

[38] Giuliano Laccetti, Raffaele Montella, Carlo Palmieri, and Valentina Pel- liccia. The high performance internet of things: using gvirtus to share high-end gpus with arm based cluster computing nodes. In International Conference on Parallel Processing and Applied Mathematics, pages 734– 744. Springer, 2013.

[39] Raffaele Montella, Giulio Giunta, and Giuliano Laccetti. Virtualizing high- end gpgpus on arm clusters for the next generation of high performance cloud computing. Cluster computing, 17(1):139–152, 2014.

[40] Raffaele Montella, Giulio Giunta, Giuliano Laccetti, Marco Lapegna, Carlo Palmieri, Carmine Ferraro, and Valentina Pelliccia. Virtualizing cuda en- abled gpgpus on arm clusters. In Parallel Processing and Applied Mathe- matics, pages 3–14. Springer, 2016.

[41] Lara L ́opez, Francisco Javier Nieto, Terpsichori-Helen Velivassaki, Sokol Kosta, Cheol-Ho Hong, Raffaele Montella, Iakovos Mavroidis, and Carles Fern ́andez. Heterogeneous secure multi-level remote acceleration service for low-power integrated systems and devices. Procedia Computer Science, 97:118–121, 2016.

[42] Raffaele Montella, Carmine Ferraro, Sokol Kosta, Valentina Pelliccia, and Giulio Giunta. Enabling android-based devices to high-end gpgpus. In In- ternational Conference on Algorithms and Architectures for Parallel Pro- cessing, pages 118–125. Springer, 2016.

[43] Ardelio Galletti, Livia Marcellino, Raffaele Montella, Vincenzo Santopi- etro, and Sokol Kosta. A virtualized software based on the nvidia cufft library for image denoising: performance analysis. Procedia computer sci- ence, 113:496–501, 2017.

[44] Livia Marcellino, Raffaele Montella, Sokol Kosta, Ardelio Galletti, Diana Di Luccio, Vincenzo Santopietro, Mario Ruggieri, Marco Lapegna, Luisa D’Amore, and Giuliano Laccetti. Using gpgpu accelerated interpolation algorithms for marine bathymetry processing with on-premises and cloud based computational resources. In International Conference on Parallel Processing and Applied Mathematics, pages 14–24. Springer, 2017.

[45] Raffaele Montella, Alfredo Petrosino, and Vincenzo Santopietro. Whoareyou (way): A mobile cuda powered picture id card recognition sys- tem. In International Conference on Image Analysis and Processing, pages 375–382. Springer, 2017.

[46] Raffaele Montella, Giulio Giunta, Giuliano Laccetti, Marco Lapegna, Carlo Palmieri, Carmine Ferraro, Valentina Pelliccia, Cheol-Ho Hong, Ivor Spence, and Dimitrios S Nikolopoulos. On the virtualization of cuda based gpu remoting on arm and x86 machines in the gvirtus framework. Inter- national Journal of Parallel Programming, 45(5):1142–1163, 2017.

[47] Raffaele Montella, Sokol Kosta, David Oro, Javier Vera, Carles Fern ́andez, Carlo Palmieri, Diana Di Luccio, Giulio Giunta, Marco Lapegna, and Giu- liano Laccetti. Accelerating linux and android applications on low-power devices through remote gpgpu offloading. Concurrency and Computation: Practice and Experience, 29(24):e4286, 2017.

[48] Dimitris Deyannis, Rafail Tsirbas, Giorgos Vasiliadis, Raffaele Montella, Sokol Kosta, and Sotiris Ioannidis. Enabling gpu-assisted antivirus pro- tection on android devices through edge offloading. In Proceedings of the 1st International Workshop on Edge Systems, Analytics and Networking, pages 13–18, 2018.

[49] Giuliano Laccetti, Marco Lapegna, Valeria Mele, and Raffaele Montella. An adaptive algorithm for high-dimensional integrals on heterogeneous cpu- gpu systems. Concurrency and Computation: Practice and Experience, 31(19):e4945, 2019.

[50] Antonio Mentone, Diana Di Luccio, Luca Landolfi, Sokol Kosta, and Raf- faele Montella. Cuda virtualization and remoting for gpgpu based acceler- ation offloading at the edge. In International Conference on Internet and Distributed Computing Systems, pages 414–423. Springer, 2019.

[51] Raffaele Montella, Diana Di Luccio, Ciro Giuseppe De Vita, Gennaro Mel- lone, Marco Lapegna, Giuliano Laccetti, Sokol Kosta, and Giulio Giunta. Enabling the cuda unified memory model in edge, cloud and hpc offloaded gpu kernels. In 2022 22nd IEEE International Symposium on Cluster, Cloud and Internet Computing (CCGrid), pages 834–841. IEEE, 2022.

