Radio-Aware Service-Level Scheduling to Minimize Downlink Traffic Delay Through Mobile Edge Computing

Fajardo, José Oscar; Taboada, Ianire; Liberal, Fidel

doi:10.1007/978-3-319-26925-2_10

Cited by 16 publications

(11 citation statements)

References 12 publications

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“…The authors design an optimal computation task scheduling policy for MEC systems. The delay of general traffic flows in the LTE downlink can be minimized by service level scheduling via MEC server deployed at the eNodeB [58]. Fog also provides low delay but with low capacity limitation, while the combined operation of fog and cloud can minimize the service latency and guarantee the capacity requirements at the same time [55].…”

Section: A Objectivesmentioning

confidence: 99%

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

et al. 2017

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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.

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Section: A Objectivesmentioning

confidence: 99%

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

et al. 2017

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“…The MEC, initially introduced by IBM and Nokia Siemens Network, aims at optimizing the existing mobile infrastructure service, and minimizing the mean delay of general traffic flow in the LTE downlink [11]. Due to its characters of low latency, on-premises, and location awareness, MEC is introduced into the proposed architecture to improve the responsiveness for traffic light control and accident rescue.…”

Section: Mobile-edge Computing Server Layermentioning

confidence: 99%

High-Efficiency Urban Traffic Management in Context-Aware Computing and 5G Communication

et al. 2017

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Abstract:With the increasing number of vehicle and traffic jams, the urban-traffic management is becoming a serious issue. In this article, we propose novel four-tier architecture for urban-traffic management with the convergence of vehicle ad hoc networks (VANETs), 5G wireless network, software-defined network (SDN), and mobile-edge computing (MEC) technologies. The proposed architecture provides better communication and rapider responsive speed in a more distributed and dynamic manner. The practical case of rapid accident rescue can significantly cut down the time for rescue. Key technologies with respect to vehicle localization, data pre-fetching, traffic lights control, and traffic prediction are also discussed. Obviously, the novel architecture shows noteworthy potential for alleviating the traffic congestion and improving the efficiency of urban-traffic management.

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“…In order to exemplify the expected performance improvements of the proposed solution, preliminary simulation studies have demonstrated the associated benefits for the problem of general flow scheduling [29] and for multimedia delivery [30] in multi-user scenarios.…”

Section: Conclusion and Further Workmentioning

confidence: 99%

Introducing Mobile Edge Computing Capabilities through Distributed 5G Cloud Enabled Small Cells

et al. 2016

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Abstract:Current trends in broadband mobile networks are addressed towards the placement of different capabilities at the edge of the mobile network in a centralised way. On one hand, the split of the eNB between baseband processing units and remote radio headers makes it possible to process some of the protocols in centralised premises, likely with virtualised resources. On the other hand, mobile edge computing makes use of processing and storage capabilities close to the air interface in order to deploy optimised services with minimum delay. The confluence of both trends is a hot topic in the definition of future 5G networks. The full centralisation of both technologies in cloud data centres imposes stringent requirements to the fronthaul connections in terms of throughput and latency. Therefore, all those cells with limited network access would not be able to offer these types of services. This paper proposes a solution for these cases, based on the placement of processing and storage capabilities close to the remote units, which is especially well suited for the deployment of clusters of small cells. The proposed cloudenabled small cells include a highly efficient microserver with a limited set of virtualised resources offered to the cluster of small cells. As a result, a light data centre is created and commonly used for deploying centralised eNB and mobile edge computing functionalities. The paper covers the proposed architecture, with special focus on the integration of both aspects, and possible scenarios of application.

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Radio-Aware Service-Level Scheduling to Minimize Downlink Traffic Delay Through Mobile Edge Computing

Cited by 16 publications

References 12 publications

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

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

High-Efficiency Urban Traffic Management in Context-Aware Computing and 5G Communication

Introducing Mobile Edge Computing Capabilities through Distributed 5G Cloud Enabled Small Cells

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