Multicast Pre-Distribution in VoD Services Noriaki Kamiyama, Ryoichi Kawahara, Tatsuya Mori,...
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Transcript of Multicast Pre-Distribution in VoD Services Noriaki Kamiyama, Ryoichi Kawahara, Tatsuya Mori,...
Multicast Pre-Distribution in VoD Services
Noriaki Kamiyama, Ryoichi Kawahara,
Tatsuya Mori, Haruhisa Hasegawa
NTT Service Integration Laboratories
2011. 5. 11
Problem in VoD System
Demand in VoD concentrates at night and changes widely on daily basis.
2
Need to design VoD system based on demand at peak hours to maintain stable service quality
Important for ISPs to reduce server and network load at peak hours to suppress network cost
12/1Date
0
5
10
15
20
25
Max
imum
act
ive
sess
ion
coun
t in
each
hou
r [1
02 ]
2 3 4 5 6 7
Max. active session count in each hour for seven days from Dec. 1, 2004 in VoD service of China Telecom
Demand at peak hours is five times larger than that at off-peak hours.
Multicast Pre-Distribution (MPD) VoD
Users are provided huge amount of access link bandwidth much larger than playback rate.
Large part of downlink bandwidth remains unused.
Effective to always deliver content and store them at STBs independently of user requests
Video server can freely select delivery content and freely set time at which each content is delivered.
Delivers some popular content to all users in multicast session
Propose MPD VoD system
3
Overview of MPD VoD Video server always pre-distributes popular content to
all users, and STBs store all of them. Determines pre-distribution schedule on daily basis Users can watch pre-distributed content without
generating load at server and network at request. Delivers content on-demand in unicast session for
requests of content not pre-distributed
4
Server
NetworkSTB
TV
Multicast pre-distribution
On-demand unicast delivery
Watching pre-distributed content
Assumptions
Set transmission rate of each MPD channel as
Rb = Ad – R (Ad: downlink capacity, R: playback rate)
Video server makes pre-distribution schedule for 24 hours in n-th day at beginning of n-th day (0:00)
To preserve copyright of content, remove pre-distributed content from STBs at 0:00 after L days elapse
5
Selecting Pre-distributed Content
To improve reduction effect of server and network load in n-th day, desirable to pre-distribute content m with large Dm,n, total download time (TDLT) for content m in n-th day
Estimates Dm,n using EMA (exponential moving average):
Dm,n = Dm,n-1 + (1 - )Dm,n-1 (: smoothing parameter)
Except content pre-distributed between (n-L)-th day and (n-1)-th day, selects content in descending order of Dm,n
Pre-distributes selected content in descending order of estimated request count Dm,n/Sm (Sm: length of content m)
6
Access Log Data Used in Evaluation
Access log data in PowerInfo VoD system, commercial VoD service of China Telecom
Seven months from 2004/6/1 to 2004/12/31 Request count: 20,921,657, content count: 6,735 User count: 37,360, average content size: 3,510 seconds
7
10-1
1
1 10 102
CC
D
Content size (minutes)
10-2
10-3
10-4
Average TDLT per day (hours)
CC
D
Users Content10-1
1
10-2
10-3
10-4
10-5
103 1 10 10210-5 10-4 10-3 10-2 10-1 103
40% content was 45 minutes. Another 40% content was 90 minutes.
Few users generated many requests. Many requests concentrated on specific content.
Evaluation Condition
Transmission capacity of downlink: Ad = 10 Mbps Playback rate: R = 2 Mbps Transmission rate of MPD channel:
Rb = Ad – R = 8 Mbps Average content count pre-distributed on each day:
X = 98.46 Smoothing parameter of EMA: = 2/3
(Data of most recent two days occupied 86% of information used in estimation.)
8
Effect of MPD on Server Load
9
0
5
10
15
20
25
Date
L = 0
12/1Date
0
5
10
15
20
25
6/1 7/1 8/1 9/1 10/1 11/1 12/1 1/1
L = 1
L = 7
2 3 4 5 6 7
L = 0L = 1
L = 7Max
imum
act
ive
sess
ion
coun
t in
eac
h da
y [1
02 ]
Max
imum
act
ive
sess
ion
coun
t in
eac
h ho
ur [1
02 ] Max. session count was largely reduced by MPD
compared with only unicast delivery (L = 0). Effect of MPD was stronger when demand was larger.
Effect of MPD on Network Load
Average link load was reduced by MPD in all 31 networks. The effect of MPD was larger as L increased.
10
L: content life length in STBs [days]
0
0.2
0.4
0.6
0.8
1.0
0 1 2 3 4 5 6 7
Server load
Used 31 topologies of commercial ISPs
Allocated server at node giving minimum av. hop length of unicast flows
Transmitted packets on minimum spanning tree
(Av. traffic on each link using MPD) / (That using only unicast delivery)
Required Storage Size of STBs
As L increased, Kmax and V decreased.
