Analysis and Optimization of Caching for Content Delivery in - PowerPoint PPT Presentation

1896 1920 1987 2006 Analysis and Optimization of Caching for Content Delivery in Wireless Networks Ying Cui Department of Electronic Engineering Shanghai Jiao Tong University, China 1

Outline • Introduction • Caching at BSs – joint caching and multicasting [Cui16], [Wang17], [Xing17] – joint caching and BS cooperation [Jiang17], [Wen17] • Caching at end users – coded caching and multicasting [Jin17] – joint pushing and caching [Sun17] • Conclusion 2

INTRODUCTION 3

Shift of Wireless Commun. Services • Connection-oriented to content-oriented services 4

Mobile Data Traffic Growth • Dramatic growth of mobile data traffic [Cisco2017] – sevenfold increase 2016 -> 2021 – mobile video 78% of mobile data traffic by 2021 • Cause significant stress on wireless networks 5

Two Classic Approaches • Increase access rates • Increase densification of network infrastructure • Disadvantage – cannot alleviate backhaul burden 6

Data Reuse • Widely different file popularity – 5 –10 percent of “popular” contents are consumed by the majority of mobile users • Reusable content – 70 percent of wireless traffic is from videos – users watch most recently released video content 7

Promising Approaches • Content caching at wireless edge – reduce delay, backhaul burden and load of wireless links – caching at BSs and caching at end users • Cache-assisted multicast to concurrently serve multiple users – reduce traffic load of wireless links – based on cache content at BSs and end users • Cache-assisted BS cooperation to jointly serve each user by multiple BSs storing same content – increase transmission rate over wireless links – based on cache content at BSs 8

Benefits of Caching • Reduce response time – bring popular contents closer to mobile user 9

Benefits of Caching • Alleviate traffic loads – on the core networks and backhaul (caching at BSs and users) – over-the-air wireless traffic (caching at users) 10

Benefits of Caching • Smoothen traffic – gathering data during idle timeslots – shift traffic from peak to off-peak hours 11

Our Work (2015-2017) • [Cui16] Ying Cui , D. Jiang and Y. Wu, "Analysis and optimization of caching and multicasting in cache- enabled wireless networks," IEEE Trans. Wireless Commun. , vol. 15, no. 7, pp. 5101-5112, 2016. ( IEEE GLOBECOM , 2015) • [Cui17] Ying Cui and D. Jiang, "Analysis and optimization of caching and multicasting in cache-enabled heterogeneous wireless networks," IEEE Trans. Wireless Commun. , vol. 16, no. 1, pp. 250-264, 2017. ( IEEE GLOBECOM , 2016) • [Cui16’] Ying Cui , F. Lai, S. Hanly and P. Whiting, "Optimal caching and user association in cache-enabled Caching at BSs heterogeneous wireless networks," IEEE GLOBECOM 2016. • [Wang17] Z. Wang, Z. Cao, Ying Cui and Y. Yang, “ Joint and Competitive Caching Designs in Large-Scale Multi- Tier Wireless Multicasting Networks,” major revision, IEEE Trans. Commun. , 2017. ( IEEE GLOBECOM , 2017) • [Wen17] W. Wen, Ying Cui , F. Zheng and S. Jin, "Random caching based cooperative transmission in heterogeneous wireless networks,” major revision, IEEE Trans. Commun. , 2017. ( IEEE ICC , 2017) • [Jiang17] D. Jiang and Ying Cui , "Partition-based caching in large-scale SIC- enabled wireless networks,” minor revision, IEEE Trans. Wireless Commun. , 2017. ( IEEE ICC , 2017) • [Xing17] J. Xing, Ying Cui and V. Lau, "Temporal-spatial aggregation for cache-enabled wireless multicasting networks with asynchronous content requests," submitted to IEEE Trans. Wireless Commun. , Caching at users 2017. ( IEEE GLOBECOM , 2017) • [Jin16] S. Jin, Ying Cui , H. Liu and G. Caire, "New Order-optimal decentralized coded caching schemes with good performance in finite file size regime," submitted to IEEE Trans. Information Theory, 2016. ( IEEE GLOBECOM , 2016) • [Jin17] S. Jin, Ying Cui , H. Liu and G. Caire, "Structural properties of uncoded placement optimization for coded delivery," submitted to IEEE Trans. Information Theory, 2017. • [Sun17] Y. Sun, Ying Cui and H. Liu, "Joint pushing and caching for bandwidth utilization maximization in wireless networks," submitted to IEEE Trans. Commun. , 2017. ( IEEE GLOBECOM , 2017) 12

