MDC2: An Integrated Communication and Computing Framework to Optimize Edge-Assisted Caching for Improved Multimedia Services in UAV-Based IoT Networks

Multiaccess edge computing (MEC) has revolutionized the delivery of large-scale mobile multimedia services by endowing network edge with computing and caching capabilities. This not only relieves the load on core networks, but also significantly reduces data access latency. However, deploying edge data centers with a high density to accommodate the growing demand for multimedia services is not cost-effective. With the rapid development of the Internet of Things (IoT) industry, recent studies have shown that by allowing UAVs with integrated computing and communication to form a mobile device cloud (MDC) environment via UAV-to-UAV (U2U) communications in IoT networks, UAVs can play an important role in assisting cellular networks with multimedia delivery and providing excellent service for IoT devices on the ground. While a MDC environment composed of UAVs offers flexibility and cost-effectiveness, the challenge remains in allocating caching resources in a timely manner to meet the dynamic content demands. To address this challenge, we design a novel MDC-enabled Caching (MDC2) framework, which makes use of the available caching and U2U communication capabilities to enable any UAV to obtain dynamically content from other nearby UAVs via the IoT network. By modeling the dynamic network status as a fluid-based system, MDC2 employs a dynamic caching allocation algorithm to minimize both service latency and caching costs. Extensive experiments demonstrate that MDC2 outperforms a state-of-the-art MDC multimedia delivery approach by improving average cache utilization with over 40% and reducing average access latency with more than 25%.