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Performance Analysis of Non-stationary Peer-assistedVoD Systems
Delia Ciullo1, Valentina Martina1, Michele Garetto2, Emilio Leonardi1,Gianluca Torrisi3
1Politecnico di Torino
2Universita di Torino
3CNR - Instituto per le Applicazioni di Calcolo
March 26-th, 2012
E. Leonardi Performance of P2P-VOD systems
Introduction
In peer-assisted Video-on-Demand (VoD) systems:
users browse a catalog of available videos and asynchronously issuerequests to watch a given content;
content is divided into chunks that can be retrieved either from
the serversother peers currently retrieving the same video (leechers)peers storing the whole video (seeds);
chunks must be retrieved by peers almost in sequence to guaranteesmall play-out delays;
a minimum average download rate equal to the video playback ratemust be sustained to guarantee service continuity; the system(exploiting servers bandwidth when needed) is able to steadily meetthis constraint.
E. Leonardi Performance of P2P-VOD systems
Introduction
In peer-assisted Video-on-Demand (VoD) systems:
users browse a catalog of available videos and asynchronously issuerequests to watch a given content;
content is divided into chunks that can be retrieved either from
the serversother peers currently retrieving the same video (leechers)peers storing the whole video (seeds);
chunks must be retrieved by peers almost in sequence to guaranteesmall play-out delays;
a minimum average download rate equal to the video playback ratemust be sustained to guarantee service continuity; the system(exploiting servers bandwidth when needed) is able to steadily meetthis constraint.
E. Leonardi Performance of P2P-VOD systems
Introduction
In peer-assisted Video-on-Demand (VoD) systems:
users browse a catalog of available videos and asynchronously issuerequests to watch a given content;
content is divided into chunks that can be retrieved either from
the serversother peers currently retrieving the same video (leechers)peers storing the whole video (seeds);
chunks must be retrieved by peers almost in sequence to guaranteesmall play-out delays;
a minimum average download rate equal to the video playback ratemust be sustained to guarantee service continuity; the system(exploiting servers bandwidth when needed) is able to steadily meetthis constraint.
E. Leonardi Performance of P2P-VOD systems
Introduction
In peer-assisted Video-on-Demand (VoD) systems:
users browse a catalog of available videos and asynchronously issuerequests to watch a given content;
content is divided into chunks that can be retrieved either from
the servers
other peers currently retrieving the same video (leechers)peers storing the whole video (seeds);
chunks must be retrieved by peers almost in sequence to guaranteesmall play-out delays;
a minimum average download rate equal to the video playback ratemust be sustained to guarantee service continuity; the system(exploiting servers bandwidth when needed) is able to steadily meetthis constraint.
E. Leonardi Performance of P2P-VOD systems
Introduction
In peer-assisted Video-on-Demand (VoD) systems:
users browse a catalog of available videos and asynchronously issuerequests to watch a given content;
content is divided into chunks that can be retrieved either from
the serversother peers currently retrieving the same video (leechers)
peers storing the whole video (seeds);
chunks must be retrieved by peers almost in sequence to guaranteesmall play-out delays;
a minimum average download rate equal to the video playback ratemust be sustained to guarantee service continuity; the system(exploiting servers bandwidth when needed) is able to steadily meetthis constraint.
E. Leonardi Performance of P2P-VOD systems
Introduction
In peer-assisted Video-on-Demand (VoD) systems:
users browse a catalog of available videos and asynchronously issuerequests to watch a given content;
content is divided into chunks that can be retrieved either from
the serversother peers currently retrieving the same video (leechers)peers storing the whole video (seeds);
chunks must be retrieved by peers almost in sequence to guaranteesmall play-out delays;
a minimum average download rate equal to the video playback ratemust be sustained to guarantee service continuity; the system(exploiting servers bandwidth when needed) is able to steadily meetthis constraint.
