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Journal articles on the topic 'Multicast Congestion Control'

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Published: 4 June 2021
Last updated: 6 September 2023

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1

Singh, Karan, and Rama Shankar Yadav. "Efficient Multicast Congestion Control." Wireless Personal Communications 78, no. 2 (May 4, 2014): 1159–76. http://dx.doi.org/10.1007/s11277-014-1809-9.

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2

Li, Jiang, Murat Yuksel, Xingzhe Fan, and Shivkumar Kalyanaraman. "Generalized multicast congestion control." Computer Networks 51, no. 6 (April 2007): 1421–43. http://dx.doi.org/10.1016/j.comnet.2006.07.014.

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3

Long, Yan. "Evaluation on Multicast Congestion Control Scheme." Advanced Materials Research 805-806 (September 2013): 1941–47. http://dx.doi.org/10.4028/www.scientific.net/amr.805-806.1941.

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This paper presents a evaluation on existing multicast congestion control schemes. We evaluate several recently proposed schemes to summarize state of the art in this field. Solutions to typical problems in multicast congestion control, especially those in layered multicast, such as layer granularity, loss path multiplicity and receiver coordination, are also studied to motivate further research.
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4

Duan, Yingjie, Hong Ni, Xiaoyong Zhu, and Xu Wang. "A Single-Rate Multicast Congestion Control (SRMCC) Mechanism in Information-Centric Networking." Future Internet 14, no. 2 (January 25, 2022): 38. http://dx.doi.org/10.3390/fi14020038.

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Information-centric networking (ICN) is expected to be a candidate for future internet architecture, and it supports features such as multicast that improves bandwidth utilization and transmission efficiency. However, multicast itself does not provide congestion control. When multiple multicast groups coexist, multicast traffic may exhaust all network resources, and cause network congestion and packet loss. Additionally, traditional IP multicast congestion control mechanisms cannot be directly applied to ICN architecture. Therefore, it is necessary to consider an effective congestion control mechanism for ICN multicast. This paper proposes a single-rate multicast congestion control mechanism, called SRMCC. It supports router-assisted awareness of the network congestion state and congestion control message aggregation. Moreover, the fair shared rate estimation method is innovatively proposed to achieve protocol fairness. Most importantly, it adjusts the rate according to different congestion states indicated by the queue occupancy ratio. By introducing a rate selection factor, it can achieve a balance between packet loss rate and throughput. Experimental results show that our proposal outperforms other mechanisms in throughput, packet loss rate, total bandwidth utilization, and overhead, and achieves protocol fairness and better TCP friendliness.
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5

Gan, Yung-Sze, and Chen-Khong Tham. "Loss differentiated multicast congestion control." Computer Networks 41, no. 2 (February 2003): 161–76. http://dx.doi.org/10.1016/s1389-1286(02)00372-9.

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6

Li, Jiang, Murat Yuksel, and Shivkumar Kalyanaraman. "Explicit rate multicast congestion control." Computer Networks 50, no. 15 (October 2006): 2614–40. http://dx.doi.org/10.1016/j.comnet.2005.09.026.

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7

Bai, Baochun, Janelle Harms, and Yuxi Li. "Configurable active multicast congestion control." Computer Networks 52, no. 7 (May 2008): 1410–32. http://dx.doi.org/10.1016/j.comnet.2007.12.010.

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8

Manjul, Manisha, Rajesh Mishra, and Joytsna  . "Link Utilization Based Multicast Congestion Control." Communications and Network 05, no. 03 (2013): 649–53. http://dx.doi.org/10.4236/cn.2013.53b2116.

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9

Chen, Hualiang, Zhongxin Liu, Zengqiang Chen, and Zhuzhi Yuan. "Extending TCP congestion control to multicast." Computer Networks 51, no. 11 (August 2007): 3090–109. http://dx.doi.org/10.1016/j.comnet.2007.01.004.

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10

Paschos, Georgios S., Chih-Ping Li, Eytan Modiano, Kostas Choumas, and Thanasis Korakis. "In-Network Congestion Control for Multirate Multicast." IEEE/ACM Transactions on Networking 24, no. 5 (October 2016): 3043–55. http://dx.doi.org/10.1109/tnet.2015.2503261.

