{"id":2296,"date":"2021-05-17T10:25:46","date_gmt":"2021-05-17T10:25:46","guid":{"rendered":"https:\/\/dev.algolysis.eu\/test\/?post_type=research_project&#038;p=2296"},"modified":"2024-09-03T20:05:30","modified_gmt":"2024-09-03T20:05:30","slug":"prefail","status":"publish","type":"research_project","link":"https:\/\/dev.algolysis.eu\/test\/index.php\/research-project\/prefail\/","title":{"rendered":"PREFAIL"},"excerpt":{"rendered":"<p>As the Digital Transformation of Europe, and the rest of the world, is rapidly picking up pace, the underlying physical infrastructure is similarly expanding to keep up with demand generated by over 2 billion connected computers and more than 30 billion smartphones, wearables and IoT devices. Nevertheless, Internet applications and services remain prone to inevitable hardware failures, that lead to data losses and increased maintenance costs. The primary problem lies with the cost of implementing data redundancy by constantly adding expensive hardware to cater to the needs of traditional data replication approaches (e.g. by always keeping copies of a file on multiple servers).<\/p>\n<p>With the assistance of an Innovation Associate specializing in Machine Learning, Algolysis Ltd aspires to extend its cloud-based storage device monitoring service (DriveNest \u2013 www.drivenest.com) with a robust state-of-the-art failure prediction engine. Reliably identifying soon-to-fail storage devices can be a transformative capability across the ICT sector, as a range of proactive data management and mitigation services can be built on top.\u00a0<\/p>\n","protected":false},"featured_media":960,"template":"","project_funding_agency":[48],"project_partner":[],"project_type":[],"research_area":[47,46],"class_list":["post-2296","research_project","type-research_project","status-publish","has-post-thumbnail","hentry","project_funding_agency-horizon-2020","research_area-ds","research_area-ml"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v25.3.1 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>PREFAIL - Algolysis Ltd<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/dev.algolysis.eu\/test\/index.php\/research-project\/prefail\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"PREFAIL - Algolysis Ltd\" \/>\n<meta property=\"og:description\" content=\"As the Digital Transformation of Europe, and the rest of the world, is rapidly picking up pace, the underlying physical infrastructure is similarly expanding to keep up with demand generated by over 2 billion connected computers and more than 30 billion smartphones, wearables and IoT devices. Nevertheless, Internet applications and services remain prone to inevitable hardware failures, that lead to data losses and increased maintenance costs. The primary problem lies with the cost of implementing data redundancy by constantly adding expensive hardware to cater to the needs of traditional data replication approaches (e.g. by always keeping copies of a file on multiple servers).  With the assistance of an Innovation Associate specializing in Machine Learning, Algolysis Ltd aspires to extend its cloud-based storage device monitoring service (DriveNest \u2013 www.drivenest.com) with a robust state-of-the-art failure prediction engine. Reliably identifying soon-to-fail storage devices can be a transformative capability across the ICT sector, as a range of proactive data management and mitigation services can be built on top.\u00a0\" \/>\n<meta property=\"og:url\" content=\"https:\/\/dev.algolysis.eu\/test\/index.php\/research-project\/prefail\/\" \/>\n<meta property=\"og:site_name\" content=\"Algolysis Ltd\" \/>\n<meta property=\"article:modified_time\" content=\"2024-09-03T20:05:30+00:00\" \/>\n<meta property=\"og:image\" content=\"https:\/\/dev.algolysis.eu\/test\/wp-content\/uploads\/2023\/09\/prefail_logo_v1.3-768x532-1.png\" \/>\n\t<meta property=\"og:image:width\" content=\"768\" \/>\n\t<meta property=\"og:image:height\" content=\"532\" \/>\n\t<meta property=\"og:image:type\" content=\"image\/png\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:label1\" content=\"Est. reading