CE-D2D: Dual Framework Chunks Caching and offloading in Collaborative Edge networks with D2D communication

The advancement of technology has pushed the cloud computing capabilities to the edge networks, paving the way for network operators and multimedia service providers to leverage video caching and transcoding to the Mobile Edge computing (MEC) servers. However, because of high load demands in peak hours and the limited bandwidth, congestions may occur, leading to lower network performance. This problem is worsened by the redundancies of the same content requests and the expectation for the highest video quality, which exhausts the cellular spectrum and the backhaul links. Collaboration between edge servers, to cache and transcode videos, is proposed and proved its efficiency to store highly requested contents and relieve the load on the backhaul links. Meanwhile, Device-to-device (D2D) offloading is considered to alleviate cellular spectrum utilization. In this paper, we will extend the Collaborative Edge (CE) network to include the mobile users (D2D) caching and offloading and create a CE-D2D dual framework. Still, this framework does not present the perfect solution for exhaustive bandwidth utilization. In fact, users’ mobiles have small storage capacities and very scarce bandwidth availability, which limits the number of cached videos and constraints sharing large sized contents. Additionally, existing D2D approaches are considering video requests as simple contents similar to any HTML page request. However, in realistic cases, a lower bitrate version of the content can be offered to the viewers, if the bandwidth (cellular or mobile) is unavailable. Hence, to maximize the caching efficiency, we formulate the CE-D2D framework as a linear program, where MEC servers and users’ mobiles collaborate to cache and offload different chunks of the requested content constrained by cache and bandwidth availability. In this way, instead of caching and serving full popular videos, as done in previous works, we will only cache popular chunks within different helpers, which maximizes the efficiency of caching in small storage devices.