Cloud storage for Small Cell Networks

Baştuğ, Ejder; Guenego, Jean-Louis; Debbah, Mérouane

doi:10.1109/cloudnet.2012.6483659

Cited by 5 publications

(5 citation statements)

References 20 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Synchronous delivery with no change in file popularities paired with the use of coded caching and/or delivery was studied in [5]- [18]. Asynchronous delivery with changing file popularities but with uncoded caching and uncoded delivery was studied in [2]- [4]. The use of index-coded caching and/or index-coded delivery for asynchronous delivery is not well explored in the literature.…”

Section: Related Work and Motivationmentioning

confidence: 99%

mentioning

confidence: 99%

“…Wireless networks with caches are considered extensively in the recent literature [2]- [21]. The proactive caching research focuses on two main caching strategies, the first is storing raw files in respective caches [2]- [4]. The second, is coding of different files together (e.g., index coding [22]) to optimize the usage of the resources [5]- [21].…”

mentioning

confidence: 99%

“…The second, is coding of different files together (e.g., index coding [22]) to optimize the usage of the resources [5]- [21]. The authors of [2] proposed the idea of small-cell network cloud as a technique to increase cloud capacity, relieve the backhaul constraints and increase the peak rate through content caching. Mobility and proactive caching are considered in [3], where a cache-aided smallcell system is considered while users are moving through the network and the content demand distribution is assumed to be known.…”

mentioning

confidence: 99%

See 3 more Smart Citations

Coded Caching for Time-Varying Files Popularities and Asynchronous Delivery

Amir

Bedeer

Ahmed

et al. 2021

IEEE Open J. Commun. Soc.

View full text Add to dashboard Cite

Data communication has seen exponential growth recently, and it currently dominates wireless communication. As a result, proactive caching was developed to minimize peak traffic rates by storing content, in advance, at different nodes in the network. We consider proactive caching for a broadcast wireless network with one central hub such as a satellite (ST) and K associated mobile units (MUs) such as mobile mini-ground stations or end users. The ST has a library of files, and the MUs demands are assumed to be limited to this library, while the popularity of the library files changes over time. We assume that the MUs demands arrive at different times, and hence, asynchronous file delivery is necessary. We propose a new scheme that minimizes the files delivery sum rate and show that we can use the file delivery messages to proactively and constantly update the MU finite caches. We show that this mechanism reduces the downloaded traffic of the network. The proposed scheme uses index coding to jointly encode the delivery of different demanded files with the cache updates to other MUs to follow the changes in the files popularities. An offline optimization of the delivery sum rate of the scheme is proposed, where it requires knowledge of the files popularities across the whole transmission period. In particular, the problem is formulated as a linear program and the optimal caching is obtained numerically. Moreover closed form solutions to two special cases are derived and a lowerbound to the achievable delivery sum rate is developed. Numerical results show the benefits of the proposed scheme over conventional caching schemes, in terms of reducing the delivery sum rate.Index Terms-Coded caching, data communications, index coding, proactive caching. I. INTRODUCTIONC ELLULAR traffic has shifted over the past decade from mainly locally generated instantaneous traffic (voice calls) to centrally generated delay-tolerant bulks of traffic (data driven communication) [1]. This necessitated the development of new information theoretic analysis and new algorithms for communication networks. One key characteristic of data communication is that the delay between the time of data generation and the time of data demand at the receivers is mostly large. This enables the data to be stored midway in different nodes along the path from the transmitter to the receiver to relieve pressure of congested links. Future expansions of future generation cellular networks are targeting satellite integration with terrestrial networks to increase coverage and availability. Satellite links have broadcast nature and introduces further delays; thus, strengthening the case for midway storage (or caching). Moreover, the shift from voice to data traffic contradicts the classical assumption of network analysis that messages are generally independent. This assumption is not accurate for data communication, especially in broadcast networks, where a piece of data is generally demanded by multiple users over time. Proactive caching is an efficient technique t...

show abstract

Section: Related Work and Motivationmentioning

confidence: 99%

mentioning

confidence: 99%

mentioning

confidence: 99%

mentioning

confidence: 99%

See 2 more Smart Citations

Coded Caching for Time-Varying Files Popularities and Asynchronous Delivery

Amir

Bedeer

Ahmed

et al. 2021

IEEE Open J. Commun. Soc.

View full text Add to dashboard Cite

show abstract

“…Due to the costly nature of this requirement, the current state of the art proposes to add high storage units (i.e., hard-disks, solid-state drives) to small cells (SCs) and use these units for caching purposes [4], (i.e., in order to offload the significant amount of backhaul usage). To decrease the cost and have additional benefits, the work in [5] proposes to use such a dense infrastructure opportunistically for cloud storage scenarios either for caching or persistent storage. Independently, another line of research focuses on proactivity to handle network resources efficiently, and can be seen as a complementary [6], [7].…”

Section: Introductionmentioning

confidence: 99%

Proactive small cell networks

2013

Self Cite

View full text Add to dashboard Cite

Abstract-Proactive scheduling in mobile networks is known as a way of using network resources efficiently. In this work, we investigate proactive Small Cell Networks (SCNs) from a caching perspective. We first assume that these small base stations are deployed with high capacity storage units but have limited capacity backhaul links. We then describe the model and define a Quality of Experience (QoE) metric in order to satisfy a given file request. The optimization problem is formulated in order to maximize this QoE metric for all requests under the capacity constraints. We solve this problem by introducing an algorithm, called PropCaching (proactive popularity caching), which relies on the popularity statistics of the requested files. Since not all requested files can be cached due to storage constraints, the algorithm selects the files with the highest popularities until the total storage capacity is achieved. Consecutively, the proposed caching algorithm is compared with random caching. Given caching and sufficient capacity of the wireless links, numerical results illustrate that the number of satisfied requests increases. Moreover, we show that PropCaching performs better than random caching in most cases. For example, for R = 192 number of requests and a storage ratio γ = 0.25 (storage capacity over sum of length of all requested files), the satisfaction in PropCaching is 85% higher than random caching and the backhaul usage is reduced by 10%.

show abstract

Distributed storage in the plane

Altman

Avrachenkov

Goseling

2014

2014 IFIP Networking Conference

View full text Add to dashboard Cite

We consider storage devices located in the plane according to a general point process and specialize the results for the homogeneous Poisson process. A large data file is stored at the storage devices, which have limited storage capabilities. Hence, they can only store parts of the data. Clients can contact the storage devices to retrieve the data. We compare the expected cost of obtaining the complete data under uncoded as well as coded data allocation strategies. It is shown that for the general class of cost measures where the cost of retrieving data is increasing with the distance between client and storage devices, coded allocation outperforms uncoded allocation. The improvement offered by coding is quantified for two more specific classes of performance measures. Finally, our results are validated by computing the costs of the allocation strategies for the case that storage devices coincide with currently deployed mobile base stations.

show abstract

Cloud storage for Small Cell Networks

Cited by 5 publications

References 20 publications

Coded Caching for Time-Varying Files Popularities and Asynchronous Delivery

Coded Caching for Time-Varying Files Popularities and Asynchronous Delivery

Proactive small cell networks

Distributed storage in the plane

Contact Info

Product

Resources

About