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11

Byers, J. W., G. Horn, M. Luby, M. Mitzenmacher, and W. Shaver. "FLID-DL: congestion control for layered multicast." IEEE Journal on Selected Areas in Communications 20, no. 8 (October 2002): 1558–70. http://dx.doi.org/10.1109/jsac.2002.803998.

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12

Peng, J., and B. Sikdar. "Multilayer Multicast Congestion Control in Satellite Environments." IEEE Journal on Selected Areas in Communications 22, no. 3 (April 2004): 449–61. http://dx.doi.org/10.1109/jsac.2004.823408.

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13

Mu, Zhang, Huang Wei, and Zou Qian. "Performance Evaluation of Multicast Congestion Control Protocol." Journal of Computational and Theoretical Nanoscience 13, no. 9 (September 1, 2016): 5737–41. http://dx.doi.org/10.1166/jctn.2016.5480.

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14

Shapiro, J. K., D. Towsley, and J. Kurose. "Optimization-based congestion control for multicast communications." IEEE Communications Magazine 40, no. 9 (September 2002): 90–95. http://dx.doi.org/10.1109/mcom.2002.1031834.

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15

Lucas, Vincent, Jean-Jacques Pansiot, Dominique Grad, and Benoît Hilt. "Robust and fair Multicast Congestion Control (M2C)." Computer Networks 57, no. 3 (February 2013): 699–724. http://dx.doi.org/10.1016/j.comnet.2012.10.016.

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16

Azcorra, Arturo, Jose Ignacio Moreno, María Calderón, and Marifeli Sedano. "Multicast Congestion Control for Active Network Services." European Transactions on Telecommunications 10, no. 3 (May 1999): 309–17. http://dx.doi.org/10.1002/ett.4460100310.

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17

Mathad, Channabasayya, Paramesha Paramesha, and D. Srinivasa Rao. "Congestion Control for Fault Tolerant Multicast Routing in MANET." INTERNATIONAL JOURNAL OF COMPUTERS & TECHNOLOGY 15, no. 9 (June 24, 2016): 7041–48. http://dx.doi.org/10.24297/ijct.v15i9.194.

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Mobile Ad hoc Network (MANET) is a collection of two or more devices or nodes or terminals with wireless communications and networking capability that communicate with each other without the aid of any centralized administrator a dynamic network consisting of several mobile nodes communicating wirelessly. MANET is an infrastructure less network and each member node is free to move in and out of the network in a random manner. Congestion may occur in any node when data packets travel from source to destination. Controlling congestion is critical to ensure adequate network operation and performance. Due to this mobile nature of the nodes in MANET, the possibility for the network to get congested is high. This may result in isolated nodes and reduced network performance. So in this paper, we proposed to develop a congestion control technique for fault tolerant multicast routing in MANET. In this technique, the congestion probability around the forwarding node is initially estimated and then according to the congestion level, the future transmission rates are adapted. The data transmission rate is varied dynamically to efficiently handle the congestion in the network. In this way, the network performance is enhanced.
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18

TANISAWA, Yuki, and Miki YAMAMOTO. "Multicast Congestion Control with Quantized Congestion Notification in Data Center Networks." IEICE Transactions on Communications E97.B, no. 6 (2014): 1121–29. http://dx.doi.org/10.1587/transcom.e97.b.1121.

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19

XUE, Jian-sheng, Dong-hui FENG, Xu-hong SUN, and Bao-yan SONG. "DAMCC: Improved multi-rate multicast congestion control protocol." Journal of Computer Applications 29, no. 10 (December 17, 2009): 2599–602. http://dx.doi.org/10.3724/sp.j.1087.2009.02599.

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20

Sarkar, S., and L. Tassiulas. "Fair distributed congestion control in multirate multicast networks." IEEE/ACM Transactions on Networking 13, no. 1 (February 2005): 121–33. http://dx.doi.org/10.1109/tnet.2004.842234.

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21

Chen, Lijun, Tracey Ho, Mung Chiang, Steven H. Low, and John C. Doyle. "Congestion Control for Multicast Flows With Network Coding." IEEE Transactions on Information Theory 58, no. 9 (September 2012): 5908–21. http://dx.doi.org/10.1109/tit.2012.2204170.

