TY - JOUR
T1 - Energy-Aware Coded Caching Strategy Design with Resource Optimization for Satellite-UAV-Vehicle-Integrated Networks
AU - Gu, Shushi
AU - Sun, Xinyi
AU - Yang, Zhihua
AU - Huang, Tao
AU - Xiang, Wei
AU - Yu, Keping
N1 - Publisher Copyright:
© 2014 IEEE.
PY - 2022/4/15
Y1 - 2022/4/15
N2 - The Internet of Vehicles (IoV) can offer safe and comfortable driving experience, by the enhanced advantages of space-air-ground-integrated networks (SAGINs), i.e., global seamless access, wide-area coverage, and flexible traffic scheduling. However, due to the huge popular traffic volume, limited cache/power resources, and the heterogeneous network infrastructures, the burden of backhaul link will be seriously enlarged, degrading the energy efficiency of IoV in SAGIN. In this article, to implement the popular content severing multiple vehicle users (VUs), we consider a cache-enabled satellite-UAV-vehicle-integrated network (CSUVIN), where the geosynchronous Earth orbit (GEO) satellite is regard as a cloud server, and unmanned aerial vehicles are deployed as edge caching servers. Then, we propose an energy-aware coded caching strategy employed in our system model to provide more multicast opportunities, and to reduce the backhaul transmission volume, considering the effects of file popularity, cache size, request frequency, and mobility in different road sections (RSs). Furthermore, we derive the closed-form expressions of total energy consumption both in single-RS and multi-RSs scenarios with asynchronous and synchronous services schemes, respectively. An optimization problem is formulated to minimize the total energy consumption, and the optimal content placement matrix, power allocation vector, and coverage deployment vector are obtained by well-designed algorithms. We finally show, numerically, our coded caching strategy can greatly improve energy efficient performance in CSUVINs, compared with other benchmarked caching schemes under the heterogeneous network conditions.
AB - The Internet of Vehicles (IoV) can offer safe and comfortable driving experience, by the enhanced advantages of space-air-ground-integrated networks (SAGINs), i.e., global seamless access, wide-area coverage, and flexible traffic scheduling. However, due to the huge popular traffic volume, limited cache/power resources, and the heterogeneous network infrastructures, the burden of backhaul link will be seriously enlarged, degrading the energy efficiency of IoV in SAGIN. In this article, to implement the popular content severing multiple vehicle users (VUs), we consider a cache-enabled satellite-UAV-vehicle-integrated network (CSUVIN), where the geosynchronous Earth orbit (GEO) satellite is regard as a cloud server, and unmanned aerial vehicles are deployed as edge caching servers. Then, we propose an energy-aware coded caching strategy employed in our system model to provide more multicast opportunities, and to reduce the backhaul transmission volume, considering the effects of file popularity, cache size, request frequency, and mobility in different road sections (RSs). Furthermore, we derive the closed-form expressions of total energy consumption both in single-RS and multi-RSs scenarios with asynchronous and synchronous services schemes, respectively. An optimization problem is formulated to minimize the total energy consumption, and the optimal content placement matrix, power allocation vector, and coverage deployment vector are obtained by well-designed algorithms. We finally show, numerically, our coded caching strategy can greatly improve energy efficient performance in CSUVINs, compared with other benchmarked caching schemes under the heterogeneous network conditions.
KW - Cache-enabled satellite-UAV-vehicle-integrated network (CSUVIN)
KW - coded caching strategy
KW - content placement
KW - energy efficient optimization
KW - power allocation
KW - unmanned aerial vehicle (UAV) deployment
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U2 - 10.1109/JIOT.2021.3065664
DO - 10.1109/JIOT.2021.3065664
M3 - Article
AN - SCOPUS:85102678073
VL - 9
SP - 5799
EP - 5811
JO - IEEE Internet of Things Journal
JF - IEEE Internet of Things Journal
SN - 2327-4662
IS - 8
ER -