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.

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

Junaid Qadir;Anwar Khan;
2020-01-01

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.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11567/1106821
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