{"id":12582,"date":"2023-07-12T15:39:45","date_gmt":"2023-07-12T13:39:45","guid":{"rendered":"https:\/\/new.sano.science\/?post_type=research&#038;p=12582"},"modified":"2024-01-05T13:58:08","modified_gmt":"2024-01-05T12:58:08","slug":"cloud-computing-infrastructure-for-the-vph-community","status":"publish","type":"research","link":"https:\/\/sano.science\/research\/cloud-computing-infrastructure-for-the-vph-community\/","title":{"rendered":"Cloud computing infrastructure for the VPH community\u00a0"},"content":{"rendered":"\n<h2 class=\"wp-block-heading eplus-wrapper\">Nowakowski, Piotr; Bubak, Marian; Barty\u0144ski, Tomasz; Guba\u0142a, Tomasz; Harce\u017clak, Daniel; Kasztelnik, Marek; Malawski, Maciej; Meizner, Jan<\/h2>\n\n\n\n<div style=\"height:50px\" aria-hidden=\"true\" class=\"wp-block-spacer eplus-wrapper\"><\/div>\n\n\n\n<p class=\" eplus-wrapper\">As virtualization technologies mature and become ever more widespread, cloud computing has emerged as a promising paradigm for e-science. In order to facilitate successful application of cloud computing in scientific research \u2013 particularly in a domain as security-minded as medical research \u2013 several technical challenges need to be addressed. This paper reports on the successful deployment and utilization of a cloud computing platform for the Virtual Physiological Human (VPH) research community, originating in the VPH-Share project and continuing beyond the end of this project. The platform tackles technical issues involved in porting existing desktop applications to the cloud environment and constitutes a uniform research space where application services can be developed, stored, accessed and shared using a variety of computational infrastructures. The paper also presents examples of application workflows which make use of the presented infrastructure \u2013 both internal and external to the VPH community.<\/p>\n\n\n\n<div style=\"height:50px\" aria-hidden=\"true\" class=\"wp-block-spacer eplus-wrapper\"><\/div>\n\n\n\n\t\n    \n        \n\t\t\t<a href=\"https:\/\/dx.doi.org\/10.1016\/j.jocs.2017.06.012\" target=\"_blank\" rel= \"noopener noreferrer nofollow\" class=\"button primary \">\n\n\t\t\t\t<span>\n\t\t\t\t\tREAD HERE\n\t\t\t\t<\/span>\n\n\t\t\t<\/a>\n\n        \n    \n","protected":false},"excerpt":{"rendered":"<p>In: Journal of Computational Science, vol. 24, pp. 169\u2013179, 2018, ISSN: 18777503.<\/p>\n","protected":false},"featured_media":0,"template":"","research_type":[8],"research_team":[16],"class_list":["post-12582","research","type-research","status-publish","hentry","research_type-publications","research_team-extreme-scale-data-and-computing"],"yoast_head":"<!-- This site is optimized with the Yoast SEO Premium plugin v27.4 (Yoast SEO v27.4) - 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