E. Leonardi Performance of P2P-VOD systems
Introduction
In peer-assisted Video-on-Demand (VoD) systems:
users browse a catalog of available videos and asynchronously issuerequests to watch a given content;
content is divided into chunks that can be retrieved either from
the serversother peers currently retrieving the same video (leechers)peers storing the whole video (seeds);
chunks must be retrieved by peers almost in sequence to guaranteesmall play-out delays;
a minimum average download rate equal to the video playback ratemust be sustained to guarantee service continuity; the system(exploiting servers bandwidth when needed) is able to steadily meetthis constraint.
E. Leonardi Performance of P2P-VOD systems
Introduction
In peer-assisted Video-on-Demand (VoD) systems:
users browse a catalog of available videos and asynchronously issuerequests to watch a given content;
content is divided into chunks that can be retrieved either from
the serversother peers currently retrieving the same video (leechers)peers storing the whole video (seeds);
chunks must be retrieved by peers almost in sequence to guaranteesmall play-out delays;
a minimum average download rate equal to the video playback ratemust be sustained to guarantee service continuity; the system(exploiting servers bandwidth when needed) is able to steadily meetthis constraint.
E. Leonardi Performance of P2P-VOD systems
Assumptions
Video is downloaded by each user at constant rate d , greater or equalto the playback rate dv ;
upload available bandwidth Ui of peer i is a random variable with aassigned distribution (Ui are i.i.d.);
users contribute their upload bandwidth to the video distribution aslong as they are in the system;
the arrival process of requests (and users) for a video is a (possiblynon-homogeneous) Poisson process with intensity λ(t);
user’s sojourn time is described by an arbitrary random variable Twith finite mean T and complementary cumulative distributionfunction GT (x).
E. Leonardi Performance of P2P-VOD systems
Assumptions
Video is downloaded by each user at constant rate d , greater or equalto the playback rate dv ;
upload available bandwidth Ui of peer i is a random variable with aassigned distribution (Ui are i.i.d.);
users contribute their upload bandwidth to the video distribution aslong as they are in the system;
the arrival process of requests (and users) for a video is a (possiblynon-homogeneous) Poisson process with intensity λ(t);
user’s sojourn time is described by an arbitrary random variable Twith finite mean T and complementary cumulative distributionfunction GT (x).
E. Leonardi Performance of P2P-VOD systems
Assumptions
Video is downloaded by each user at constant rate d , greater or equalto the playback rate dv ;
upload available bandwidth Ui of peer i is a random variable with aassigned distribution (Ui are i.i.d.);
users contribute their upload bandwidth to the video distribution aslong as they are in the system;
the arrival process of requests (and users) for a video is a (possiblynon-homogeneous) Poisson process with intensity λ(t);
user’s sojourn time is described by an arbitrary random variable Twith finite mean T and complementary cumulative distributionfunction GT (x).
E. Leonardi Performance of P2P-VOD systems
Assumptions
Video is downloaded by each user at constant rate d , greater or equalto the playback rate dv ;
upload available bandwidth Ui of peer i is a random variable with aassigned distribution (Ui are i.i.d.);
users contribute their upload bandwidth to the video distribution aslong as they are in the system;
the arrival process of requests (and users) for a video is a (possiblynon-homogeneous) Poisson process with intensity λ(t);
user’s sojourn time is described by an arbitrary random variable Twith finite mean T and complementary cumulative distributionfunction GT (x).
E. Leonardi Performance of P2P-VOD systems
Assumptions
Video is downloaded by each user at constant rate d , greater or equalto the playback rate dv ;
upload available bandwidth Ui of peer i is a random variable with aassigned distribution (Ui are i.i.d.);
users contribute their upload bandwidth to the video distribution aslong as they are in the system;
the arrival process of requests (and users) for a video is a (possiblynon-homogeneous) Poisson process with intensity λ(t);
user’s sojourn time is described by an arbitrary random variable Twith finite mean T and complementary cumulative distributionfunction GT (x).