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22

Tang, Ken, and Mario Gerla. "Congestion control multicast in wireless ad hoc networks." Computer Communications 26, no. 3 (February 2003): 278–88. http://dx.doi.org/10.1016/s0140-3664(02)00142-1.

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23

Singh, Karan, and Rama Shankar Yadav. "Multilayer Joining for Receiver Driven Multicast Congestion Control." Procedia Technology 4 (2012): 151–57. http://dx.doi.org/10.1016/j.protcy.2012.05.022.

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24

Gorinsky, Sergey, Sugat Jain, Harrick Vin, and Yongguang Zhang. "Robustness of multicast congestion control to inflated subscription." ACM SIGMETRICS Performance Evaluation Review 31, no. 1 (June 10, 2003): 312–13. http://dx.doi.org/10.1145/885651.781073.

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25

Widmer, Jörg, and Mark Handley. "Extending equation-based congestion control to multicast applications." ACM SIGCOMM Computer Communication Review 31, no. 4 (October 2001): 275–85. http://dx.doi.org/10.1145/964723.383081.

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26

Manjul, Manisha, Rajesh Mishra, Karan Singh, Le Hoang Son, Mohamed Abdel-Basset, and Pham Huy Thong. "Single rate based extended logarithmic multicast congestion control." Journal of Ambient Intelligence and Humanized Computing 11, no. 7 (June 12, 2019): 2779–91. http://dx.doi.org/10.1007/s12652-019-01340-z.

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27

Kulatunga, Chamil, and Gorry Fairhurst. "Enforcing layered multicast congestion control using ECN-nonce." Computer Networks 54, no. 3 (February 2010): 489–505. http://dx.doi.org/10.1016/j.comnet.2009.09.015.

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28

Xie, Feng, Gang Feng, and Chee Kheong Siew. "Study on nominee selection for multicast congestion control." Computer Communications 29, no. 9 (May 2006): 1458–69. http://dx.doi.org/10.1016/j.comcom.2005.09.006.

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29

Alexiou, Antonios, Christos Bouras, and Andreas Papazois. "A study of multicast congestion control for UMTS." International Journal of Communication Systems 22, no. 6 (June 2009): 739–54. http://dx.doi.org/10.1002/dac.997.

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30

Ardiansyah, Rizka. "Pengukuran Performa Algoritma Kendali Kongesti Active Queue Manajemen (AQM) Pada Jaringan Backbone Multicast Berbasis Protocol Multicast PIM-DM." ScientiCO : Computer Science and Informatics Journal 1, no. 2 (March 7, 2019): 71. http://dx.doi.org/10.22487/j26204118.2018.v1.i2.12061.

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UDP is a data transmission protocol on the Internet that allows data to be sent in realtime and become a development base of various services such as IPTV, VOIP, VOD, and video conferencing. The multicast network was a solution to provide better service to many public needs with the concept of simplicity and efficiency. Dense traffic situation triggering a packet loss and delay that not tolerated by some services, especially multimedia streaming service, while UDP does not guarantee the quality of service so that the necessary traffic management method that serves as a traffic controller to the congestion in the network. This study analyzes the performance of technology based on Active Queue Management (AQM) congestion control in a multicast backbone network based on Protocol Independent Multicast – Dense Multicast using Droptail, Deficit Round Robin (DRR), and Random Early Detection (RED) algorithm, which is simulated using NS2. The simulation results show that the congestion control algorithm, DRR provides the best performance with a balanced value of mean delay, mean throughput, and the mean loss. RED is a congestion control algorithm which has the best queue management mechanism but not able to suppress the mean loss in each scenario tested because RED has a small amount of buffer size, Droptail not an appropriate algorithm for multicast networks implemented in, the absence of an interrupt mechanism trigger data services will have a tendency towards a particular data packet.
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31

Duan, Yingjie, Hong Ni, and Xiaoyong Zhu. "Reliable Multicast Based on Congestion-Aware Cache in ICN." Electronics 10, no. 13 (June 30, 2021): 1579. http://dx.doi.org/10.3390/electronics10131579.