[52] Isabella Ascione, Giulio Giunta, Patrizio Mariani, Raffaele Montella, and Angelo Riccio. A grid computing based virtual laboratory for environmental simulations. In European Conference on Parallel Processing, pages 1085– 1094. Springer, 2006.

[53] Quan Pham, Tanu Malik, Ian Foster, Roberto Di Lauro, and Raffaele Mon- tella. Sole: linking research papers with science objects. In International Provenance and Annotation Workshop, pages 203–208. Springer, 2012.

[54] Raffaele Montella, David Kelly, Wei Xiong, Alison Brizius, Joshua Elliott, Ravi Madduri, Ketan Maheshwari, Cheryl Porter, Peter Vilter, Michael Wilde, et al. Face-it: A science gateway for food security research. Con- currency and Computation: Practice and Experience, 27(16):4423–4436, 2015.

[55] Raffaele Montella, Alison Brizius, Diana Di Luccio, Cheryl Porter, Joshua Elliot, Ravi Madduri, David Kelly, Angelo Riccio, and Ian Foster. Applica- tions of the face-it portal and workflow engine for operational food quality prediction and assessment: Mussel farm monitoring in the bay of napoli, italy, 2016.

[56] Raffaele Montella, Alison Brizius, Diana Di Luccio, Cheryl Porter, Joshua Elliot, Ravi Madduri, David Kelly, Angelo Riccio, and Ian Foster. Using the face-it portal and workflow engine for operational food quality prediction and assessment: An application to mussel farms monitoring in the bay of napoli, italy. Future Generation Computer Systems, 2018.

[57] Raffaele Montella, Diana Di Luccio, and Sokol Kosta. Dagon*: Executing direct acyclic graphs as parallel jobs on anything. In 2018 IEEE/ACM Workflows in Support of Large-Scale Science (WORKS), pages 64–73. IEEE, 2018.

[58] Dante D S ́anchez-Gallegos, Diana Di Luccio, Jos ́e Luis Gonzalez-Compean, and Raffaele Montella. Internet of things orchestration using dagon* work- flow engine. In 2019 IEEE 5th World Forum on Internet of Things (WF- IoT), pages 95–100. IEEE, 2019.

[59] Dante D S ́anchez-Gallegos, Diana Di Luccio, JL Gonzalez-Compean, and Raffaele Montella. A microservice-based building block approach for sci- entific workflow engines: Processing large data volumes with dagonstar. In 2019 15th International Conference on Signal-Image Technology & Internet-Based Systems (SITIS), pages 368–375. IEEE, 2019.

[60] Miguel Santiago-Duran, JL Gonzalez-Compean, Andr ́e Brinkmann, Hugo G Reyes-Anastacio, Jesus Carretero, Raffaele Montella, and Gre- gorio Toscano Pulido. A gearbox model for processing large volumes of data by using pipeline systems encapsulated into virtual containers. Future Generation Computer Systems, 106:304–319, 2020.

[61] Dante Domizzi S ́anchez-Gallegos, Diana Di Luccio, Sokol Kosta, JL Gonzalez-Compean, and Raffaele Montella. An efficient pattern-based approach for workflow supporting large-scale science: The dagonstar expe- rience. Future Generation Computer Systems, 122:187–203, 2021.

[62] J Armando Barron-Lugo, Jose Luis Gonzalez-Compean, Jesus Carretero, Ivan Lopez-Arevalo, and Raffaele Montella. A novel transversal processing model to build environmental big data services in the cloud. Environmental Modelling & Software, 144:105173, 2021.

[63] Dante Domizzi Sanchez-Gallegos, JL Gonzalez-Compean, Jesus Carretero, Heidy Marin, Andrei Tchernykh, and Raffaele Montella. Puzzlemesh: A puzzle model to build mesh of agnostic services for edge-fog-cloud. IEEE Transactions on Services Computing, 2022.

[64] Raffaele Montella, Diana Di Luccio, Livia Marcellino, Ardelio Galletti, Sokol Kosta, Alison Brizius, and Ian Foster. Processing of crowd-sourced data from an internet of floating things. In Proceedings of the 12th Work- shop on Workflows in Support of Large-Scale Science, pages 1–11, 2017.

Raffaele Montella, Sokol Kosta, and Ian Foster. Dynamo: Distributed leisure yacht-carried sensor-network for atmosphere and marine data crowd- sourcing applications. In 2018 IEEE International Conference on Cloud Engineering (IC2E), pages 333–339. IEEE, 2018.