E. Leonardi Performance of P2P-VOD systems
Assumptions
Video is downloaded by each user at constant rate d , greater or equalto the playback rate dv ;
upload available bandwidth Ui of peer i is a random variable with aassigned distribution (Ui are i.i.d.);
users contribute their upload bandwidth to the video distribution aslong as they are in the system;
the arrival process of requests (and users) for a video is a (possiblynon-homogeneous) Poisson process with intensity λ(t);
user’s sojourn time is described by an arbitrary random variable Twith finite mean T and complementary cumulative distributionfunction GT (x).
E. Leonardi Performance of P2P-VOD systems
Preliminary Observations
The number of active users N(t) follows a Poisson distribution withmean
N(t) =
∫ ∞
0λ(t − x)GT (x)dx ;
τd = L/d is the time needed to download the whole video, andT d =
∫ τd0 GT (x)dx is the average time spent by peers downloading
the video, taking into account premature abandonments;
Nd(t) is the number of downloading users with meanNd(t) =
∫ τd0 λ(t − x)GT (x)dx , and Nseed(t) the number of seeds
with mean Nseed(t) = N(t)− Nd(t);
we define the average system load as:
γ =dT d
U T.
E. Leonardi Performance of P2P-VOD systems
Preliminary Observations
The number of active users N(t) follows a Poisson distribution withmean
N(t) =
∫ ∞
0λ(t − x)GT (x)dx ;
τd = L/d is the time needed to download the whole video, andT d =
∫ τd0 GT (x)dx is the average time spent by peers downloading
the video, taking into account premature abandonments;
Nd(t) is the number of downloading users with meanNd(t) =
∫ τd0 λ(t − x)GT (x)dx , and Nseed(t) the number of seeds
with mean Nseed(t) = N(t)− Nd(t);
we define the average system load as:
γ =dT d
U T.
E. Leonardi Performance of P2P-VOD systems
Preliminary Observations
The number of active users N(t) follows a Poisson distribution withmean
N(t) =
∫ ∞
0λ(t − x)GT (x)dx ;
τd = L/d is the time needed to download the whole video, andT d =
∫ τd0 GT (x)dx is the average time spent by peers downloading
the video, taking into account premature abandonments;
Nd(t) is the number of downloading users with meanNd(t) =
∫ τd0 λ(t − x)GT (x)dx , and Nseed(t) the number of seeds
with mean Nseed(t) = N(t)− Nd(t);
we define the average system load as:
γ =dT d
U T.
E. Leonardi Performance of P2P-VOD systems
Preliminary Observations
The number of active users N(t) follows a Poisson distribution withmean
N(t) =
∫ ∞
0λ(t − x)GT (x)dx ;
τd = L/d is the time needed to download the whole video, andT d =
∫ τd0 GT (x)dx is the average time spent by peers downloading
the video, taking into account premature abandonments;
Nd(t) is the number of downloading users with meanNd(t) =
∫ τd0 λ(t − x)GT (x)dx , and Nseed(t) the number of seeds
with mean Nseed(t) = N(t)− Nd(t);
we define the average system load as:
γ =dT d
U T.
E. Leonardi Performance of P2P-VOD systems
Goal
Our goal is:
to characterize the bandwidth requested from the servers S (and itsaverage S);
we develop an approximate efficient and accurate fluid model tocompute S ;our approach is able to capture several stochastic effects related topeer churn, upload bandwidth heterogeneity, non-stationary trafficconditions;our methodology can be exploited to design efficient peer-assisted VoDsystems and optimal resource allocation strategies.
In [1] we obtain rigorous bounds for the sequential delivery scheme andasymptotic results as the number of users increases.