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Reliable multicast distribution is essential for some applications such as Internet of Things (IoT) alarm information and important file distribution. Traditional IP reliable multicast usually relies on multicast source retransmission for recovery losses, causing huge recovery delay and redundancy. Moreover, feedback implosion tends to occur towards multicast source as the number of receivers grows. Information-Centric Networking (ICN) is an emerging network architecture that is efficient in content distribution by supporting multicast and in-network caching. Although ubiquitous in-network caching provides nearby retransmission, the design of cache strategy greatly affects the performance of loss recovery. Therefore, how to recover losses efficiently and quickly is an urgent problem to be solved in ICN reliable multicast. In this paper, we first propose an overview architecture of ICN-based reliable multicast and formulate a problem using recovery delay as the optimization target. Based on the architecture, we present a Congestion-Aware Probabilistic Cache (CAPC) strategy to reduce recovery delay by caching recently transmitted chunks during multicast transmission. Then, we propose NACK feedback aggregation and recovery isolation scheme to decrease recovery overhead. Finally, experimental results show that our proposal can achieve fully reliable multicast and outperforms other approaches in recovery delay, cache hit ratio, transmission completion time, and overhead.
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32

BONASTRE, O. M., S. NEVILLE, and C. E. PALAU. "MULTICAST CONGESTION CONTROL SRMSH APPROACH USING COMMUNICATING REAL-TIME STATE MACHINES." International Journal of Bifurcation and Chaos 20, no. 09 (September 2010): 2965–73. http://dx.doi.org/10.1142/s0218127410027519.

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New real-time applications frequently involve timing constraints related to accurate services from communication protocols. Concretely, real-time communication protocols utilize timers to implement these constraints between system event occurrences. In this context, the study of congestion control for Internet reliable multicast is at present an active research field related to real-time protocols. In this paper, the authors present an innovative real-time transport protocol named Scalable Reliable Multicast Stair Hybrid (SRMSH) as new hybrid multiple layer mechanism for multicast congestion control providing detection and recovery loss. This work is focused on formal specification of SRMSH approach using Communicating Real-Time State Machines as a formal method. Besides, SRMSH validation is presented within a formal proof framework in order to check the functional safety and liveness properties. As a result, authors outline a dynamical system framework in order to model behavior of their presented solution.
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33

Rakrak, Fathia Ouakasse, Said. "Congestion Control in Unicast and Multicast CoAP-based Communications." International Journal of Advanced Engineering Research and Science 8, no. 10 (2021): 167–73. http://dx.doi.org/10.22161/ijaers.810.18.

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34

Yuan Gao, J. C. Hou, and S. Paul. "RACCOOM: a rate-based congestion control approach for multicast." IEEE Transactions on Computers 52, no. 12 (December 2003): 1521–34. http://dx.doi.org/10.1109/tc.2003.1252849.

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35

Rhee, Injong, Nallathambi Balaguru, and George N. Rouskas. "MTCP: scalable TCP-like congestion control for reliable multicast." Computer Networks 38, no. 5 (April 2002): 553–75. http://dx.doi.org/10.1016/s1389-1286(01)00268-7.

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36

Wu, Eric Hsiao-Kuang, and Wei-Ren Yang. "Pragmatic general multicast congestion control protocol for wireless networks." Wireless Communications and Mobile Computing 5, no. 4 (2005): 487–99. http://dx.doi.org/10.1002/wcm.305.

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37

Rodríguez Pérez, M., S. Herrería Alonso, M. Fernández Veiga, and C. López García. "An adaptive multirate congestion control protocol for multicast communications." Computer Communications 29, no. 12 (August 2006): 2247–60. http://dx.doi.org/10.1016/j.comcom.2006.03.008.

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38

Chumchu, Prawit, Roksana Boreli, and Aruna Seneviratne. "A Model-based Scalable Reliable Multicast Transport Protocol for Satellite Networks." Journal of Communications Software and Systems 1, no. 1 (April 6, 2017): 24. http://dx.doi.org/10.24138/jcomss.v1i1.313.

