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Optimal Fairness Scheduling for Coded Caching in Multi-AP Wireless Local Area Networks

Kagan Akcay, MohammadJavad Salehi, Giuseppe Caire

TL;DR

This work considers CC for on-demand video streaming over WLANs where multiple users are served simultaneously by multiple spatially distributed access points (AP) and considers the region of achievable long-term average delivery rate and the per-user rate distribution under proportional fairness scheduling.

Abstract

Coded caching (CC) schemes exploit the cumulative cache memory of the users and simple linear coding to turn unicast traffic (individual file requests) into a multicast transmission. For the originally proposed $K$-user single-server/single shared link network model, CC yields an $O(K)$ gain with respect to conventional uncoded caching with the same per-user memory. While several information-theoretic optimality results for a variety of problems and carefully crafted network topologies have been proved, the gains and suitability of CC for practical scenarios such as content streaming over existing wireless networks have not yet been fully demonstrated. In this work, we consider CC for on-demand video streaming over WLANs where multiple users are served simultaneously by multiple spatially distributed access points (AP). Users sequentially request video ``chunks". The CC scheme operates above the IP layer, leaving the underlying standard physical layer and MAC layer untouched. The cache placement is completely asynchronous and decentralized, and the users are placed at random over the network coverage area. For such a system, we consider the region of achievable long-term average delivery rate (defined as the number of video chunks delivered per unit of time) and study the per-user rate distribution under proportional fairness scheduling. We also consider reduced complexity scheduling strategies and compare them with standard state-of-the-art techniques such as conventional (uncoded) caching and collision avoidance by allocating APs on different sub-channels (i.e., frequency reuse).

Optimal Fairness Scheduling for Coded Caching in Multi-AP Wireless Local Area Networks

TL;DR

This work considers CC for on-demand video streaming over WLANs where multiple users are served simultaneously by multiple spatially distributed access points (AP) and considers the region of achievable long-term average delivery rate and the per-user rate distribution under proportional fairness scheduling.

Abstract

Coded caching (CC) schemes exploit the cumulative cache memory of the users and simple linear coding to turn unicast traffic (individual file requests) into a multicast transmission. For the originally proposed -user single-server/single shared link network model, CC yields an gain with respect to conventional uncoded caching with the same per-user memory. While several information-theoretic optimality results for a variety of problems and carefully crafted network topologies have been proved, the gains and suitability of CC for practical scenarios such as content streaming over existing wireless networks have not yet been fully demonstrated. In this work, we consider CC for on-demand video streaming over WLANs where multiple users are served simultaneously by multiple spatially distributed access points (AP). Users sequentially request video ``chunks". The CC scheme operates above the IP layer, leaving the underlying standard physical layer and MAC layer untouched. The cache placement is completely asynchronous and decentralized, and the users are placed at random over the network coverage area. For such a system, we consider the region of achievable long-term average delivery rate (defined as the number of video chunks delivered per unit of time) and study the per-user rate distribution under proportional fairness scheduling. We also consider reduced complexity scheduling strategies and compare them with standard state-of-the-art techniques such as conventional (uncoded) caching and collision avoidance by allocating APs on different sub-channels (i.e., frequency reuse).
Paper Structure (10 sections, 5 equations, 3 figures, 2 tables, 1 algorithm)

This paper contains 10 sections, 5 equations, 3 figures, 2 tables, 1 algorithm.

Figures (3)

  • Figure 1: Example network with $H=2$, $K=5$, $L = 3$, and $t=1$.
  • Figure 2: CDF for changing $L$, $U=10$, analytical solution, $\frac{M}{N} = 0.2$, Time is calculated assuming a full video chunk can be transmitted in one second.
  • Figure 3: CDF for changing $U$, $L=5$, $\frac{M}{N}$ = 0.2.

Theorems & Definitions (6)

  • Example 1
  • Example 2
  • Example 3
  • Example 4
  • Remark 1
  • Example 5