For a hierarchical network consisting of a server, multiple relays and multiple users, this paper studies on how to utilize cache at user and relay nodes to reduce the transmission delay. We propose novel coded caching schemes for the centralized and decentralized settings respectively. Our centralized scheme achieves better performance but requiring a fixing number of users, and our decentralized scheme supports flexible network change with only small loss of performance. Both schemes combine the traditional caching technology with network coding, and exploit the relays' cache resource to assist the transmission between the server and users. Moreover, our schemes allow parallel transmission between the server and relay, and achieve multicast gain by using coding during the delivery phase. The simulation results show that compared to the previous scheme, our schemes can greatly reduce the transmission delay without increasing the caching size.
WANG Ke
,
CHEN Jiahui
,
WU Youlong
. Coded caching in hierarchical network with centralized and decentralized strategy[J]. Journal of University of Chinese Academy of Sciences, 2022
, 39(2)
: 224
-231
.
DOI: 10.7523/j.ucas.2020.0017
[1] Cisco. Cisco visual networking index: global mobile data traffic forecast update, 2015-2020 white paper[R/OL]. 2016,Document ID 958959758.(2017-05-26) [2020-04-02]. http://www.cisco.com/c/en/us/solutions/service-provide/visual-networking-index-vni/index.html.
[2] Maddah-Ali M A, Niesen U. Fundamental limits of caching[J]. IEEE Transactions on Information Theory, 2014, 60(5): 2856-2867. DOI: 10.1109/TIT.2014.2306938.
[3] Maddah-Ali M A, Niesen U. Decentralized coded caching attains order-optimal memory-rate tradeoff[J]. IEEE/ACM Transactions on Networking, 2015, 23(4): 1029-1040. DOI:10.1109/TNET.2014.2317316.
[4] Karamchandani N, Niesen U, Maddah-Ali M A, et al. Hierarchical coded caching[J]. IEEE Transactions on Information Theory, 2016, 62(6): 3212-3229. DOI:10.1109/TIT.2016.2557804.
[5] Niesen U, Maddah-Ali M A. Coded caching with nonuniform demands[J]. IEEE Transactions on Information Theory, 2017, 63(2): 1146-1158.DOI:10.1109/TIT.2016.2639522.
[6] Shariatpanahi S P, Motahari S A, Khalaj B H. Multi-server coded caching[J]. IEEE Transactions on Information Theory, 2016, 62(12): 7253-7271.DOI:10.1109/TIT.2016.2614722.
[7] Li S Z, Maddah-Ali M A, Yu Q, et al. A fundamental tradeoff between computation and communication in distributed computing[J]. IEEE Transactions on Information Theory, 2018, 64(1): 109-128.DOI:10.1109/TIT.2017.2756959.
[8] Yan Q F, Cheng M Q, Tang X H, et al. On the placement delivery array design for centralized coded caching scheme[J]. IEEE Transactions on Information Theory, 2017, 63(9): 5821-5833.DOI:10.1109/TIT.2017.2725272.
[9] Shangguan C, Zhang Y W, Ge G N. Centralized coded caching schemes: a hypergraph theoretical approach[J]. IEEE Transactions on Information Theory, 2018, 64(8): 5755-5766.DOI:10.1109/TIT.2018.2847679.
[10] Yan Q F, Tang X H, Chen Q C, et al. Placement delivery array design through strong edge coloring of bipartite graphs[J]. IEEE Communications Letters, 2018, 22(2): 236-239.DOI:10.1109/LCOMM.2017.2765629.
[11] Saberali S A, Lampe L, Blake I F. Decentralized coded caching without file splitting[J]. IEEE Transactions on Wireless Communications, 2019, 18(2): 1289-1303.DOI:10.1109/TWC.2019.2891618.
[12] Ravindrakumar V, Panda P, Karamchandani N, et al. Private coded caching[J]. IEEE Transactions on Information Forensics and Security, 2018, 13(3): 685-694.DOI:10.1109/TIFS.2017.2765503.
[13] Kamel S, Sarkiss M, Wigger M, et al. Secrecy capacitymemory tradeoff of erasure broadcast channels[J]. IEEE Transactions on Information Theory, 2019, 65(8): 5094-5124.DOI:10.1109/TIT.2019.2902578.
[14] Tandon R. The capacity of cache aided private information retrieval[C]//2017 55th Annual Allerton Conference on Communication, Control, and Computing. October 3-6, 2017, Monticello, IL, USA. IEEE, 2017: 1078-1082.DOI:10.1109/ALLERTON.2017.8262857.