TY - GEN
T1 - Enhancing software-defined RAN with collaborative caching and scalable video coding
AU - Yu, Ruozhou
AU - Qin, Shuang
AU - Bennis, Mehdi
AU - Chen, Xianfu
AU - Feng, Gang
AU - Han, Zhu
AU - Xue, Guoliang
N1 - Funding Information:
This research was supported in part by NSF grant 1457262 (Yu and Xue), NSFC-61401076 and FRFCU-ZYGX2014J010 (Qin and Feng), TEKES grant 2364/31/2014 (Bennis), TEKES grant 2368/31/2014 (Chen), and NSF grant 1456921 and NSFC-61428101 (Han). The information reported here does not reflect the position or the policy of the federal governments.
Publisher Copyright:
© 2016 IEEE.
PY - 2016/7/12
Y1 - 2016/7/12
N2 - The ever increasing video demands from mobile users have posed great challenges to cellular networks. To address this issue, video caching in radio access networks (RANs) has been recognized as one of the enabling technologies in future 5G mobile networks, which brings contents near the end-users, reducing the transmission cost of duplicate contents, meanwhile increasing the Quality-of-Experience (QoE) of users. Inspired by the emerging software-defined networking technology, recent proposals have employed centralized collaborative caching among cells to further increase the caching capacity of the RAN. In this paper, we explore a new dimension in video caching in software-defined RANs to expand its capacity. We enable the controller with the capability to adaptively select the bitrates of videos received by users, in order to maximize the number and quality of video requests that can be served, meanwhile minimizing the transmission cost. To achieve this, we further incorporate Scalable Video Coding (SVC), which enables caching and serving sliced video layers that can serve different bitrates. We formulate the problem of joint video caching and scheduling as a reward maximization (cost minimization) problem. Based on the formulation, we further propose a 2-stage rounding-based algorithm to address the problem efficiently. Simulation results show that using SVC with collaborative caching greatly improves the cache capacity and the QoE of users.
AB - The ever increasing video demands from mobile users have posed great challenges to cellular networks. To address this issue, video caching in radio access networks (RANs) has been recognized as one of the enabling technologies in future 5G mobile networks, which brings contents near the end-users, reducing the transmission cost of duplicate contents, meanwhile increasing the Quality-of-Experience (QoE) of users. Inspired by the emerging software-defined networking technology, recent proposals have employed centralized collaborative caching among cells to further increase the caching capacity of the RAN. In this paper, we explore a new dimension in video caching in software-defined RANs to expand its capacity. We enable the controller with the capability to adaptively select the bitrates of videos received by users, in order to maximize the number and quality of video requests that can be served, meanwhile minimizing the transmission cost. To achieve this, we further incorporate Scalable Video Coding (SVC), which enables caching and serving sliced video layers that can serve different bitrates. We formulate the problem of joint video caching and scheduling as a reward maximization (cost minimization) problem. Based on the formulation, we further propose a 2-stage rounding-based algorithm to address the problem efficiently. Simulation results show that using SVC with collaborative caching greatly improves the cache capacity and the QoE of users.
KW - 5G mobile networks
KW - Scalable Video Coding
KW - Software-defined radio access network
KW - collaborative video caching
UR - http://www.scopus.com/inward/record.url?scp=84981328337&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84981328337&partnerID=8YFLogxK
U2 - 10.1109/ICC.2016.7511029
DO - 10.1109/ICC.2016.7511029
M3 - Conference contribution
AN - SCOPUS:84981328337
T3 - 2016 IEEE International Conference on Communications, ICC 2016
BT - 2016 IEEE International Conference on Communications, ICC 2016
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2016 IEEE International Conference on Communications, ICC 2016
Y2 - 22 May 2016 through 27 May 2016
ER -