Towards Mobile Edge Computing: Taxonomy, Challenges, Applications and Future Realms

Abstract

The realm of cloud computing has revolutionized access to cloud resources and their utilization and applications over the Internet. However, deploying cloud computing for delay critical applications and reducing the delay in access to the resources are challenging. The Mobile Edge Computing (MEC) paradigm is one of the effective solutions, which brings the cloud computing services to the proximity of the edge network and leverages the available resources. This paper presents a survey of the latest and state-of-the-art algorithms, techniques, and concepts of MEC. The proposed work is unique in that the most novel algorithms are considered, which are not considered by the existing surveys. Moreover, the chosen novel literature of the existing researchers is classified in terms of performance metrics by describing the realms of promising performance and the regions where the margin of improvement exists for future investigation for the future researchers. This also eases the choice of a particular algorithm for a particular application. As compared to the existing surveys, the bibliometric overview is provided, which is further helpful for the researchers, engineers, and scientists for a thorough insight, application selection, and future consideration for improvement. In addition, applications related to the MEC platform are presented. Open research challenges, future directions, and lessons learned in area of the MEC are provided for further future investigation.

Operating Systems and Hypervisors for Network Functions: A Survey of Enabling Technologies and Research Studies

“…We note that the different forms of software entities can be physically executed in any computing location in communication networks [76], such as in-network computing [77]- [79] also referred to as computing in the network (COIN) [80], fog computing [81], [82], and multi-access edge computing (MEC) [83]- [89].…”

“…The traditional implementation of containers and VMs involves multiple levels of abstraction for effective management of the hardware resources and application demands. Multi-level abstractions with nested VMs and containers are particularly necessary for network and resource slicing in Multi-access Edge Computing (MEC) [83]- [89], where high degrees of isolation and flexibility are needed. For instance, VMs running on an MEC can provide service provider level isolation, whereas containers running inside VMs can provide application level isolation for the Container Network Functions (CNFs).…”

“…One of the key benefits of virtualization is the dynamic migration of the virtualized entities, such as the VNFs. VM migration has been widely studied in the cloud-native environment [132]; however, the VM migration still needs to be explored in the MEC context [83]- [89]. The VM migration in the MEC context is much more complex than in the cloudnative environment because of resource constraints, both in terms of the target computing resource availability and the connectivity bit rate (i.e., throughput) restrictions.…”

A dark and stormy night: Reallocation storms in edge computing

“…Workload is the computational burden on edge servers (ES) or cloud, caused by user tasks accumulating on those servers [11,12]. Workload may be the result of, for example, user applications or their components offloaded on the edge servers [13]; by edge applications following users, migrating from one ES to another [14,15]; or by cloud applications being onloaded to edge servers for low-latency interaction with users or environment [13,16].…”

Weathering the Reallocation Storm: Large-Scale Analysis of Edge Server Workload

“…Workload. Workload is the computational burden on edge servers (ES) or cloud, caused by user tasks accumulating on those servers [11], [21]. Workload may be the result of, for example, user applications or their components offloaded on the edge servers [22]; by edge applications following users, migrating from one ES to another [23], [24]; or by cloud applications being onloaded to edge servers for low-latency interaction with users or environment [22], [25].…”