[1] D.Ciullo, V.Martina, M.Garetto, E.Leonardi, G.L.Torrisi, “Stochastic Analysis ofSelf-Sustainability in Peer-Assisted VoD Systems”, Session TS05, Thursday, h.8.30-10.00
E. Leonardi Performance of P2P-VOD systems
Goal
Our goal is:
to characterize the bandwidth requested from the servers S (and itsaverage S);
we develop an approximate efficient and accurate fluid model tocompute S ;our approach is able to capture several stochastic effects related topeer churn, upload bandwidth heterogeneity, non-stationary trafficconditions;our methodology can be exploited to design efficient peer-assisted VoDsystems and optimal resource allocation strategies.
In [1] we obtain rigorous bounds for the sequential delivery scheme andasymptotic results as the number of users increases.
[1] D.Ciullo, V.Martina, M.Garetto, E.Leonardi, G.L.Torrisi, “Stochastic Analysis ofSelf-Sustainability in Peer-Assisted VoD Systems”, Session TS05, Thursday, h.8.30-10.00
E. Leonardi Performance of P2P-VOD systems
Goal
Our goal is:
to characterize the bandwidth requested from the servers S (and itsaverage S);
we develop an approximate efficient and accurate fluid model tocompute S ;
our approach is able to capture several stochastic effects related topeer churn, upload bandwidth heterogeneity, non-stationary trafficconditions;our methodology can be exploited to design efficient peer-assisted VoDsystems and optimal resource allocation strategies.
In [1] we obtain rigorous bounds for the sequential delivery scheme andasymptotic results as the number of users increases.
[1] D.Ciullo, V.Martina, M.Garetto, E.Leonardi, G.L.Torrisi, “Stochastic Analysis ofSelf-Sustainability in Peer-Assisted VoD Systems”, Session TS05, Thursday, h.8.30-10.00
E. Leonardi Performance of P2P-VOD systems
Goal
Our goal is:
to characterize the bandwidth requested from the servers S (and itsaverage S);
we develop an approximate efficient and accurate fluid model tocompute S ;our approach is able to capture several stochastic effects related topeer churn, upload bandwidth heterogeneity, non-stationary trafficconditions;
our methodology can be exploited to design efficient peer-assisted VoDsystems and optimal resource allocation strategies.
In [1] we obtain rigorous bounds for the sequential delivery scheme andasymptotic results as the number of users increases.
[1] D.Ciullo, V.Martina, M.Garetto, E.Leonardi, G.L.Torrisi, “Stochastic Analysis ofSelf-Sustainability in Peer-Assisted VoD Systems”, Session TS05, Thursday, h.8.30-10.00
E. Leonardi Performance of P2P-VOD systems
Goal
Our goal is:
to characterize the bandwidth requested from the servers S (and itsaverage S);
we develop an approximate efficient and accurate fluid model tocompute S ;our approach is able to capture several stochastic effects related topeer churn, upload bandwidth heterogeneity, non-stationary trafficconditions;our methodology can be exploited to design efficient peer-assisted VoDsystems and optimal resource allocation strategies.
In [1] we obtain rigorous bounds for the sequential delivery scheme andasymptotic results as the number of users increases.
[1] D.Ciullo, V.Martina, M.Garetto, E.Leonardi, G.L.Torrisi, “Stochastic Analysis ofSelf-Sustainability in Peer-Assisted VoD Systems”, Session TS05, Thursday, h.8.30-10.00
E. Leonardi Performance of P2P-VOD systems
Goal
Our goal is:
to characterize the bandwidth requested from the servers S (and itsaverage S);
we develop an approximate efficient and accurate fluid model tocompute S ;our approach is able to capture several stochastic effects related topeer churn, upload bandwidth heterogeneity, non-stationary trafficconditions;our methodology can be exploited to design efficient peer-assisted VoDsystems and optimal resource allocation strategies.
In [1] we obtain rigorous bounds for the sequential delivery scheme andasymptotic results as the number of users increases.
[1] D.Ciullo, V.Martina, M.Garetto, E.Leonardi, G.L.Torrisi, “Stochastic Analysis ofSelf-Sustainability in Peer-Assisted VoD Systems”, Session TS05, Thursday, h.8.30-10.00
E. Leonardi Performance of P2P-VOD systems
A simple Lower Bound
A simple universal lower bound to S(t) for any chunk distribution schemeis
S(t) ≤ max{0, dNd(t)− U N(t)}.
