Hybrid Content Caching in 5G Wireless Networks: Cloud Versus Edge Caching

Kwak, Jeongho; Kim, Yeongjin; Le, Long Bao; Chong, Song

doi:10.1109/twc.2018.2805893

Cited by 136 publications

(54 citation statements)

References 28 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In recent years, using machine learning techniques to predict the unknown content popularity, and proactively cache the popular contents at the BSs in advance of users' requests, has attracted the attention of the researchers [24]. In [25], the authors propose a Lyapunov optimization approach to hybrid content caching design to tackle spatial dynamics in traffic demands, where the content popularity is not required. The authors in [3] and [26] relax this assumption and introduce the multi-armed bandit (MAB) based learning approaches to estimate the content popularity distribution over time horizon.…”

Section: A Related Workmentioning

confidence: 99%

A Reinforcement Learning-Based User-Assisted Caching Strategy for Dynamic Content Library in Small Cell Networks

Zhang

Zheng

Lambotharan

et al. 2020

IEEE Trans. Commun.

View full text Add to dashboard Cite

This paper studies the problem of joint edge cache placement and content delivery in cache-enabled small cell networks in the presence of spatio-temporal content dynamics unknown a priori. The small base stations (SBSs) satisfy users' content requests either directly from their local caches, or by retrieving from other SBSs' caches or from the content server. In contrast to previous approaches that assume a static content library at the server, this paper considers a more realistic nonstationary content library, where new contents may emerge over time at different locations. To keep track of spatio-temporal content dynamics, we propose that the new contents cached at users can be exploited by the SBSs to timely update their flexible cache memories in addition to their routine off-peak main cache updates from the content server. To take into account the variations in traffic demands as well as the limited caching space at the SBSs, a user-assisted caching strategy is proposed based on reinforcement learning principles to progressively optimize the caching policy with the target of maximizing the weighted network utility in the long run. Simulation results verify the superior performance of the proposed caching strategy against various benchmark designs.

show abstract

Section: A Related Workmentioning

confidence: 99%

A Reinforcement Learning-Based User-Assisted Caching Strategy for Dynamic Content Library in Small Cell Networks

Zhang

Zheng

Lambotharan

et al. 2020

IEEE Trans. Commun.

View full text Add to dashboard Cite

show abstract

“…Probabilistic content placement is designed to maximize the performance of content delivery for cache-enabled multi-antenna dense small cell network [14]. Dynamic content caching is studied via stochastic optimization for a hierarchical caching system consisting of original content servers, central cloud units and base stations (BSs) [15]. The successful transmission probabilities are analyzed for a two-tier large-scale cache-enabled wireless multicasting network [16], [17].…”

Section: ) Optimization Of Content Placementmentioning

confidence: 99%

Cloud-Edge Coordinated Processing: Low-Latency Multicasting Transmission

Ren

Wang

et al. 2019

IEEE J. Select. Areas Commun.

View full text Add to dashboard Cite

Recently, edge caching and multicasting arise as two promising technologies to support highdata-rate and low-latency delivery in wireless communication networks. In this paper, we design three transmission schemes aiming to minimize the delivery latency for cache-enabled multigroup multicasting networks. In particular, full caching bulk transmission scheme is first designed as a performance benchmark for the ideal situation where the caching capability of each enhanced remote radio head (eRRH) is sufficient large to cache all files. For the practical situation where the caching capability of each eRRH is limited, we further design two transmission schemes, namely partial caching bulk transmission (PCBT) and partial caching pipelined transmission (PCPT) schemes. In the PCBT scheme, eRRHs first fetch the uncached requested files from the baseband unit (BBU) and then all requested files are simultaneously transmitted to the users. In the PCPT scheme, eRRHs first transmit the cached requested files while fetching the uncached requested files from the BBU. Then, the remaining cached requested files and fetched uncached requested files are simultaneously transmitted to the users. The design goal of the three transmission schemes is to minimize the delivery latency, subject to some practical constraints. Efficient algorithms are developed for the low-latency cloud-edge coordinated transmission strategies. Numerical results are provided to evaluate the performance of the proposed ). 2 transmission schemes and show that the PCPT scheme outperforms the PCBT scheme in terms of the delivery latency criterion. Index TermsCache-enabled radio access networks, delivery latency, multigroup multicasting, non-convex optimization. I. INTRODUCTIONDriven by the visions of ultra-high-definition video, intelligent driving, and Internet of Things, high-data-rate and low-latency delivery become two key performance indicators of future wireless communication networks [1]. The vast resources available in the cloud radio access server can be leveraged to deliver elastic computing power and storage to support resource-constrained enduser devices [2]. However, it is not suitable for a large set of cloud-based applications such as the delay-sensitive ones, since end devices in general are far away from the central cloud server, i.e., data center [3], [4]. To overcome these drawbacks, caching popular content at the network edge during the off-peak period is proved to be a powerful technique to realize low-latency delivery for some specific applications, such as real-time online gaming, virtual reality, and ultra-highdefinition video streaming, in next-generation communication systems [5]- [7]. Consequently, an evolved network architecture, labeled as cache-enabled radio access networks (RANs), has emerged to satisfy the demands of ultra-low-latency delivery by migrating the computing and caching functions from the cloud to the network edge [7]- [9]. In the cache-enabled RANs, the cache-enabled radio access nodes named as enhanced remote radio he...

show abstract

“…Constraint (13) ensures that the number of UPs that are accommodated by a DU d at EC r cannot exceed this EC-DUs UP capacity. Constraint (15) ensures that the total occupied midhaul bandwidth in a wavelength cannot exceed the wavelengths capacity, i.e., K.…”

Section: Constraintsmentioning

confidence: 99%

Joint Functional Splitting and Content Placement for Green Hybrid CRAN

Sriram

Masoudi

Alabbasi

et al. 2019

2019 IEEE 30th Annual International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC)

View full text Add to dashboard Cite

A hybrid cloud radio access network (H-CRAN) architecture has been proposed to alleviate the midhaul capacity limitation in C-RAN. In this architecture, functional splitting is utilized to distribute the processing functions between a central cloud and edge clouds. The flexibility of selecting specific split point enables the H-CRAN designer to reduce midhaul bandwidth, or reduce latency, or save energy, or distribute the computation task depending on equipment availability. Meanwhile, techniques for caching are proposed to reduce content delivery latency and the required bandwidth. However, caching imposes new constraints on functional splitting. In this study, considering H-CRAN, a constraint programming problem is formulated to minimize the overall power consumption by selecting the optimal functional split point and content placement, taking into account the content access delay constraint. We also investigate the trade-off between the overall power consumption and occupied midhaul bandwidth in the network. Our results demonstrate that functional splitting together with enabling caching at edge clouds reduces not only content access delays but also fronthaul bandwidth consumption but at the expense of higher power consumption.

show abstract

Hybrid Content Caching in 5G Wireless Networks: Cloud Versus Edge Caching

Cited by 136 publications

References 28 publications

A Reinforcement Learning-Based User-Assisted Caching Strategy for Dynamic Content Library in Small Cell Networks

A Reinforcement Learning-Based User-Assisted Caching Strategy for Dynamic Content Library in Small Cell Networks

Cloud-Edge Coordinated Processing: Low-Latency Multicasting Transmission

Joint Functional Splitting and Content Placement for Green Hybrid CRAN

Contact Info

Product

Resources

About