A Survey on Mobile Edge Networks: Convergence of Computing, Caching and Communications

Abstract

As the explosive growth of smart devices and the advent of many new applications, traffic volume has been growing exponentially. The traditional centralized network architecture cannot accommodate such user demands due to heavy burden on the backhaul links and long latency. Therefore, new architectures which bring network functions and contents to the network edge are proposed, i.e., mobile edge computing and caching. Mobile edge networks provide cloud computing and caching capabilities at the edge of cellular networks. In this survey, we make an exhaustive review on the state-of-the-art research efforts on mobile edge networks. We first give an overview of mobile edge networks including definition, architecture and advantages. Next, a comprehensive survey of issues on computing, caching and communication techniques at the network edge is presented respectively. The applications and use cases of mobile edge networks are discussed. Subsequently, the key enablers of mobile edge networks such as cloud technology, SDN/NFV and smart devices are discussed. Finally, open research challenges and future directions are presented as well.Index Terms-Mobile edge computing, mobile edge caching, D2D, SDN, NFV, content delivery, computational offloading.

The role of caching in next generation cellular networks: A survey and research outlook

“…To enlarge the utmost benefits to facilitate network‐wide content replication, ICN is proposed to equip router with caches. Interestingly, in the work of Roberts and Sbihi, there also exists ICN, which ambitions to change the mode of retrieving the contents on the internet by uniquely naming the content and smart distribute these across the network, instead than conventionally having one source for the content access . It was also shown that most of the caching acquisitions in ICN can be acquired by caching at the edges of the network using existing CDNs, contrary to the popular belief that caching close to users is highly inefficient.…”

A proposed computation, which benefits from the cooperation of dew, edge, and cloud computations

“…Clouds may be limited to a single organization (enterprise cloud), be available to many organizations (public cloud) or a combination of both (hybrid cloud). The cloud computing architecture has two layers: the end devices (the bottom layer) and the cloud servers (the top layer) (see Figure ) …”

“…The disadvantage of edge computing is the limited processing power and storage capacity of the edge servers. The edge computing architecture has three layers: the end devices (the bottom layer), the edge servers (the intermediate layer), and the cloud servers (the top layer) (see Figure ) …”

“…By using the information, the resources of the network can be allocated more efficiently, and the user experience can be improved. The edge computing has some disadvantages, such as the limited processing power and storage capacity of edge servers …”

Bringing Geospatial Data Closer to Mobile Users: A Caching Approach Based on Vector Tiles for Wireless Multihop Scenarios

“…Recently, as D2D communications gain research attentions, caching on terminal devices also starts to show its significance [62]. For that reason, researchers are making efforts to answer questions around caching such as where to cache (placement) [63,64], what to cache (content type, popularity, and mobility awareness) [65], and how to cache (replacement policies) [66,67]. In this work, we adopt the idea of caching for vector tile sharing, and we thus introduce the definition of vector tile layers and naming scheme for data caching and exchanging.…”