Intuition: The additional server bandwidth is given by users requested
bandwidth minus their total upload bandwidth.
Note that this trivial lower bound was already shown in: C. Huang, J. Li, and K. W.Ross, Can Internet Video-on-Demand Be Profitable? in ACM SIGCOMM, 2007.
E. Leonardi Performance of P2P-VOD systems
Analysis
Let Sd be the aggregate bandwidth requested by the downloading users.The aggregate upload bandwidth offered by the seeds is
Sseed =
Nseed∑i=1
Ui .
The bandwidth requested from the servers is:
S , max{0,Sd − Sseed}
where Sd is the bandwidth demanded by downloading peers.
E. Leonardi Performance of P2P-VOD systems
Analysis
Let Sd be the aggregate bandwidth requested by the downloading users.The aggregate upload bandwidth offered by the seeds is
Sseed =
Nseed∑i=1
Ui .
The bandwidth requested from the servers is:
S , max{0,Sd − Sseed}
where Sd is the bandwidth demanded by downloading peers.
E. Leonardi Performance of P2P-VOD systems
Analysis
Let Sd be the aggregate bandwidth requested by the downloading users.The aggregate upload bandwidth offered by the seeds is
Sseed =
Nseed∑i=1
Ui .
The bandwidth requested from the servers is:
S , max{0,Sd − Sseed}
where Sd is the bandwidth demanded by downloading peers.
E. Leonardi Performance of P2P-VOD systems
Analysis(2)
We define Sd(k) , (Sd(t) | Nd(t) = k)
Theorem
Sd(k) satisfies the following recursive equation:
Sd(k) =
{d k = 1d + max{0, Sd(k − 1)− Uk} k > 1
E. Leonardi Performance of P2P-VOD systems
Analysis(2)
We define Sd(k) , (Sd(t) | Nd(t) = k)
Theorem
Sd(k) satisfies the following recursive equation:
Sd(k) =
{d k = 1d + max{0, Sd(k − 1)− Uk} k > 1
E. Leonardi Performance of P2P-VOD systems
Analysis(3)
We characterize the distribution of the server bandwidth using asecond-order approximation;
we approximate the distribution of the quantity Sd(k − 1)− Uk (foreach k ≥ 2) with a normal distribution matching the first twomoments of this quantity;
we apply standard formulas of the truncated normal distribution toderive the first two moments of Sd(k) as a function of the first twomoments of Sd(k − 1);
a similar approximation is subsequently applied to take into accountthe effect of the seeds.
E. Leonardi Performance of P2P-VOD systems
Analysis(3)
We characterize the distribution of the server bandwidth using asecond-order approximation;
we approximate the distribution of the quantity Sd(k − 1)− Uk (foreach k ≥ 2) with a normal distribution matching the first twomoments of this quantity;
we apply standard formulas of the truncated normal distribution toderive the first two moments of Sd(k) as a function of the first twomoments of Sd(k − 1);
a similar approximation is subsequently applied to take into accountthe effect of the seeds.
E. Leonardi Performance of P2P-VOD systems
Analysis(3)
We characterize the distribution of the server bandwidth using asecond-order approximation;
we approximate the distribution of the quantity Sd(k − 1)− Uk (foreach k ≥ 2) with a normal distribution matching the first twomoments of this quantity;
we apply standard formulas of the truncated normal distribution toderive the first two moments of Sd(k) as a function of the first twomoments of Sd(k − 1);
a similar approximation is subsequently applied to take into accountthe effect of the seeds.
