Optimal Resource Allocation for Loss-Tolerant Multicast Video Streaming

被引:1
作者
ul Zuhra, Sadaf [1 ]
Besser, Karl-Ludwig [1 ]
Chaporkar, Prasanna [2 ]
Karandikar, Abhay [2 ,3 ]
Poor, H. Vincent [1 ]
机构
[1] Princeton Univ, Dept Elect & Comp Engn, Princeton, NJ 08544 USA
[2] Indian Inst Technol, Dept Elect Engn, Mumbai 400076, India
[3] Indian Inst Technol Kanpur, Kanpur, India
基金
美国国家科学基金会;
关键词
multicast; video streaming; loss tolerance; MBMS; resource allocation; ALGORITHMS;
D O I
10.3390/e25071045
中图分类号
O4 [物理学];
学科分类号
0702 ;
摘要
In video streaming applications, especially during live streaming events, video traffic can account for a significant portion of the network traffic and can lead to severe network congestion. For such applications, multicast provides an efficient means to deliver the same content to a large number of users simultaneously. However, in multicast, if the base station transmits content at rates higher than what can be decoded by users with the worst channels, these users will experience outages. This makes the multicast system's performance dependent on the weakest users in the system. Interestingly, video streams can tolerate some packet loss without a significant degradation in the quality experienced by the users. This property can be leveraged to improve the multicast system's performance by reducing the dependence of the multicast transmissions on the weakest users. In this work, we design a loss-tolerant video multicasting system that allows for some controlled packet loss while satisfying the quality requirements of the users. In particular, we solve the resource allocation problem in a multimedia broadcast multicast services (MBMS) system by transforming it into the problem of stabilizing a virtual queuing system. We propose two loss-optimal policies and demonstrate their effectiveness using numerical examples with realistic traffic patterns from real video streams. It is shown that the proposed policies are able to keep the loss encountered by every user below its tolerable loss. The proposed policies are also able to achieve a significantly lower peak SNR degradation than the existing schemes.
引用
收藏
页数:24
相关论文
共 36 条
[1]   Multicast Scheduling and Resource Allocation Algorithms for OFDMA-Based Systems: A Survey [J].
Afolabi, Richard O. ;
Dadlani, Aresh ;
Kim, Kiseon .
IEEE COMMUNICATIONS SURVEYS AND TUTORIALS, 2013, 15 (01) :240-254
[2]  
[Anonymous], 2023, 26247 3GPP TS
[3]  
[Anonymous], 2023, 3GPP TS 38.214
[4]  
[Anonymous], 2009, 36213 3GPP TS
[5]   Multicast Optimization for Video Delivery in Multi-RAT Networks [J].
Basaras, Pavlos ;
Iosifidis, George ;
Kucera, Stepan ;
Claussen, Holger .
IEEE TRANSACTIONS ON COMMUNICATIONS, 2020, 68 (08) :4973-4985
[6]   Network-Based H.264/AVC Whole-Frame Loss Visibility Model and Frame Dropping Methods [J].
Chang, Yueh-Lun ;
Lin, Ting-Lan ;
Cosman, Pamela C. .
IEEE TRANSACTIONS ON IMAGE PROCESSING, 2012, 21 (08) :3353-3363
[7]   Wireless multicast: Theory and approaches [J].
Chaporkar, P ;
Sarkar, S .
IEEE TRANSACTIONS ON INFORMATION THEORY, 2005, 51 (06) :1954-1972
[8]   Dynamic Resource Allocation for Scalable Video Multirate Multicast Over Wireless Networks [J].
Chen, Shuangwu ;
Yang, Bowen ;
Yang, Jian ;
Hanzo, Lajos .
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, 2020, 69 (09) :10227-10241
[9]  
Cormen TH., 2009, INTRO ALGORITHMS
[10]   Resource Allocation for Layered Multicast Video Streaming in NOMA Systems [J].
Dani, Muhammad Norfauzi ;
So, Daniel K. C. ;
Tang, Jie ;
Ding, Zhiguo .
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, 2022, 71 (11) :11379-11394