time\" \/>\n\t<meta name=\"twitter:data1\" content=\"1 minute\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\/\/schema.org\",\"@graph\":[{\"@type\":\"WebPage\",\"@id\":\"https:\/\/dev.algolysis.eu\/test\/index.php\/research-project\/prefail\/\",\"url\":\"https:\/\/dev.algolysis.eu\/test\/index.php\/research-project\/prefail\/\",\"name\":\"PREFAIL - Algolysis Ltd\",\"isPartOf\":{\"@id\":\"https:\/\/dev.algolysis.eu\/test\/#website\"},\"primaryImageOfPage\":{\"@id\":\"https:\/\/dev.algolysis.eu\/test\/index.php\/research-project\/prefail\/#primaryimage\"},\"image\":{\"@id\":\"https:\/\/dev.algolysis.eu\/test\/index.php\/research-project\/prefail\/#primaryimage\"},\"thumbnailUrl\":\"https:\/\/dev.algolysis.eu\/test\/wp-content\/uploads\/2023\/09\/prefail_logo_v1.3-768x532-1.png\",\"datePublished\":\"2021-05-17T10:25:46+00:00\",\"dateModified\":\"2024-09-03T20:05:30+00:00\",\"breadcrumb\":{\"@id\":\"https:\/\/dev.algolysis.eu\/test\/index.php\/research-project\/prefail\/#breadcrumb\"},\"inLanguage\":\"en-US\",\"potentialAction\":[{\"@type\":\"ReadAction\",\"target\":[\"https:\/\/dev.algolysis.eu\/test\/index.php\/research-project\/prefail\/\"]}]},{\"@type\":\"ImageObject\",\"inLanguage\":\"en-US\",\"@id\":\"https:\/\/dev.algolysis.eu\/test\/index.php\/research-project\/prefail\/#primaryimage\",\"url\":\"https:\/\/dev.algolysis.eu\/test\/wp-content\/uploads\/2023\/09\/prefail_logo_v1.3-768x532-1.png\",\"contentUrl\":\"https:\/\/dev.algolysis.eu\/test\/wp-content\/uploads\/2023\/09\/prefail_logo_v1.3-768x532-1.png\",\"width\":768,\"height\":532},{\"@type\":\"BreadcrumbList\",\"@id\":\"https:\/\/dev.algolysis.eu\/test\/index.php\/research-project\/prefail\/#breadcrumb\",\"itemListElement\":[{\"@type\":\"ListItem\",\"position\":1,\"name\":\"Home\",\"item\":\"https:\/\/dev.algolysis.eu\/test\/\"},{\"@type\":\"ListItem\",\"position\":2,\"name\":\"Research Projects\",\"item\":\"https:\/\/dev.algolysis.eu\/test\/index.php\/research-project\/\"},{\"@type\":\"ListItem\",\"position\":3,\"name\":\"PREFAIL\"}]},{\"@type\":\"WebSite\",\"@id\":\"https:\/\/dev.algolysis.eu\/test\/#website\",\"url\":\"https:\/\/dev.algolysis.eu\/test\/\",\"name\":\"Algolysis Ltd\",\"description\":\"Research-IT-Software\",\"publisher\":{\"@id\":\"https:\/\/dev.algolysis.eu\/test\/#organization\"},\"potentialAction\":[{\"@type\":\"SearchAction\",\"target\":{\"@type\":\"EntryPoint\",\"urlTemplate\":\"https:\/\/dev.algolysis.eu\/test\/?s={search_term_string}\"},\"query-input\":{\"@type\":\"PropertyValueSpecification\",\"valueRequired\":true,\"valueName\":\"search_term_string\"}}],\"inLanguage\":\"en-US\"},{\"@type\":\"Organization\",\"@id\":\"https:\/\/dev.algolysis.eu\/test\/#organization\",\"name\":\"Algolysis Ltd\",\"url\":\"https:\/\/dev.algolysis.eu\/test\/\",\"logo\":{\"@type\":\"ImageObject\",\"inLanguage\":\"en-US\",\"@id\":\"https:\/\/dev.algolysis.eu\/test\/#\/schema\/logo\/image\/\",\"url\":\"https:\/\/dev.algolysis.eu\/test\/wp-content\/uploads\/2023\/09\/cropped-algolysis-logo-white-png.png\",\"contentUrl\":\"https:\/\/dev.algolysis.eu\/test\/wp-content\/uploads\/2023\/09\/cropped-algolysis-logo-white-png.png\",\"width\":5889,\"height\":1792,\"caption\":\"Algolysis Ltd\"},\"image\":{\"@id\":\"https:\/\/dev.algolysis.eu\/test\/#\/schema\/logo\/image\/\"}}]}<\/script>\n<!-- \/ Yoast SEO plugin. -->","yoast_head_json":{"title":"PREFAIL - Algolysis Ltd","robots":{"index":"index","follow":"follow","max-snippet":"max-snippet:-1","max-image-preview":"max-image-preview:large","max-video-preview":"max-video-preview:-1"},"canonical":"https:\/\/dev.algolysis.eu\/test\/index.php\/research-project\/prefail\/","og_locale":"en_US","og_type":"article","og_title":"PREFAIL - Algolysis Ltd","og_description":"As the Digital Transformation of Europe, and the rest of the world, is rapidly picking up pace, the underlying physical infrastructure is similarly expanding to keep up with demand generated by over 2 billion connected computers and more than 30 billion smartphones, wearables and IoT devices. 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