On Multi-Access Edge Computing: A Survey of the Emerging 5G Network Edge Cloud Architecture and Orchestration

Taleb, Tarik; Samdanis, Konstantinos; Mada, Badr Eddine; Flinck, Hannu; Dutta, Sunny; Sabella, Dario

doi:10.1109/comst.2017.2705720

Cited by 1,466 publications

(846 citation statements)

References 143 publications

Supporting

Mentioning

746

Contrasting

Unclassified

Order By: Relevance

“…In our study, we focus on the term edge computing to maintain the consistency. The history of edge computing paradigms is explained in the work of Taleb et al The Cloudlet concept formed in light of the definition of Satyanarayanan et al was the first study in this domain . The cloudlets can be considered as the micro‐clouds in the proximity and the mobile users deploy and manage their own VMs over wireless networks.…”

Section: Edge Computing Background and Related Workmentioning

confidence: 99%

EdgeCloudSim: An environment for performance evaluation of edge computing systems

Sonmez

Özgövde

Ersoy

2018

Trans Emerging Tel Tech

289

171

View full text Add to dashboard Cite

Edge computing is a fast growing field of research that covers a spectrum of technologies bringing the cloud computing services closer to the end user. Growing interest in this area yields many edge computing approaches that need to be evaluated and optimized. Experimenting on the real cloud environments is not always feasible due to the operational cost and the scalability. Despite increasing research activity, this field lacks a simulation tool that supports the modeling of both computational and networking resources to handle the edge computing scenarios. Existing network simulators can model the network behavior at different levels of granularity. The cloud computing simulators support the modeling and simulation of the computational infrastructures and services efficiently. Starting from the available simulators, a significant programming effort is required to obtain a simulation tool meeting the actual needs. On the other hand, designing a new edge computing tool has many challenges such as the scalability, extensibility, and modeling the mobility, network, and virtualized resources. To decrease the barriers, a new simulator tool called EdgeCloudSim streamlined for the edge computing scenarios is proposed in this work. EdgeCloudSim builds upon CloudSim to address the specific demands of edge computing research and support the necessary functionalities. To demonstrate the capabilities of EdgeCloudSim, an experiment setup based on different edge architectures is simulated. In addition, the effect of the edge server capacity and the mobility on the overall system performance are investigated.

show abstract

Section: Edge Computing Background and Related Workmentioning

confidence: 99%

EdgeCloudSim: An environment for performance evaluation of edge computing systems

Sonmez

Özgövde

Ersoy

2018

Trans Emerging Tel Tech

289

171

View full text Add to dashboard Cite

show abstract

“…Dew architecture includes a dew virtual machine (DVM). In DVM (in the local PC), the dew server is executed . DVM consists of at least three components: Dew server (DS) : The DS acts such as the cloud service in the local PC.…”

Section: Related Workmentioning

confidence: 99%

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

Abdoos

Taheri

Taeezadeh

2019

Trans Emerging Tel Tech

View full text Add to dashboard Cite

We propose a computation that compensates the weakness of the processing power and storage capacity of the dew and edge servers. In the proposed computation, the nodes near to each other, which can be the dew, edge, or cloud servers, form a computational grid. The dew servers can be mobile devices, laptops, or computers. Their processing power and storage capacity can be used when they are idle. Our goal is to achieve load balancing of different nodes (servers). A server of the grid with proper processing power, storage capacity, remained energy, and low task load is selected as the grid head (each server of grid shares its specification with the other servers of grid periodically). The grid head (server) is responsible for grid communications. The grid head shares the specification of the grid, with the neighbor nodes (we suppose that the end device is aware of the specification of the nearest dew, edge, and cloud grid heads to itself). The end device decides about sending its created tasks to the grid head of a dew or edge or cloud grid, with attention to the distance between itself and the grid head, and the free processing power and storage capacity of the grid. The scheduling algorithm of a grid is the combination of first‐come–first‐served and priority scheduling algorithms. The simulation results show that the proposed computation has less delay and energy consumption and more efficiency than the cloud and edge computations.

show abstract

“…Functionally, switches that are used in the tactile system can be viewed as a packet forwarding devices with single or multiple flow tables [34]. Two types of switches are deployed in the OpenFlow based network, pure switches, and hybrid switches.…”

Section: System Structurementioning

confidence: 99%

Development of Intelligent Core Network for Tactile Internet and Future Smart Systems

Ateya

Muthanna

Gudkova

et al. 2018

JSAN

View full text Add to dashboard Cite

Abstract:One of the main design aspects of the Tactile Internet system is the 1 ms end-to-end latency, which is considered as being the main challenge with the system realization. Forced by recent development and capabilities of the fifth generation (5G) cellular system, the Tactile Internet will become a real. One way to overcome the 1 ms latency is to employ a centralized controller in the core of the network with a global knowledge of the system, together with the concept of network function virtualization (NFV). This is the idea behind the software defined networking (SDN). This paper introduces a Tactile Internet system structure, which employs SDN in the core of the cellular network and mobile edge computing (MEC) in multi-levels. The work is mainly concerned with the structure of the core network. The system is simulated over a reliable environment and introduces a round trip latency of orders of 1 ms. This can be interpreted by the reduction of intermediate nodes that are involved in the communication process.

show abstract

On Multi-Access Edge Computing: A Survey of the Emerging 5G Network Edge Cloud Architecture and Orchestration

Cited by 1,466 publications

References 143 publications

EdgeCloudSim: An environment for performance evaluation of edge computing systems

EdgeCloudSim: An environment for performance evaluation of edge computing systems

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

Development of Intelligent Core Network for Tactile Internet and Future Smart Systems

Contact Info

Product

Resources

About