Low subpacketization schemes for coded caching

Tang, Li; Ramamoorthy, Aditya

doi:10.1109/isit.2017.8007038

Cited by 22 publications

(8 citation statements)

References 4 publications

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“…For a large number of receivers, a large coding times is a problem in the coded caching schemes and beyond the scope of discussion in this paper. This problem has been discussed in [14]- [16]. In future works, these methods will be applied to proposed scheme and the conventional schemes and we will evaluate the partical delay time of these scheme in multi-rate wireless networks.…”

Section: Numerical Resultsmentioning

confidence: 99%

Coded Caching in Multi-Rate Wireless Networks

Takita

Hirotomo

Morii

2020

IEICE Trans. Fundamentals

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The network load is increasing due to the spread of content distribution services. Caching is recognized as a technique to reduce the peak network load by storing popular content into memories of users. Coded caching is a new caching approach based on a carefully designed content placement to create coded multicasting opportunities. Coded caching schemes in single-rate networks are evaluated by the tradeoff between the size of memory and that of delivered data. For considering the network with multiple transmission rates, it is crucial how to operate multicast. In multicast delivery, a sender must communicate to intended receivers at a rate that is available to all receivers. Multicast scheduling method of determining rates to deliver are evaluated by throughput and delay in multi-rate wireless networks. In this paper, we discuss coded caching in the multi-rate wireless networks. We newly define a measure for evaluating the coded caching scheme as coded caching delay and propose a new coded caching scheme. Also, we compare the proposed coded caching scheme with conventional coded caching schemes and show that the proposed scheme is suitable for multi-rate wireless networks.

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Section: Numerical Resultsmentioning

confidence: 99%

Coded Caching in Multi-Rate Wireless Networks

Takita

Hirotomo

Morii

2020

IEICE Trans. Fundamentals

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“…Note that the achievable bound in (10) has been shown to be achievable for any integers r, h with r < h in [11], by using MDS code before placement phase. From (16), is inferior to the new scheme when M = N · 1 − h−r+1 K .…”

Section: Transforming Pdas Into Larger C-pdasmentioning

confidence: 94%

Placement Delivery Array Design for Combination Networks with Edge Caching

Yan

Wigger

Yang

2018

2018 IEEE International Symposium on Information Theory (ISIT)

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A major practical limitation of the Maddah-Ali-Niesen coded caching techniques is their high subpacketization level. For the simple network with a single server and multiple users, Yan et al. proposed an alternative scheme with the so-called placement delivery arrays (PDA). Such a scheme requires slightly higher transmission rates but significantly reduces the subpacketization level. In this paper, we extend the PDA framework and propose three low-subpacketization schemes for combination networks, i.e., networks with a single server, multiple relays, and multiple cache-aided users that are connected to subsets of relays. One of the schemes achieves the cutset lower bound on the link rate when the cache memories are sufficiently large. Our other two schemes apply only to resolvable combination networks. For these networks and for a wide range of cache sizes, the new schemes perform closely to the coded caching schemes that directly apply Maddah-Ali-Niesen scheme while having significantly reduced subpacketization levels.

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“…They have been introduced in the literature through several other equivalent formulations (like placement delivery array etc.) [13]- [18]. In the next section,…”

Section: A Centralized Schemes -Ruzsa-szemerédi Constructionsmentioning

confidence: 97%

“…Initial centralized schemes required file sizes exponential in K to obtain constant worst case rate (we always assume ratio M/N is a constant in this work that does not scale with K). Subsequent works [13]- [18] have explored centralized schemes that attain sub-exponential file size and constant worst-case rate. Even linear file size for near-constant rates is feasible in theory although this requires impractically large values of K [19].…”

Section: Introductionmentioning

confidence: 99%

From Centralized to Decentralized Coded Caching

Chen¹,

Shanmugam²,

Dimakis³

2018

Preprint

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We consider the problem of designing decentralized schemes for coded caching. In this problem there are K users each caching M files out of a library of N total files. The question is to minimize R, the number of broadcast transmissions to satisfy all the user demands. Decentralized schemes allow the creation of each cache independently, allowing users to join or leave without dependencies. Previous work showed that to achieve a coding gain g, i.e. R ≤ K(1 − M/N )/g transmissions, each file has to be divided into number of subpackets that is exponential in g.In this work we propose a simple translation scheme that converts any constant rate centralized scheme into a random decentralized placement scheme that guarantees a target coding gain of g. If the file size in the original constant rate centralized scheme is subexponential in K, then the file size for the resulting scheme is subexponential in g. When new users join, the rest of the system remains the same. However, we require an additional communication overhead of O(log K) bits to determine the new user's cache state. We also show that the worst-case rate guarantee degrades only by a constant factor due to the dynamics of user arrival and departure.

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Low subpacketization schemes for coded caching

Cited by 22 publications

References 4 publications

Coded Caching in Multi-Rate Wireless Networks

Coded Caching in Multi-Rate Wireless Networks

Placement Delivery Array Design for Combination Networks with Edge Caching

From Centralized to Decentralized Coded Caching

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