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In this paper, we design a new scalable reliable multicast transport protocol for satellite networks (RMT). This paper is the extensions of paper in [18]. The proposed protocoldoes not require inspection and/or interception of packets at intermediate nodes. The protocol would not require anymodification of satellites, which could be bent-pipe satellites or onboard processing satellites. The proposed protocol is divided in 2 parts: error control part and congestion control part. In error control part, we intend to solve feedback implosion and improve scalability by using a new hybrid of ARQ (Auto Repeat Request) and adaptive forward error correction (AFEC). The AFEC algorithm adapts proactive redundancy levels following the number of receivers and average packet loss rate. This leads to a number of transmissions and the number of feedback signals are virtually independent of the number of receivers. Therefore, wireless link utilization used by the proposed protocol is virtually independent of the number of multicast receivers. In congestion control part, the proposed protocol employs a new window-based congestion control scheme, which is optimized for satellite networks. To be fair to the other traffics, the congestion control mimics congestion control in the wellknown Transmission Control Protocol (TCP) which relies on “packet conservation” principle. To reduce feedback implosion, only a few receivers, ACKers, are selected to report the receiving status. In addition, in order to avoid “drop-to-zero” problem, we use a new simple wireless loss filter algorithm. This loss filter algorithm significantly reduces the probability of the congestion window size to be unnecessarily reduced because of common wireless losses. Furthermore, to improve achievable throughput, we employ slow start threshold adaptation based on estimated bandwidth. The congestion control also deals with variations in network conditions by dynamically electing ACKers.
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39

Xie, F., G. Feng, and C. K. Siew. "Joint local delivery and congestion control framework for reliable multicast." IEE Proceedings - Communications 152, no. 2 (2005): 177. http://dx.doi.org/10.1049/ip-com:20041151.

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40

Ye, Xiaoguo. "ANLMCC—An Active Network-Based Layered Multicast Congestion Control Scheme." Journal of Computer Research and Development 42, no. 2 (2005): 273. http://dx.doi.org/10.1360/crad20050214.

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41

Seada, K., A. Helmy, and S. Gupta. "A Framework for Systematic Evaluation of Multicast Congestion Control Protocols." IEEE Journal on Selected Areas in Communications 22, no. 10 (December 2004): 2048–61. http://dx.doi.org/10.1109/jsac.2004.836013.

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42

Bhattacharyya, S., D. Towsley, and J. Kurose. "A novel loss indication filtering approach for multicast congestion control." Computer Communications 24, no. 5-6 (March 2001): 512–24. http://dx.doi.org/10.1016/s0140-3664(00)00299-1.

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43

Huang, Jau-Hsiung, Chun-Chuan Yang, and Nai-Cheng Fang. "A novel congestion control mechanism for multicast real-time connections." Computer Communications 22, no. 1 (January 1999): 56–72. http://dx.doi.org/10.1016/s0140-3664(98)00260-6.

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44

Singh, Karan, and Rama Shankar Yadav. "Efficient Joining and Leaving for Receiver Driven Multicast Congestion Control." International Journal of Computer Applications 1, no. 26 (February 25, 2010): 120–26. http://dx.doi.org/10.5120/471-777.

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45

Matrawy, Ashraf, and Ioannis Lambadaris. "A survey of congestion control schemes for multicast video applications." IEEE Communications Surveys & Tutorials 5, no. 2 (2003): 22–31. http://dx.doi.org/10.1109/comst.2003.5341336.

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46

Kammoun, Wafa, and Habib Youssef. "Equation-based end-to-end single-rate multicast congestion control." annals of telecommunications - annales des télécommunications 65, no. 3-4 (February 16, 2010): 219–31. http://dx.doi.org/10.1007/s12243-010-0159-1.

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47

Sarkar, S., and L. Tassiulas. "A framework for routing and congestion control for multicast information flows." IEEE Transactions on Information Theory 48, no. 10 (October 2002): 2690–708. http://dx.doi.org/10.1109/tit.2002.802619.

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48

Deb, S., and R. Srikant. "Congestion Control for Fair Resource Allocation in Networks With Multicast Flows." IEEE/ACM Transactions on Networking 12, no. 2 (April 2004): 274–85. http://dx.doi.org/10.1109/tnet.2004.826293.

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49

Xie, Feng, Gang Feng, and Chee Kheong Siew. "The Impact of Loss Recovery on Congestion Control for Reliable Multicast." IEEE/ACM Transactions on Networking 14, no. 6 (December 2006): 1323–35. http://dx.doi.org/10.1109/tnet.2006.886322.

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50

YE, Xiao-Guo. "A Congestion Control Algorithm for Layered Multicast Based on Differentiated Services." Journal of Software 17, no. 7 (2006): 1609. http://dx.doi.org/10.1360/jos171609.

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