Edge-Boost: Enhancing Multimedia Delivery with Mobile Edge Caching in 5G-D2D Networks
Venkatraman Balasubramanian, Mu Wang, Martin Reisslein, Changqiao Xu · 2019
By moving computation and caching to the network edge, Mobile Edge Computing (MEC) offloads core networks and shortens data access latencies, which is important for large scale mobile multimedia services. Increasing the density of edge data centers to service these multimedia requests is uneconomical. Recent research has proven the benefits of involving devices in the delivery of multimedia services. This is done by exploiting the idle computation and storage resources via device-to-device (D2D) communication, i.e., by forming a so-called Mobile Device Cloud (MDC). Despite the flexibility and cost efficiency of this MDC paradigm, the timely allocation of caching resources to satisfy the dynamic user demands is challenging. This is mainly due to the uncertainty in resource availability of mobile devices. To this end, we propose Edge-Boost, a novel MDC caching architecture for lowlatency multimedia streaming services. We develop a novel fluid-based model to capture the dynamically changing network status. Additionally, we propose a dynamic caching allocation to jointly minimize caching cost and service latency. Edge-Boost achieves over 20% higher average cache utilization and 15% shorter average access latency than the state-of-the-art MDC approach.