{"id":{"repo_id":"unm","oai_identifier":"oai:digitalrepository.unm.edu:ece_etds-1107"},"canonical_url":"https://search.dev.ndltd.org/etd/unm/oai:digitalrepository.unm.edu:ece_etds-1107","repository":{"repo_id":"unm","name":"University of New Mexico","base_url":"https://digitalrepository.unm.edu/do/oai/"},"display":{"title":"Analysis of Performance and Power Aspects of Hypervisors in Soft Real-Time Embedded Systems","abstract":"The exponential growth of malware designed to attack soft real-time embedded systems has necessitated solutions to secure these systems. Hypervisors are a solution, but the overhead imposed by them needs to be quantitatively understood. Experiments were conducted to quantify the overhead hypervisors impose on soft real-time embedded systems. A soft real-time computer vision algorithm was executed, with average and worst-case execution times measured as well as the average power consumption. These experiments were conducted with two hypervisors and a control configuration. The experiments showed that each hypervisor imposed differing amounts of overhead, with one achieving near native performance and the other noticeably impacting the performance of the system.","abstract_html":"The exponential growth of malware designed to attack soft real-time embedded systems has necessitated solutions to secure these systems. Hypervisors are a solution, but the overhead imposed by them needs to be quantitatively understood. Experiments were conducted to quantify the overhead hypervisors impose on soft real-time embedded systems. A soft real-time computer vision algorithm was executed, with average and worst-case execution times measured as well as the average power consumption. These experiments were conducted with two hypervisors and a control configuration. The experiments showed that each hypervisor imposed differing amounts of overhead, with one achieving near native performance and the other noticeably impacting the performance of the system.","abstract_has_math":false,"creators":["Guthrie, John"],"institution":null,"degree_name":"Computer Engineering","degree_level":"Thesis","degree_discipline":"Electrical and Computer Engineering","degree_department":null,"school":null,"contributors":["Heileman, Gregory","Lamb, Chris","Shu, Wennie"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2016,"date_issued":"2016-08-25T07:00:00Z","date_published":"2016-08-25T07:00:00Z","updated_at":"2026-07-24T05:27:19Z","subjects":["hypervisor","virtualization","soft real-time","Docker","KVM","embedded","performance","power"],"languages":["English"],"rights":[],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://digitalrepository.unm.edu/ece_etds/108","outbound_label":"Repository record","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Heileman, Gregory","Lamb, Chris","Shu, Wennie"]},{"key":"dc:creator","label":"Author","values":["Guthrie, John"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"thesis:degree_discipline","label":"Discipline","values":["Electrical and Computer Engineering"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Thesis","Masters"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Computer Engineering"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["hypervisor","virtualization","soft real-time","Docker","KVM","embedded","performance","power"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["English"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://digitalrepository.unm.edu/ece_etds/108"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["The exponential growth of malware designed to attack soft real-time embedded systems has necessitated solutions to secure these systems. Hypervisors are a solution, but the overhead imposed by them needs to be quantitatively understood. Experiments were conducted to quantify the overhead hypervisors impose on soft real-time embedded systems. A soft real-time computer vision algorithm was executed, with average and worst-case execution times measured as well as the average power consumption. These experiments were conducted with two hypervisors and a control configuration. The experiments showed that each hypervisor imposed differing amounts of overhead, with one achieving near native performance and the other noticeably impacting the performance of the system."]},{"key":"dc:title","label":"Title","values":["Analysis of Performance and Power Aspects of Hypervisors in Soft Real-Time Embedded Systems"]}]}],"canonical_facts":{"dc:contributor":["Heileman, Gregory","Lamb, Chris","Shu, Wennie"],"dc:creator":["Guthrie, John"],"dc:description.abstract":["The exponential growth of malware designed to attack soft real-time embedded systems has necessitated solutions to secure these systems. Hypervisors are a solution, but the overhead imposed by them needs to be quantitatively understood. Experiments were conducted to quantify the overhead hypervisors impose on soft real-time embedded systems. A soft real-time computer vision algorithm was executed, with average and worst-case execution times measured as well as the average power consumption. These experiments were conducted with two hypervisors and a control configuration. The experiments showed that each hypervisor imposed differing amounts of overhead, with one achieving near native performance and the other noticeably impacting the performance of the system."],"dc:identifier":["https://digitalrepository.unm.edu/ece_etds/108"],"dc:language":["English"],"dc:subject":["hypervisor","virtualization","soft real-time","Docker","KVM","embedded","performance","power"],"dc:title":["Analysis of Performance and Power Aspects of Hypervisors in Soft Real-Time Embedded Systems"],"thesis:degree_discipline":["Electrical and Computer Engineering"],"thesis:degree_level":["Thesis","Masters"],"thesis:degree_name":["Computer Engineering"]},"updated_at":"2026-07-24T05:27:19Z"}