Reference number : GC-2017-Q1-02743, amendment number : , agreement type : G, recipient legal name : Lu, Ning (Thompson Rivers University), recipient country : CA, recipient province : nan, recipient city : British Columbia|Colombie-Britannique, recipient postal code : nan, program name english : Discovery Grants Program - Individual, program name french : Programme de subventions à la découverte - individuelles, program purpose english : Internet of Vehicles (IoV) is envisioned to enable next-generation vehicular applications, such as preventive maintenance/diagnostics, feedback-based routing, speed and fuel management, and advanced active safety, among others. As a mission-critical system, IoV is required to guarantee the Quality of Service (QoS) requirements of various services/applications, especially for real-time services with deadline constraints either at packet level or application level. Serving real-time applications is therefore considered as a key component of IoV and many other cyber-physical systems. Despite significant research effort on IoV technology, a mature science to support real-time applications of high-confidence IoV is still missing, and traditional analysis tools/algorithms are unable to cope with the full complexity of IoV or adequately predict system behavior, due to great challenges that arise from the high mobility and intrinsic heterogeneity of such systems. 
 
The long-term goal of this research program is to advance the development of efficient and low-complexity scheduling algorithms for delivering heterogeneous services in IoV. The short-term objectives in the next five years are to model and characterize the impact of vehicle mobility on real-time scheduling, to develop a rigorous and systematic framework for design scheduling policies that can achieve optimal performance, and to develop efficient real-time scheduling algorithms considering various engineering costs and constraints. 
 
A heterogeneous vehicular connectivity will be considered in this program, where vehicles are capable of connecting to cellular network base stations, Wi-Fi access points, and other vehicles. The proposed research includes three thrusts: 
(1) Intra-cell scheduling: the development of throughput/utility-optimal scheduling algorithms for enhancing today&rsquo;s cellular network or for next-generation cellular network to serve location-specific IoV services in a real-time manner; 
(2) Network-wide scheduling: the development of optimal distributed scheduling algorithms for packets with hard deadlines in a vehicular ad hoc network, taking account of both the long-term and short-term guarantees, and flow-level dynamics due to vehicle mobility; 
(3) Application-level scheduling: the development of optimal application-level scheduling algorithms in favor of cellular traffic steering subject to application delay constraints. 
 
It is anticipated that the proposed research program will generate significant scientific, technological, and social impacts in providing the scientific research foundation for supporting real-time applications in IoV. This program will also contribute to the training of highly qualified personnel, providing the trainees with solid knowledge and research background in R&amp;D of IoV, and enabling them to contribute to Canadian high technology industry., program purpose french : Internet of Vehicles (IoV) is envisioned to enable next-generation vehicular applications, such as preventive maintenance/diagnostics, feedback-based routing, speed and fuel management, and advanced active safety, among others. As a mission-critical system, IoV is required to guarantee the Quality of Service (QoS) requirements of various services/applications, especially for real-time services with deadline constraints either at packet level or application level. Serving real-time applications is therefore considered as a key component of IoV and many other cyber-physical systems. Despite significant research effort on IoV technology, a mature science to support real-time applications of high-confidence IoV is still missing, and traditional analysis tools/algorithms are unable to cope with the full complexity of IoV or adequately predict system behavior, due to great challenges that arise from the high mobility and intrinsic heterogeneity of such systems. 
 
The long-term goal of this research program is to advance the development of efficient and low-complexity scheduling algorithms for delivering heterogeneous services in IoV. The short-term objectives in the next five years are to model and characterize the impact of vehicle mobility on real-time scheduling, to develop a rigorous and systematic framework for design scheduling policies that can achieve optimal performance, and to develop efficient real-time scheduling algorithms considering various engineering costs and constraints. 
 
A heterogeneous vehicular connectivity will be considered in this program, where vehicles are capable of connecting to cellular network base stations, Wi-Fi access points, and other vehicles. The proposed research includes three thrusts: 
(1) Intra-cell scheduling: the development of throughput/utility-optimal scheduling algorithms for enhancing today&rsquo;s cellular network or for next-generation cellular network to serve location-specific IoV services in a real-time manner; 
(2) Network-wide scheduling: the development of optimal distributed scheduling algorithms for packets with hard deadlines in a vehicular ad hoc network, taking account of both the long-term and short-term guarantees, and flow-level dynamics due to vehicle mobility; 
(3) Application-level scheduling: the development of optimal application-level scheduling algorithms in favor of cellular traffic steering subject to application delay constraints. 
 
It is anticipated that the proposed research program will generate significant scientific, technological, and social impacts in providing the scientific research foundation for supporting real-time applications in IoV. This program will also contribute to the training of highly qualified personnel, providing the trainees with solid knowledge and research background in R&amp;D of IoV, and enabling them to contribute to Canadian high technology industry., agreement title english : Real-Time Scheduling for Internet of Vehicles, agreement title french : Real-Time Scheduling for Internet of Vehicles, agreement number : RGPIN, agreement value : 120000.0, agreement start date : 2017-05-10, agreement end date : nan, description english : nan, description french : nan, expected results english : nan, expected results french : nan, additional information english : Grant or Award spanning more than one fiscal year. (2017-2018 to 2022-2023), additional information french : Subvention ou bourse octroyée s'appliquant à plus d'un exercice financier. (2017-2018 à 2022-2023), owner organization : nserc-crsng, owner organization title : Natural Sciences and Engineering Research Council of Canada | Conseil de recherches en sciences naturelles et en génie du Canada