E. Leonardi Performance of P2P-VOD systems
Analysis(3)
We characterize the distribution of the server bandwidth using asecond-order approximation;
we approximate the distribution of the quantity Sd(k − 1)− Uk (foreach k ≥ 2) with a normal distribution matching the first twomoments of this quantity;
we apply standard formulas of the truncated normal distribution toderive the first two moments of Sd(k) as a function of the first twomoments of Sd(k − 1);
a similar approximation is subsequently applied to take into accountthe effect of the seeds.
E. Leonardi Performance of P2P-VOD systems
Analysis(3)
We characterize the distribution of the server bandwidth using asecond-order approximation;
we approximate the distribution of the quantity Sd(k − 1)− Uk (foreach k ≥ 2) with a normal distribution matching the first twomoments of this quantity;
we apply standard formulas of the truncated normal distribution toderive the first two moments of Sd(k) as a function of the first twomoments of Sd(k − 1);
a similar approximation is subsequently applied to take into accountthe effect of the seeds.
E. Leonardi Performance of P2P-VOD systems
Swarm size effect
d = dv = 1, T = T d = τd
0.1
1
10
100
1 10 100 1000
Aver
age
serv
er b
and
wid
th
Average number of users
approx - U = 0.9sim - U = 0.9
sim lower bound - U = 0.9
E. Leonardi Performance of P2P-VOD systems
Swarm size effect
d = dv = 1, T = T d = τd
0.1
1
10
100
1 10 100 1000
Aver
age
serv
er b
and
wid
th
Average number of users
approx - U = 1.2sim - U = 1.2
sim lower bound - U = 1.2
E. Leonardi Performance of P2P-VOD systems
Download rate impact
U = 1.2, dv = 1, T = T d = τd
0
0.25
0.5
0.75
1
1.25
1.5
1.75
2
2.25
2.5
2.75
3
3.25
3.5
1 1.2 1.4 1.6 1.8 2 2.2
download rate, d
simapprox
sim lower bound
E. Leonardi Performance of P2P-VOD systems
Extension to non sequential download
A common approach in P2P-VoD is to allow users to receive alsoout-of-sequence chunks of the video within a limited sliding windowof data starting from the point currently played;
for simplicity, instead of considering an actual sliding window, wedivide the video into a fixed number W of non-overlapping segmentsof size LW = L/W ;
we assume that, within a segment, chunk based out-of-sequencedistribution can be exploited, and we extend our approximate modelto deal with partially non-sequential chunk delivery.
E. Leonardi Performance of P2P-VOD systems
Extension to non sequential download
A common approach in P2P-VoD is to allow users to receive alsoout-of-sequence chunks of the video within a limited sliding windowof data starting from the point currently played;
for simplicity, instead of considering an actual sliding window, wedivide the video into a fixed number W of non-overlapping segmentsof size LW = L/W ;
we assume that, within a segment, chunk based out-of-sequencedistribution can be exploited, and we extend our approximate modelto deal with partially non-sequential chunk delivery.
E. Leonardi Performance of P2P-VOD systems
Extension to non sequential download
A common approach in P2P-VoD is to allow users to receive alsoout-of-sequence chunks of the video within a limited sliding windowof data starting from the point currently played;
for simplicity, instead of considering an actual sliding window, wedivide the video into a fixed number W of non-overlapping segmentsof size LW = L/W ;
we assume that, within a segment, chunk based out-of-sequencedistribution can be exploited, and we extend our approximate modelto deal with partially non-sequential chunk delivery.
E. Leonardi Performance of P2P-VOD systems
Extension to non sequential download
A common approach in P2P-VoD is to allow users to receive alsoout-of-sequence chunks of the video within a limited sliding windowof data starting from the point currently played;
for simplicity, instead of considering an actual sliding window, wedivide the video into a fixed number W of non-overlapping segmentsof size LW = L/W ;
we assume that, within a segment, chunk based out-of-sequencedistribution can be exploited, and we extend our approximate modelto deal with partially non-sequential chunk delivery.