However, as L increased, Zmax linearly increased. Just small part of pre-distributed content were viewed.
11
L Kmax V(107) (%) Zmax (TB)
0 2409 8.79 *** ***
1 1738 6.34 0.231 0.69
2 1488 5.26 0.331 1.38
3 1312 4.62 0.389 2.07
4 1174 4.15 0.432 2.76
5 1059 3.77 0.465 3.46
6 972 3.45 0.492 4.15
7 916 3.18 0.514 4.84
Kmax: max. active session count over entire log period
V: average total session length in each day
: utilization of
pre-distributed content Zmax: max. required storage
size of STBs
Conclusion
Important to reduce peak load in VoD service
Proposed to pre-distribute popular content to all users on multicast session independently of actual user requests, in addition to on-demand unicast delivery
Numerical evaluation using access log of actual VoD: Reduced server and network load Reduction effect of peak server load:
30% (L = 1), 60% (L = 7) Needed several TB storage at STBs
12
Merit of MPD VoD
Reduction of load of video server and network Pre-distributes popular content
Reduces number of on-demand deliveries Multicast pre-distribution
Suppresses load cause by pre-distribution
On-demand service & simple VCR operations Users view pre-distributed content from STBs. On-demand delivery for content not pre-distributed
No need for user cooperation Only user owning STB can view pre-distributed content
13
14
VoD Service
Increase of transmission capacity of access links
Dramatically increasing user count of VoD services
VoD delivering UGC (user generated content): Provided by service providers independent of ISPs
VoD delivering rich content: Provided mainly by ISPs regarding it as important service
Server
STB(set-top box)TV
Request
Content delivery
Network
CDN
Provides multiple cache servers over network and distributes copies of content on cache servers
Delivers content from cache server close to requesting user
15
Total cost of server facilities is not reduced because total load over all server facilities is constant.
Original server
Network
Cache serverSTB
TV
Multicast Delivery System
Delvers content to multiple users requesting same content on single multicast delivery session
16
Increases user response time to increase user count accommodated in each multicast session
Needs complex operations to switch delivery session to support VCR operations
ServerNetwork
STB
TV
P2P Delivery System
Each peer, i.e., user, uploads viewing content to other peers viewing same content
17
Needs to sustain content delivery when uploading user leaves or making VCR operations Needs complex operations, i.e., switching source peers
Needs incentive for users
ServerNetwork
STB
TV
サーバ負荷低減法 (4): ISP制御型 P2P配信
HDレコーダーの価格低下は目覚ましく,現在, 1Tバイトの容量のHDレコーダーを4万円程度で購入可能
ユーザ宅内の STBを ISPの管理下で大容量のキャッシュとして運用 ユーザ離脱への対応が不要で全体最適化が可能
18
ユーザに対して ISP管理下の STBを設置させ,他のユーザへの配信に要する電力を負担するインセンティブの付与が必要
配信サーバの負荷は低減されるが, NWの負荷は低減せず
ServerNetwork
STB
TV
総視聴時間上位コンテンツの一致度
d 日間離れた日の各総視聴時間上位 x 個のコンテンツの中で,両日ともに上位 x 以内となったコンテンツの割合
19
0
0.2
0.4
0.6
0.8
1
1 10Av.
dup
licat
ion
ratio
of t
op x
co
nten
t bet
wee
n la
g d
days
x102 103 104
d = 1d = 2d = 3
d = 4
d = 5
d = 6
d = 7
x が小さい領域では,間隔 d が増加するに伴い総視聴時間上位x 個のコンテンツの一致度は低下するが, x の増加に伴い一致度は増加し, x が 1,000程度以上になると d による一致度の差異は消滅
BC事前配信コンテンツの選択効率 各日にx 個を BC事前配信した際の選択効率 : (STB上の Lx個の総視聴時間 ) / (実際の上位 Lx個の総視聴時間 )
20
0
0.2
0.4
0.6
0.8
1
1 10
Ave
rage
effi
cien
cy o
f se
lect
ing
top
x co
nten
t
x
L = 1
102 103 104
L = 3L = 7
xが小さい場合, Lの増加に伴い, BC事前配信時点と各日の総視聴時間上位コンテンツの一致度が低下し,選択効率は低下
しかし選択効率の低下度合いは小さく, Lが 7日でも 70%の選択効率
xの増加に伴い選択効率は向上し, x 10であれば 85~ 90%を達成
⇒ EMAを用いた総視聴時間の推定値に基づき BC事前配信コンテンツを選択することで,十分な選択効率が達成可能