Large Scale Multicast Large Scale Multicast over UDL over UDL Asian Institute of Technology Asian Institute of Technology
Satellite network & IP Satellite network & IP • Wide Area Coverage Wide Area Coverage • • Broadcast & High Bandwidth Broadcast & High Bandwidth • • One One- -way communication channel way communication channel • • Strengthen the broadcasting property Strengthen the broadcasting property • • Minimum bandwidth consumption Minimum bandwidth consumption •
Multicast Loss on Multicast Loss on Satellite UDL Study Satellite UDL Study Patcharee Basu, Kanchana Kanchanasut , Kanchana Kanchanasut Patcharee Basu intERLab intERLab AIT AIT
Objectives Objectives • Study loss pattern of receivers which shares Study loss pattern of receivers which shares • same UDL link same UDL link – Does they share same loss? How much Does they share same loss? How much – percentage? percentage? – Where loss happen? Satellite link or end systems? Where loss happen? Satellite link or end systems? –
AI3 UDL Testbed Testbed AI3 UDL •Asian Internet Interconnection Initiatives project (www.ai3.net), WIDE project • 9.6 Mbps C band satellite link • FEC ¾ at link layer • Feeder at Japan • Receivers at Thailand, Indonesia, Myanmar, Vietnam, Philippine, Malaysia, Lao
Experiment Network Experiment Network Unidirectional Satellite Link Feed router Receiving routers receiver receiver sender UDL Receiving networks UDL feeding networks
Experiment Environment Experiment Environment • One Multicast sender at Japan One Multicast sender at Japan • • 4 receivers <R1, R2, R3, R4> are in different 4 receivers <R1, R2, R3, R4> are in different • UDL sites<1 in Thailand, 2 in Indonesia, 1 in UDL sites<1 in Thailand, 2 in Indonesia, 1 in Malaysia >. Malaysia >. • Link Usage ~ 7Mbps Link Usage ~ 7Mbps • • 1 Mbps steady Sending Rate 1 Mbps steady Sending Rate • • 4 file sizes <1,10,50,100 MB> 4 file sizes <1,10,50,100 MB> •
Loss Percentage Loss Percentage 30 25 20 R1 R2 1 5 R3 R4 1 0 5 0 1 1 0 50 1 00 File s ize <MB>
Loss pattern <file size = 1 M> Loss pattern <file size = 1 M>
Loss pattern <file size = 10 M> Loss pattern <file size = 10 M>
Loss pattern <file size = 50 M> Loss pattern <file size = 50 M>
Loss pattern <file size = 100 M> Loss pattern <file size = 100 M>
Loss sharing Loss sharing Number of Number of 1 M 10 M 50 M 100 M 1 M 10 M 50 M 100 M receivers shared receivers shared loss loss 1 <not 100% 56.6% 99.8% 98% 1 <not 100% 56.6% 99.8% 98% shared> shared> 2 0% 0% 0.1% 1% 2 0% 0% 0.1% 1% 3 0% 0% 0% 0% 3 0% 0% 0% 0% 4 0% 43.3% 0.1% 1% 4 0% 43.3% 0.1% 1%
Conclusion Conclusion • Receivers do not have same loss pattern Receivers do not have same loss pattern • • Low percentage of shared loss Low percentage of shared loss • • Most losses happen on end Most losses happen on end- -systems systems • – Low signal Low signal – – Bad network equipments Bad network equipments – – Power outage Power outage – • Reliable multicast which works to correct Reliable multicast which works to correct • losses on end system is needed. losses on end system is needed.
