{"id":11012,"date":"2013-12-04T23:48:50","date_gmt":"2013-12-04T21:48:50","guid":{"rendered":"http:\/\/hgpu.org\/?p=11012"},"modified":"2013-12-04T23:48:50","modified_gmt":"2013-12-04T21:48:50","slug":"gpu-based-multi-stream-analyzer-on-application-layer-for-service-oriented-router","status":"publish","type":"post","link":"https:\/\/hgpu.org\/?p=11012","title":{"rendered":"GPU-based Multi-stream Analyzer on Application Layer for Service-oriented Router"},"content":{"rendered":"<p>Service-oriented router (SoR) is a new router architecture for providing rich services to Internet users by utilizing useful information extracted from network traffic. In SoR, stream reconstruction and selection is a fundamental process for providing the services in the application layer. After real-time reconstruction of stream data, SoR used a software character string analyzer to extract important required information. One of the promised services is a router-level network intrusion detection system. Because a network consists of hundreds of thousands of data streams, achieving an intended throughput while analyzing these stream data is a critical problem. We propose an acceleration method of string matching based on a heterogeneous system consisting of a CPU and a graphics processing unit. In addition, we designed and implemented a task controller that improves the distribution of POSIX-thread-based processes so that string matching can be performed concurrently depending on the status of the string matching system.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Service-oriented router (SoR) is a new router architecture for providing rich services to Internet users by utilizing useful information extracted from network traffic. In SoR, stream reconstruction and selection is a fundamental process for providing the services in the application layer. After real-time reconstruction of stream data, SoR used a software character string analyzer to [&hellip;]<\/p>\n","protected":false},"author":351,"featured_media":0,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_jetpack_memberships_contains_paid_content":false,"footnotes":"","jetpack_publicize_message":"","jetpack_publicize_feature_enabled":true,"jetpack_social_post_already_shared":true,"jetpack_social_options":{"image_generator_settings":{"template":"highway","default_image_id":0,"font":"","enabled":false},"version":2}},"categories":[11,89,3],"tags":[1782,14,452,20,1306,476,206],"class_list":["post-11012","post","type-post","status-publish","format-standard","hentry","category-computer-science","category-nvidia-cuda","category-paper","tag-computer-science","tag-cuda","tag-heterogeneous-systems","tag-nvidia","tag-nvidia-geforce-gtx-680","tag-software-router","tag-string-matching"],"views":2257,"jetpack_publicize_connections":[],"jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/11012","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/users\/351"}],"replies":[{"embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=11012"}],"version-history":[{"count":0,"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/11012\/revisions"}],"wp:attachment":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=11012"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=11012"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=11012"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}