[66] Raffaele Montella, Mario Ruggieri, and Sokol Kosta. A fast, secure, reliable, and resilient data transfer framework for pervasive iot applications. In IEEE INFOCOM 2018-IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS), pages 710–715. IEEE, 2018.

[67] Raffaele Montella, Diana Di Luccio, Sokol Kosta, Giulio Giunta, and Ian Foster. Performance, resilience, and security in moving data from the fog to the cloud: the dynamo transfer framework approach. In International Conference on Internet and Distributed Computing Systems, pages 197– 208. Springer, 2018.

[68] Raffaele Montella, Diana Di Luccio, Livia Marcellino, Ardelio Galletti, Sokol Kosta, Giulio Giunta, and Ian Foster. Workflow-based automatic processing for internet of floating things crowdsourced data. Future Gen- eration Computer Systems, 94:103–119, 2019.

[69] Rosario Carbone, Raffaele Montella, Fabio Narducci, and Alfredo Pet- rosino. Deepnautilus: A deep learning based system for nautical engines’ live vibration processing. In International Conference on Computer Anal- ysis of Images and Patterns, pages 120–131. Springer, 2019.

[70] Raffaele Montella, Diana Di Luccio, Sokol Kosta, Aniello Castiglione, and Antonio Maratea. Security and storage issues in internet of floating things edge-cloud data movement. In International Conference on Parallel Pro- cessing and Applied Mathematics, pages 111–120. Springer, 2019.

[71] Diana Di Luccio, Angelo Riccio, Ardelio Galletti, Giuliano Laccetti, Marco Lapegna, Livia Marcellino, Sokol Kosta, and Raffaele Montella. Coastal marine data crowdsourcing using the internet of floating things: Improving the results of a water quality model. IEEE Access, 8:101209–101223, 2020.

[72] Diana Di Luccio, Sokol Kosta, Aniello Castiglione, Antonio Maratea, and Raffaele Montella. Vessel to shore data movement through the internet of floating things: A microservice platform at the edge. Concurrency and Computation: Practice and Experience, 33(4):e5988, 2021.

[73] Ivan Lopez-Arevalo, Jose Luis Gonzalez-Compean, Mariana Hinojosa- Tijerina, Cristhian Martinez-Rendon, Raffaele Montella, and Jose L Martinez-Rodriguez. A wot-based method for creating digital sentinel twins of iot devices. Sensors, 21(16):5531, 2021.

[74] Raffaele Montella, Diana Di Luccio, Angelo Ciaramella, and Ian Foster. Stormseeker: A machine-learning-based mediterranean storm tracer. In International Conference on Internet and Distributed Computing Systems, pages 444–456. Springer, 2019.

[75] Anirban Mandal and Raffaele Montella. Special issue on workflows in sup- port of large-scale science, 2021.

[76] Raffaele Montella, Giancarlo Fortino, and Eleni Karatza. Special issue on iot modeling and simulation in smart-anything computation at the edge, 2021.

[77] Sokol Kosta, Giuliano Laccetti, Marco Lapegna, Valeria Mele, and Raffaele Montella. Special issue on high-end heterogeneous architectures, method- ologies, and algorithms (hhama20), 2020.

[78] MC Buia, G Giunta, I Guala, G Iacono, R Montella, F Silvestre, and L Tib- erti. State of posidonia oceanica meadows around the sardinian coasts. In Proceedings of 7th International Conference on the Mediterranean Coastal Environment, Medcoast, volume 5, pages 431–439, 2005.

[79] Luisa D’Amore, Rossella Arcucci, Yi Li, Raffaele Montella, Andrew Moore, Luke Phillipson, and Ralf Toumi. Performance assessment of the incremen- tal strong constraints 4dvar algorithm in roms. In International Conference on Parallel Processing and Applied Mathematics, pages 48–57. Springer, 2017.

[80] Jakub Swacha, Jos ́e Carlos Paiva, Jos ́e Paulo Leal, Ricardo Queir ́os, Raf- faele Montella, and Sokol Kosta. Gedil—gamified education interoperability language. Information, 11(6):287, 2020.

[81] Jakub Swacha, Ricardo Queir ́os, Jos ́e Carlos Paiva, Jos ́e Paulo Leal, Sokol Kosta, and Raffaele Montella. A roadmap to gamify programming educa- tion. In 1st International Computer Programming Education Conference, ICPEC 2020, page 26. Schloss Dagstuhl-Leibniz-Zentrum fur Informatik GmbH, Dagstuhl Publishing, 2020.