E. Leonardi Performance of P2P-VOD systems
Impact of non-sequential delivery
0
1
2
3
4
5
6
0 10 20 30 40 50 60 70 80 90 100
Av
erag
e se
rver
ban
dw
idth
Average number of users
sim - sequentialsim - W = 32sim - W = 16
sim - W = 8sim - W = 4sim - W = 2
sim - lower bound 0
1
2
3
4
5
6
0 10 20 30 40 50 60 70 80 90 100
Average number of users
approx - sequentialapprox - W = 32approx - W = 16approx - W = 8approx - W = 4approx - W = 2approx - W = 1
E. Leonardi Performance of P2P-VOD systems
Impact of non stationarity
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9
1
12 18 24 6 12 18 24 6 0
200
400
600
800
1000
1200v
ideo
req
ues
t ra
te, λ
(t)
nu
mb
er o
f d
ow
nlo
ader
s /
seed
s
λ
downloadersseeds
0
10
20
30
40
50
60
70
12 18 24 6 12 18 24 6
aver
age
serv
er b
and
wid
th
time of day (hours)
sim - traceapprox
approx - λ = 1
E. Leonardi Performance of P2P-VOD systems
Conclusions
We have proposed a computationally-efficient methodology toestimate the server bandwidth requested in non-stationary P2P-VoDsystems;
we have discovered several interesting properties:
the server bandwidth can be minimized by a proper selection of thedownload rate;the server bandwidth increases with the variation coefficient of the peerupload bandwidth;the gain achievable by non-sequential schemes over the simplesequential scheme depends critically on the size of the sliding windowand the number of downloading users;non-stationary systems are affected by a misalignment problembetween downloaders and seeds.
E. Leonardi Performance of P2P-VOD systems
Conclusions
We have proposed a computationally-efficient methodology toestimate the server bandwidth requested in non-stationary P2P-VoDsystems;
we have discovered several interesting properties:
the server bandwidth can be minimized by a proper selection of thedownload rate;
the server bandwidth increases with the variation coefficient of the peerupload bandwidth;the gain achievable by non-sequential schemes over the simplesequential scheme depends critically on the size of the sliding windowand the number of downloading users;non-stationary systems are affected by a misalignment problembetween downloaders and seeds.
E. Leonardi Performance of P2P-VOD systems
Conclusions
We have proposed a computationally-efficient methodology toestimate the server bandwidth requested in non-stationary P2P-VoDsystems;
we have discovered several interesting properties:
the server bandwidth can be minimized by a proper selection of thedownload rate;the server bandwidth increases with the variation coefficient of the peerupload bandwidth;
the gain achievable by non-sequential schemes over the simplesequential scheme depends critically on the size of the sliding windowand the number of downloading users;non-stationary systems are affected by a misalignment problembetween downloaders and seeds.
E. Leonardi Performance of P2P-VOD systems
Conclusions
We have proposed a computationally-efficient methodology toestimate the server bandwidth requested in non-stationary P2P-VoDsystems;
we have discovered several interesting properties:
the server bandwidth can be minimized by a proper selection of thedownload rate;the server bandwidth increases with the variation coefficient of the peerupload bandwidth;the gain achievable by non-sequential schemes over the simplesequential scheme depends critically on the size of the sliding windowand the number of downloading users;
non-stationary systems are affected by a misalignment problembetween downloaders and seeds.
E. Leonardi Performance of P2P-VOD systems
Conclusions
We have proposed a computationally-efficient methodology toestimate the server bandwidth requested in non-stationary P2P-VoDsystems;
we have discovered several interesting properties:
the server bandwidth can be minimized by a proper selection of thedownload rate;the server bandwidth increases with the variation coefficient of the peerupload bandwidth;the gain achievable by non-sequential schemes over the simplesequential scheme depends critically on the size of the sliding windowand the number of downloading users;non-stationary systems are affected by a misalignment problembetween downloaders and seeds.
E. Leonardi Performance of P2P-VOD systems
Thank you!
E. Leonardi Performance of P2P-VOD systems