Mobile Edge Computing: A Survey

Abstract

Mobile edge computing (MEC) is an emergent architecture where cloud computing services are extended to the edge of networks into the mobile base stations. As a promising edge technology, it can be applied to mobile, wireless and wireline scenarios, using software and hardware platforms, located at the network edge in the vicinity of end users. MEC provides seamless integration of multiple application service providers and vendors towards mobile subscribers, enterprises and other vertical segments. It is an important component in the proposed 5G architecture that supports variety of innovative applications and services where ultra low latency is required. However, there are some challenges exists in the MEC eco system. To address these challenges, first off need to understand the network infrastructure of MEC, cloud and cellular network.Some questions and problems are addressed in this thesis that outlines the importance and challenges of MEC deployment. Impact of MEC integration with the traditional mobile and cloud network appears in this paper. A survey has been presented that contributes in general understanding of mobile edge computing (MEC). Readers will have an overview of MEC, such as definition, advantages, architectures and applications. Moreover, related research and future directions are pointed out in this thesis. Finally, security and privacy issues and their possible solutions are also discussed.iii This thesis is dedicated to my late Parents who were my first teachers. Without their support, guidance, and infinite wisdom, I would not have made it this far. My fervor towards professionalism is all colored by them.Also I would like to dedicate with my heart-felt and deepest gratitude to my siblings, I am blessed beyond belief. Their love and support means more to me than they will ever know.iv First and foremost, I thank Allah the Almighty for giving me health, strength and courage to complete my master thesis and eventually my Master in Network and System Administration at UiO.

Private mobile edge cloud for 5G network applications

“…This private cloud may provide computing, storage, data processing, data caching, and networking services. The private mobile edge cloud can then be connected to conventional edge computing systems such as a mobile edge computing system or fog computing system, or it may be connected to a central virtualized cloud data center on the Internet via long‐term evolution (LTE) or 5G networks.…”

“…The heterogeneous multi‐network management layer enables direct device‐to‐device communication and multihop communication across both ad hoc and infrastructure‐based local area networks. Existing mobile ad hoc networking technologies provide limited bandwidth. Therefore, they are not suitable for resource intensive real‐time IoT and 5G network applications.…”

“…An edge‐computing layer in which computational and storage services are provided at the network edge has been suggested as a solution for the limitations of the cloud centered approach. Edge computing implementations can be divided into three categories: mobile edge computing, fog computing, and cloudlet computing. In mobile edge computing, nodes with processing and storage capabilities are deployed at the base stations of the cellular network; thus, cloud‐computing services are provided in the radio access network.…”

“…Mobile cloud computing systems cannot fulfill the requirements of resource‐intensive real‐time IoT and 5G applications due to high communication latency. Cloud computing also introduces unnecessary traffic to the core Internet network and consumes a significant amount of transmission energy when data are transmitted via cellular networks . Consequently, edge computing implementations require adding new infrastructure or updating existing infrastructure.…”

Elucidating the challenges for the praxis of fog computing: An aspect‐based study

“…These applications demand a quick response coupled high computation abilities and large bandwidth requirements. MEC can be used to enhance the throughput of such applications by providing computation services at the edge of the network, rather than relying on the core network . MEC can also be applied in big data analytics for quick extraction of meaningful information from the heterogeneous, unstructured raw data …”