Loss burstiness burstiness study study Loss • Burstiness Burstiness of satellite link of satellite link • – Physical layer, link layer Physical layer, link layer – – FEC at link layer FEC at link layer – • Burstiness Burstiness at network layer at network layer • – Error correction at lower layer Error correction at lower layer – – Router Router’ ’s queue management < s queue management <droptail droptail, RED> , RED> –
Testbed – – 3 channels 3 channels Testbed C-band KU#1 <6M> <1.5M> KU#2 <0.5M>
Experiment Environment Experiment Environment • 3 satellite links 3 satellite links • – 2 KU links(1.5Mbps. 0.5 Mbps) 2 KU links(1.5Mbps. 0.5 Mbps) – – 1 C links ( 6 Mbps) 1 C links ( 6 Mbps) – • Send/receive between routers Send/receive between routers • • 10,000 packets each hour, sending rate of 10 10,000 packets each hour, sending rate of 10 • packets per second. packets per second. • 60 hours 60 hours •
Burstiness Frequency Frequency Burstiness Bursty – – Loss length >=2 consecutive packets Loss length >=2 consecutive packets Bursty by frequency by frequency 14.29% 14.29% C C 28.09% 28.09% KU#1 KU#1 18.90% 18.90% KU#2 KU#2
Conclusion Conclusion • Most losses are not Most losses are not bursty bursty • – Implies congestion loss Implies congestion loss – • Congestion control is needed Congestion control is needed •
Unidirectional Link (UDL) Unidirectional Link (UDL)
UDL Characteristics UDL Characteristics • Available for remote geographical area • Available for remote geographical area • No return path • No return path – sender can not get any acknowledgement from the – sender can not get any acknowledgement from the receivers. receivers. • Communication signal may be dropped due to the • Communication signal may be dropped due to the atmospheric condition atmospheric condition
Data Dissemination Techniques Data Dissemination Techniques
Data Dissemination Techniques Data Dissemination Techniques • Digital Fountain • Digital Fountain – J. Byers, M. Luby Luby, M. , M. Mitzenmacher Mitzenmacher, A. , A. Rege Rege. A Digital Fountain Approach to Reliable . A Digital Fountain Approach to Reliable – J. Byers, M. Distribution of Bulk Data, Computer Communication Review Computer Communication Review , , a publication of ACM a publication of ACM Distribution of Bulk Data, SIGCOMM , February 1998. , February 1998. SIGCOMM • Broadcast Disk • Broadcast Disk – – S. S. Acharya Acharya, R. Alonso, M. Franklin, S. , R. Alonso, M. Franklin, S. Zdonik Zdonik. Broadcast Disks: Data Management for . Broadcast Disks: Data Management for Asymmetric Communication Environments. Asymmetric Communication Environments. Proceedings of the ACM SIGMOD Conference, Proceedings of the ACM SIGMOD Conference, San Jose San Jose, , CA CA , 1994. , 1994.
Digital Fountain Digital Fountain
Digital Fountain Digital Fountain • Derived from idea of FEC Derived from idea of FEC • • Using concept of Meta Using concept of Meta- -Content Content • • Different from FEC in term of Different from FEC in term of “ “No redundant No redundant • data” ” data • Any meta Any meta- -content that equal to original data content that equal to original data • can be reconstructed can be reconstructed
Digital Fountain Digital Fountain
Meta- -Content Content Meta • Packets are independently generated from Packets are independently generated from • content at any specified rate. content at any specified rate. • A bit A bit- -for for- -bit accurate copy of the original bit accurate copy of the original • content is quickly recovered from any number content is quickly recovered from any number of Meta- -Content packets that in aggregate is Content packets that in aggregate is of Meta equal to the length of the original content equal to the length of the original content
Broadcast Disk Broadcast Disk
Broadcast Disk Broadcast Disk • Proposed in 1994 Proposed in 1994 • • Represented each data as Represented each data as “ “Disk Disk” ” • • Multiplexed all data into the same link Multiplexed all data into the same link • • Periodic data broadcasting with priority Periodic data broadcasting with priority • • Higher priority data get the higher bandwidth Higher priority data get the higher bandwidth •
Broadcast Disk Broadcast Disk
Broadcast Disk Broadcast Disk Multiplex Multiplex Data#2: Powerpoint file Data#2: Powerpoint file Data#2: Powerpoint file Data#2: Powerpoint file Data#3: Msword – Quiz paper Data#4: Archived stream Data#3: Msword – Quiz paper Data#3: Msword – Quiz paper Data#4: Archived stream Data#3: Msword – Quiz paper Data#1: Realtime stream Data#1: Realtime stream Data#1: Realtime stream Data#1: Realtime stream channel7 Source Dest.
Broadcast Disk Broadcast Disk Demultiplex Demultiplex channel7 Source Dest. Data#1: Realtime stream Data#1: Realtime stream Data#1: Realtime stream Data#1: Realtime stream Data#1: Realtime stream Data#1: Realtime stream Data#1: Realtime stream Data#2: Powerpoint file Data#2: Powerpoint file Data#2: Powerpoint file Data#2: Powerpoint file Data#2: Powerpoint file Data#2: Powerpoint file Data#3: Msword – Quiz paper Data#4: Archived stream Data#3: Msword – Quiz paper Data#4: Archived stream Data#3: Msword – Quiz paper Data#4: Archived stream Data#3: Msword – Quiz paper Data#4: Archived stream Data#3: Msword – Quiz paper
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