On the Average Rate for Coded Caching with Heterogeneous User Profiles

Zhang, Ciyuan; Peleato, Borja

doi:10.1109/icc40277.2020.9148779

Cited by 18 publications

(13 citation statements)

References 13 publications

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“…Therefore, when there are more classes of users joining the computer communication network, Scheme 2 (split) is able to provide better video streaming service than other schemes and its performance is scarcely effected. Similar results for N c = 64, N u = 64 and M = 64 can be found in papers [19] and [23].…”

Section: Gnusupporting

confidence: 87%

“…Our previous conference paper [23] provided some partial and asymptotic results for uniform-average rate, but we have decided not to include those here, postponing them to future work on a separate paper.…”

Section: Resultsmentioning

confidence: 99%

“…The scenario with heterogeneous user profiles was thoroughly analyzed in [22], but just for the case of two users. Our prior work [23] studied the average rate resulting from the three schemes proposed in [19] and compared their asymptotic performance.…”

Section: Introductionmentioning

confidence: 99%

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Coded Caching with Heterogeneous User Profiles

Zhang¹,

Wang²,

Aggarwal³

et al. 2022

Preprint

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Coded caching utilizes pre-fetching during off-peak hours and multi-casting for delivery in order to balance the traffic load in communication networks. Several works have studied the achievable peak and average rates under different conditions: variable file lengths or popularities, variable cache sizes, decentralized networks, etc. However, very few have considered the possibility of heterogeneous user profiles, despite modern content providers are investing heavily in categorizing users according to their habits and preferences.This paper proposes three coded caching schemes with uncoded pre-fetching for scenarios where end users are grouped into classes with different file demand sets (FDS). One scheme ignores the difference between the classes, another ignores the intersection between them and the third decouples the delivery of files common to all FDS from those unique to a single class. The transmission rates of the three schemes are compared with a lower bound to evaluate their gap to optimality, and with each other to show that each scheme can outperform the other two when certain conditions are met.

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Section: Gnusupporting

confidence: 87%

Section: Resultsmentioning

confidence: 99%

See 1 more Smart Citation

Coded Caching with Heterogeneous User Profiles

Zhang¹,

Wang²,

Aggarwal³

et al. 2022

Preprint

Self Cite

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“…Furthermore, the work in [5] analyzed the peak load of three different coded caching schemes that account for the user preferences, and again revealed occasional performance gains that are similarly dependent on the structure of these preferences. Related analysis appears in [6], now for the average load of these same schemes in [5].…”

Section: A Heterogeneous User Profiles and Selfish Coded Cachingmentioning

confidence: 99%

“…Consider now another demand d 2 = (1234, 2345, 1235, 1245, 1345) with its corresponding FDS request graph shown in Figure 3. Since the graphs in Figure 2 and in Figure 3 are nonisomorphic 6 , the demand d 2 accepts a different delivery solution 7 than that for demand d 1 . Such phenomenon does not happen in the standard coded caching scenario, where indeed each demand would result in the same FDS request graph (cf.…”

Section: Shared Linkmentioning

confidence: 99%

Unselfish Coded Caching can Yield Unbounded Gains over Symmetrically Selfish Caching

Brunero,

Elia

2021

Preprint

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The original coded caching scenario assumes a content library that is of interest to all receiving users. In a realistic scenario though, the users may have diverging interests which may intersect to various degrees. What happens for example if each file is of potential interest to, say, 40 % of the users and each user has potential interest in 40 % of the library? In this work, we investigate the so-called symmetrically selfish coded caching scenario, where each user only makes requests from a subset of the library that defines its own File Demand Set (FDS), each user caches selfishly only contents from its own FDS, and where the different FDSs symmetrically overlap to some extent. In the context of various traditional prefetching scenarios (prior to the emergence of coded caching), selfish approaches were known to be potentially very effective. On the other hand -with the exception of some notable works -little is known about selfish coded caching. We here present a new information-theoretic converse that proves, in a general setting of symmetric FDS structures, that selfish coded caching, despite enjoying a much larger local caching gain and a much smaller set of possible demands, introduces an unbounded load increase compared to the unselfish case. In particular, in the K-user broadcast channel where each user stores a fraction γ of the library, where each file (class) is of interest to α users, and where any one specific file is of interest to a fraction δ of users, the optimal coding gain of symmetrically selfish caching is at least (K − α)γ + 1 times smaller than in the unselfish scenario. This allows us to draw the powerful conclusion that the optimal selfish coding gain is upper bounded by 1/(1 − δ), and thus does not scale with K. These derived limits are shown to be exact for different types of demands.

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