Joint Optimization of Cloud and Edge Processing for Fog Radio Access Networks

Park, Seok-Hwan; Simeone, Osvaldo; Shamai, Shlomo

doi:10.1109/twc.2016.2605104

Cited by 211 publications

(175 citation statements)

References 50 publications

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“…The system architecture and key techniques of F-RANs have been proposed in [3]. Particularly, different caching strategies for F-RANs, such as cache most popular, cache distinct, and fractional cache distinct, has been discussed in [4], which are suitable for centralized request, discrete request, and capacitylimited fronthaul scenario, respectively. Meanwhile, significant gains of SE [5], EE [6] and latency [7] have been obtained in cache-enabled F-RANs.…”

Section: A Related Workmentioning

confidence: 99%

Tradeoff Between Ergodic Rate and Delivery Latency in Fog Radio Access Networks

Yin

Peng

Yan

et al. 2020

IEEE Trans. Wireless Commun.

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Wireless content caching has recently been considered as an efficient way in fog radio access networks (F-RANs) to alleviate the heavy burden on capacity-limited fronthaul links and reduce delivery latency. In this paper, an advanced minimal delay association policy is proposed to minimize latency while guaranteeing spectral efficiency in F-RANs. By utilizing stochastic geometry and queueing theory, closed-form expressions of successful delivery probability, average ergodic rate, and average delivery latency are derived, where both the traditional association policy based on accessing the base station with maximal received power and the proposed minimal delay association policy are concerned. Impacts of key operating parameters on the aforementioned performance metrics are exploited. It is shown that the proposed association policy has a better delivery latency than the traditional association policy. Increasing the cache size of fog-computing based access points (F-APs) can more significantly reduce average delivery latency, compared with increasing the density of F-APs. Meanwhile, the latter comes at the expense of decreasing average ergodic rate. This implies the deployment of large cache size at F-APs rather than high density of F-APs can promote performance effectively in F-RANs.

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Section: A Related Workmentioning

confidence: 99%

Tradeoff Between Ergodic Rate and Delivery Latency in Fog Radio Access Networks

Yin

Peng

Yan

et al. 2020

IEEE Trans. Wireless Commun.

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show abstract

“…In Qiu and Cao, 18 the authors evaluate how the distribution of the content popularity affects the network capacity, and derive different capacity scaling laws based on the skewness of the content popularity. In Park et al, 19 joint design of cloud and edge processing for an F-RAN architecture is studied, and the optimization of the delivery phase is considered with the goal of maximizing the minimum delivery rate of the requested files. In this line of work, content popularity is not taken into account.…”

Section: Related Workmentioning

confidence: 99%

Proactive content caching by exploiting transfer learning for mobile edge computing

Hou

Feng

Qin

et al. 2018

Int J Communication

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Summary To address the vast multimedia traffic volume and requirements of user quality of experience in the next‐generation mobile communication system (5G), it is imperative to develop efficient content caching strategy at mobile network edges, which is deemed as a key technique for 5G. Recent advances in edge/cloud computing and machine learning facilitate efficient content caching for 5G, where mobile edge computing can be exploited to reduce service latency by equipping computation and storage capacity at the edge network. In this paper, we propose a proactive caching mechanism named learning‐based cooperative caching (LECC) strategy based on mobile edge computing architecture to reduce transmission cost while improving user quality of experience for future mobile networks. In LECC, we exploit a transfer learning‐based approach for estimating content popularity and then formulate the proactive caching optimization model. As the optimization problem is NP‐hard, we resort to a greedy algorithm for solving the cache content placement problem. Performance evaluation reveals that LECC can apparently improve content cache hit rate and decrease content delivery latency and transmission cost in comparison with known existing caching strategies.

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“…A second taxonomy includes the works investigating the virtualization of the radio access networks (see, eg, references herein [36][37][38][39][40][41] ). More in depth, Michalopoulos et al 38 advocate the need for a flexible network design for next generation networks.…”

Section: Virtualization Of Network Functionsmentioning

confidence: 99%

“…However, the MEC placement, as well as the modeling of the communication channel between each user and the serving RRH, is not considered. Park et al 40 focus on the problem of joint optimization of cloud and edge processing in fog radio access networks. In particular, the authors assume that the RRHs may be equipped with local caches, containing frequently requested content and baseband processing capabilities.…”

Section: Virtualization Of Network Functionsmentioning

confidence: 99%

Optimal management of reusable functional blocks in 5G superfluid networks

et al. 2018

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Summary We consider the problem of managing a 5G network composed of virtualized entities, called reusable functional blocks (RFBs), as proposed by the Horizon 2020 SUPERFLUIDITY project. The RFBs are used to decompose network functions and services and are deployed on top of physical nodes, in order to realize the 5G functionalities. After formally modeling the RFBs in a 5G network, as well as the physical nodes hosting them, we formulate the problem of managing the 5G network through the RFBs, in order to satisfy different key performance indicators to users. In particular, we focus either on the maximization of the amount of downlink throughput sent to users or on the minimization of the number of powered‐on physical nodes. We then consider different scenarios to evaluate the proposed formulations. Our results show that, when an RFB‐based approach is put into place, a high level of flexibility and dynamicity is achieved. In particular, the RFBs can be shared, moved, and rearranged based on the network conditions. As a result, the downlink throughput can be extremely high, ie, more than 150 Mbps per user on average when the throughput maximization is pursued and more than 100 Mbps on average when the goal is the minimization of the number of powered‐on physical nodes.

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Joint Optimization of Cloud and Edge Processing for Fog Radio Access Networks

Cited by 211 publications

References 50 publications

Tradeoff Between Ergodic Rate and Delivery Latency in Fog Radio Access Networks

Tradeoff Between Ergodic Rate and Delivery Latency in Fog Radio Access Networks

Proactive content caching by exploiting transfer learning for mobile edge computing

Optimal management of reusable functional blocks in 5G superfluid networks

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