{"id":{"repo_id":"uoit","oai_identifier":"oai:ontariotechu.scholaris.ca:10155/1412"},"canonical_url":"https://search.dev.ndltd.org/etd/uoit/oai:ontariotechu.scholaris.ca:10155/1412","repository":{"repo_id":"uoit","name":"Ontario Institute of Technology","base_url":"https://ontariotechu.scholaris.ca/server/oai/request"},"display":{"title":"An energy-efficient periodic resource model for cyber-physical systems By Suzanne Elashri","abstract":"Cyber-Physical Systems (CPS), especially real-time systems, are subject to time constraints that should be met for the applications to run properly. The schedulability of workloads can be analyzed by determining the supply and demand bound functions (sbf & dbf) when the minimum resource availability (sbf) can satisfy the maximum possible resource demand (dbf) of the workload under a specific scheduling algorithm during a given time interval. Typical real-time systems are insufficient resource reservation by over-provisioning resources when resource supply is always higher than the workload demand. Energy efficiency considerations are required for resource reservations in real-time systems when calculating the optimum processor speed to ensure that the supply of resources is no less than the workload demand during any time intervals. Therefore, we explore an energy-efficient Dynamic Speed Scaling technique for CPS to efficiently estimate resource reservation and efficiently reduce energy consumption.","abstract_html":"Cyber-Physical Systems (CPS), especially real-time systems, are subject to time constraints that should be met for the applications to run properly. The schedulability of workloads can be analyzed by determining the supply and demand bound functions (sbf & dbf) when the minimum resource availability (sbf) can satisfy the maximum possible resource demand (dbf) of the workload under a specific scheduling algorithm during a given time interval. Typical real-time systems are insufficient resource reservation by over-provisioning resources when resource supply is always higher than the workload demand. Energy efficiency considerations are required for resource reservations in real-time systems when calculating the optimum processor speed to ensure that the supply of resources is no less than the workload demand during any time intervals. Therefore, we explore an energy-efficient Dynamic Speed Scaling technique for CPS to efficiently estimate resource reservation and efficiently reduce energy consumption.","abstract_has_math":false,"creators":["Elashri, Suzanne"],"institution":"University of Ontario Institute of Technology","degree_name":"Master of Applied Science (MASc)","degree_level":null,"degree_discipline":"Electrical and Computer Engineering","degree_department":null,"school":null,"contributors":[],"advisors":["Azim, Akramul"],"committee_chairs":[],"committee_members":[],"year":2021,"date_issued":"2021-08-01","date_published":"2021-08-01","updated_at":"2026-07-24T05:35:20Z","subjects":["Cyber-physical systems","Periodic resource model","Energy consumption","Delay-tolerant tasks"],"languages":["en"],"rights":[],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://hdl.handle.net/10155/1412","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.advisor","label":"Advisor","values":["Azim, Akramul"]},{"key":"dc:creator","label":"Author","values":["Elashri, Suzanne"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.accessioned","label":"Dc Date Accessioned","values":["2022-02-07T20:47:58Z","2022-03-29T16:46:11Z"]},{"key":"dc:date.available","label":"Dc Date Available","values":["2022-02-07T20:47:58Z","2022-03-29T16:46:11Z"]},{"key":"dc:date.issued","label":"Date","values":["2021-08-01"]},{"key":"dc:type","label":"Dc Type","values":["Thesis"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Electrical and Computer Engineering"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Master of Applied Science (MASc)"]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["University of Ontario Institute of Technology"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Cyber-physical systems","Periodic resource model","Energy consumption","Delay-tolerant tasks"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language.iso","label":"Language (ISO)","values":["en"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.uri","label":"Identifier URI","values":["https://hdl.handle.net/10155/1412"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["Cyber-Physical Systems (CPS), especially real-time systems, are subject to time constraints that should be met for the applications to run properly. The schedulability of workloads can be analyzed by determining the supply and demand bound functions (sbf & dbf) when the minimum resource availability (sbf) can satisfy the maximum possible resource demand (dbf) of the workload under a specific scheduling algorithm during a given time interval. Typical real-time systems are insufficient resource reservation by over-provisioning resources when resource supply is always higher than the workload demand. Energy efficiency considerations are required for resource reservations in real-time systems when calculating the optimum processor speed to ensure that the supply of resources is no less than the workload demand during any time intervals. Therefore, we explore an energy-efficient Dynamic Speed Scaling technique for CPS to efficiently estimate resource reservation and efficiently reduce energy consumption."]},{"key":"dc:title","label":"Title","values":["An energy-efficient periodic resource model for cyber-physical systems By Suzanne Elashri"]}]}],"canonical_facts":{"dc:contributor.advisor":["Azim, Akramul"],"dc:creator":["Elashri, Suzanne"],"dc:date.accessioned":["2022-02-07T20:47:58Z","2022-03-29T16:46:11Z"],"dc:date.available":["2022-02-07T20:47:58Z","2022-03-29T16:46:11Z"],"dc:date.issued":["2021-08-01"],"dc:description.abstract":["Cyber-Physical Systems (CPS), especially real-time systems, are subject to time constraints that should be met for the applications to run properly. The schedulability of workloads can be analyzed by determining the supply and demand bound functions (sbf & dbf) when the minimum resource availability (sbf) can satisfy the maximum possible resource demand (dbf) of the workload under a specific scheduling algorithm during a given time interval. Typical real-time systems are insufficient resource reservation by over-provisioning resources when resource supply is always higher than the workload demand. Energy efficiency considerations are required for resource reservations in real-time systems when calculating the optimum processor speed to ensure that the supply of resources is no less than the workload demand during any time intervals. Therefore, we explore an energy-efficient Dynamic Speed Scaling technique for CPS to efficiently estimate resource reservation and efficiently reduce energy consumption."],"dc:identifier.uri":["https://hdl.handle.net/10155/1412"],"dc:language.iso":["en"],"dc:subject":["Cyber-physical systems","Periodic resource model","Energy consumption","Delay-tolerant tasks"],"dc:title":["An energy-efficient periodic resource model for cyber-physical systems By Suzanne Elashri"],"dc:type":["Thesis"],"thesis:degree_discipline":["Electrical and Computer Engineering"],"thesis:degree_name":["Master of Applied Science (MASc)"],"thesis:institution_name":["University of Ontario Institute of Technology"]},"updated_at":"2026-07-24T05:35:20Z"}