TY - GEN
T1 - Joint drone association and content placement in cache-enabled internet of drones
AU - Yao, Jingjing
AU - Ansari, Nirwan
PY - 2019/12
Y1 - 2019/12
N2 - Internet of drones (IoD), employing drones as the internet of things (IoT) devices, brings flexibility to IoT networks and has been used to provision several applications (e.g., object tracking and traffic surveillance). The explosive growth of users and IoD applications injects massive traffic into IoD networks, hence causing congestions and reducing the quality of service (QoS). In order to improve the QoS, caching at IoD gateways is a promising solution which stores popular IoD data and sends them directly to the users instead of activating drones to transmit the data; this reduces the traffic in IoD networks. In order to fully utilize the storage-limited caches, appropriate content placement decisions should be made to determine which data should be cached. On the other hand, appropriate drone association strategies, which determine the serving IoD gateway for each drone, help distribute the network traffic properly and hence improve the QoS. In our work, we consider a joint optimization of drone association and content placement problem aimed at maximizing the average data transfer rate. This problem is formulated as an integer linear programming (ILP) problem. We then design the Drone Association and Content Placement (DACP) algorithm to solve this problem with low computational complexity. Extensive simulations demonstrate the performance of DACP.
AB - Internet of drones (IoD), employing drones as the internet of things (IoT) devices, brings flexibility to IoT networks and has been used to provision several applications (e.g., object tracking and traffic surveillance). The explosive growth of users and IoD applications injects massive traffic into IoD networks, hence causing congestions and reducing the quality of service (QoS). In order to improve the QoS, caching at IoD gateways is a promising solution which stores popular IoD data and sends them directly to the users instead of activating drones to transmit the data; this reduces the traffic in IoD networks. In order to fully utilize the storage-limited caches, appropriate content placement decisions should be made to determine which data should be cached. On the other hand, appropriate drone association strategies, which determine the serving IoD gateway for each drone, help distribute the network traffic properly and hence improve the QoS. In our work, we consider a joint optimization of drone association and content placement problem aimed at maximizing the average data transfer rate. This problem is formulated as an integer linear programming (ILP) problem. We then design the Drone Association and Content Placement (DACP) algorithm to solve this problem with low computational complexity. Extensive simulations demonstrate the performance of DACP.
KW - Caching
KW - Content placement
KW - Drone
KW - Drone association
KW - Internet of Drones (IoD)
KW - Internet of Things (IoT)
KW - Quality of service (QoS)
UR - http://www.scopus.com/inward/record.url?scp=85081973927&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85081973927&partnerID=8YFLogxK
U2 - 10.1109/GLOBECOM38437.2019.9013274
DO - 10.1109/GLOBECOM38437.2019.9013274
M3 - Conference contribution
T3 - 2019 IEEE Global Communications Conference, GLOBECOM 2019 - Proceedings
BT - 2019 IEEE Global Communications Conference, GLOBECOM 2019 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2019 IEEE Global Communications Conference, GLOBECOM 2019
Y2 - 9 December 2019 through 13 December 2019
ER -