Collaborators • Professors – Giuseppe Caire, Technical University of Berlin, Germany – Vincent Lau, Hong Kong University of Science and Technology, Hong Kong – Stephen Hanly and Philip Whiting, Macquarie University, Australia – Hui Liu, Shanghai Jiao Tong University, China – Shi Jin and Fuchun Zheng, Southeast University, China • Students – Dongdong Jiang, Yaping Sun, Jifang Xing, Sian Jin, Zitian Wang, Zhehan Cao and Fan Lai, Shanghai Jiao Tong University, China – Wanli Wen, Southeast University, China 13

CACHING AT BASE STATIONS IN LARGE-SCALE WIRELESS NETWORKS 14

Our Work • [Cui16] Ying Cui , D. Jiang, and Y. Wu, “Analysis and optimization of caching and multicasting in large-scale cache- enabled wireless networks,” IEEE Trans. Wireless Commun., vol. 15, no. 7, pp. 5101 – 5112, Jul. 2016. • [Xing17] J. Xing, Ying Cui and V. Lau, "Temporal-spatial aggregation for cache-enabled wireless multicasting networks with asynchronous content requests," submitted to IEEE Trans. Wireless Commun., 2017. • [Wang17] Z. Wang, Z. Cao, Ying Cui and Y. Yang, "Joint and competitive caching designs in large-scale multi-tier wireless multicasting networks," submitted to IEEE Trans. Commun., 2017. • [Jiang17] D. Jiang and Ying Cui , "Partition-based caching in large-scale SIC-enabled wireless networks," submitted to IEEE Trans. Wireless Commun., 2017 • [Wen17] W. Wen, Ying Cui , F. Zheng, S. Jin and Y. Jiang, "Random caching based cooperative transmission in heterogeneous wireless networks," submitted to IEEE Trans. Wireless Commun., 2017. 15

Caching, Multicasting and Cooperation random caching & multicasting [Cui16] single-tier network caching random caching & aggregation-based multicasting [Xing17] & multicasting two-tier joint/competitive random caching & multicasting HetNet [Wang17] single-tier partition-based caching & non-orthogonal transmission caching network [Jiang17] & two-tier cooperation random caching & non-coherent joint transmission HetNet [Wen17] 16

General Model of Large-Scale Wireless Networks • BSs operate at same frequency • Random locations of BSs and users – locations of BSs in tier j : PPP with density 𝜇 j independent – locations of MSs: PPP with density 𝜇 u • Downlink transmission – each BS one transmit antenna – each BS in tier j transmit power P j , bandwidth W – each MS one receive antenna • Fading – pathloss D - α : D -distance, α -pathloss exponent – small scale fading CN(0,1) 17

Content and Cache • 𝑂 files in the network – same file size – file popularity • identical among users • Each BS in tier j has a cache of size  K N j   N – : combinations of 𝐿 𝑘 different files   I K   j • Joint caching and multicasting • Joint caching and cooperation 18

Analysis and Optimization Framework parameter-based caching, multicasting and cooperation parameters: caching dist., file partition, etc. performance metric: successful transmission probability ( STP ) STP analysis STP maximization (for given parameters) (optimize parameters) general region non-convex prob. locally opt. [Cui16], [Xing17], [Wang17] solution tractable mixed disc.-cont. prob. (MDCP) expression near opt. [Wen17] solution multiple choice knapsack prob. stochastic geometry (MCKP) [Jinag17] asymp. region (e.g., SNR, user density, convex prob. [Cui16], [Xing17] closed-form file size, target rate) opt. solution discrete prob. [Jinag17] closed-form locally opt. expression MDCP [Wen17] solution asymp. approximation non-convex prob. [Wang17] 19

Obvious benefit of multicast over unicast in high user density region ! ANALYSIS AND OPTIMIZATION OF CACHING AND MULTICASTING IN LARGE-SCALE WIRELESS NETWORKS 20

Random Caching and Multicasting in Large- Scale Single-Tier Wireless Networks [Cui16] Ying Cui , D. Jiang and Y. Wu, "Analysis and optimization of caching and multicasting in cache-enabled wireless networks ," IEEE Trans. Wireless Commun. , vol. 15, no. 7, pp. 5101-5112, 2016. ( IEEE GLOBECOM , 2015) 21

Random Caching and Multicasting • Random caching specified by caching dist.  – each BS stores comb. 𝑗 wp.    [0,1], , 1 p i p file joint dist. i i    i diversity – each BS stores file n wp.   ， , T p n T K n i n   i n marginal dist. • Content-centric user association n – user requesting file n connects to nearest BS storing – serving BS may not be nearest BS • Multicasting – BS j receiving K j different file requests from its users multicasts each of these files at rate τ over bandwidth W/K j • resource sharing among different files   • STP of a typical user:    W        ( ) ( ), ( ) Pr log 1 SINR q p a q p q p , , 2 ,0 K n K n K n n    K   n n ,0 – K n,0 : file load of serving BS of a typical user requesting file n 22