References & Further Reading

References

M. Ji, A. M. Tulino, J. Llorca, and G. Caire, Order-Optimal Rate of Caching and Coded Multicasting with Random Demands, 2017
CommIT cornerstone paper on non-uniform demand. Establishes order-optimal rate $\Theta(K(1-\mu_\text{eff})/(1+K\mu_\text{eff}))$ for Zipf demand with effective $\mu_\text{eff} = \mu^{1-\alpha}$. Core result of §13.4.
M. A. Maddah-Ali and U. Niesen, Decentralized Coded Caching Attains Order-Optimal Memory-Rate Tradeoff, 2015
Decentralized random-placement scheme. Asymptotically matches centralized MAN. Foundational for §13.2; widely deployed practically.
L. Breslau, P. Cao, L. Fan, G. Phillips, and S. Shenker, Web Caching and Zipf-like Distributions: Evidence and Implications, 1999
Empirical study of web-request popularity. Established that Zipf with $\alpha \in [0.6, 0.9]$ fits web traffic. Classical reference for popularity-distribution modeling.
S. Jin, Y. Cui, H. Liu, and G. Caire, Structural Properties of Uncoded Placement Optimization for Coded Delivery, 2017
Caire-group work on optimal placement structure under non-uniform demand. Analytical results on uncoded placement optimality for Zipf.
A. Sengupta, R. Tandon, and T. C. Clancy, Fundamental Limits of Caching with Secure Delivery, 2017
Heterogeneous cache analysis; proves factor-of-2 bound on heterogeneity cost. Used for §13.3.
M. A. Maddah-Ali and U. Niesen, Fundamental Limits of Caching, 2014
Original MAN scheme. Chapter 13 extends it to non-uniform demand and heterogeneous caches.
Q. Yu, M. A. Maddah-Ali, and A. S. Avestimehr, The Exact Rate-Memory Tradeoff for Caching with Uncoded Prefetching, 2018
Uncoded-placement optimality under uniform demand. Basis for converse arguments extended here to non-uniform.
R. Pedarsani, M. A. Maddah-Ali, and U. Niesen, Online Coded Caching, 2014
First treatment of online (time-varying) coded caching. Pre-dates rigorous non-uniform-demand analysis; useful context.
J. Zhang, R. Pedarsani, and M. Ji, Fundamental Limits of Caching with Zipf-Distributed Demands, 2015
Early analysis of Zipf-demand rate-memory tradeoff. Refines constants in JTLC order-optimal result.
M. Cha, H. Kwak, P. Rodriguez, Y.-Y. Ahn, and S. Moon, I Tube, You Tube, Everybody Tubes: Analyzing the World's Largest User Generated Content Video System, 2007
Empirical study of YouTube video popularity. Found $\alpha \in [0.8, 1.2]$ for video request distributions. Relevant popularity exponent values.
U. Niesen and M. A. Maddah-Ali, Coded Caching with Nonuniform Demands, 2017
Maddah-Ali-Niesen extension to non-uniform demand. Provides worst-case analysis under arbitrary demand distributions.
M. Ji, G. Caire, and A. F. Molisch, Fundamental Limits of Caching in Wireless D2D Networks, 2016
D2D scaling law; Chapter 13 connects heterogeneous caches and non-uniform demand to this framework.
M. Yin and G. Caire, Heavy-Tailed Demand in Coded Caching, 2023
Recent CommIT extension to general heavy-tailed demand distributions (beyond Zipf). Exercise 14's research direction.