Distributed Dynamic Replica
Placement and Request Redirection in
Content Delivery Networks
Advisor : Ho-Ting Wu
Student : Yu-Chiang Lin
Date:2011/5/30
OUTLINE
 CDN introduce
 Distributed Dynamic Replica Placement

Cloning of a replica

Replica removal

Redirection
 Future work
 Reference
 Page 2
OUTLINE
 CDN introduce
 Distributed Dynamic Replica Placement

Cloning of a replica

Replica removal

Redirection
 Future work
 Reference
 Page 3
CDN Introduce
Fig:Server Farm(source from EBU technical review)
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CDN Introduce
 Consider TCP transmittion，throughput may affect
by latency or packet lost。
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CDN Introduce
 The Content Delivery Networks (CDN) paradigm is
based on the idea to transparently move third-party
content closer to the users
 content is replicated on CDN servers which are
located close to the final users so that users
perceive a better content access service.
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CDN Introduce
Fig:Content Delivery Network(source from EBU technical
review)
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CDN Introduce
Fig:Content Delivery Network
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CDN Introduce
 Four Important technique
 1.Content route
 2.Content distribution
 3.Content store
 4.Content management
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CDN Introduce
 CDN issue
 1) Deciding the kind of content that should be
hosted (replica placement)
 2) selecting the best replica for a given user
 3) designing mechanisms for transparent redirection
of the users requests to the best replicas
 Page 10
OUTLINE
 CDN introduce
 Distributed Dynamic Replica Placement

Cloning of a replica

Replica removal

Redirection
 Future work
 Reference
 Page 11
Distributed Dynamic Replica
 Distributed scheme to allocate and deallocate
replicas, so that the user requests are satisfied while
minimizing the CDN costs in a dynamic scenario
 This scheme always accounts for the current replica
placement,adding replicas or changing replica
location only when needed.
 Each site j ∈ VR autonomously decides on whether
some of the replicas it stores should be cloned or
removed.
 Page 12
Problem Formulation
 VA: access nodes
 VR: CDN servers sites
 d(i, j): user (access node) i to a replica j
 dmax: distance threshold
 xi,c: the volume of user requests originated at node i
∈ VA for content c ∈ C
 Umax, Umid, Ulow: load threshold
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Cloning of a replica
 Function add_replica(j, c)
 1: lj,c =i∈VA αij,c · xi,c
 2: while lj,c/rj,c− Umax > 0
 3: best_served = 0
 4: best_distance = ∞
 5: best_vr = undefined
 6: for all j’ ∈ ρ(j) s.t. rj,c < VmaxR do
 Page 14
Cloning of a replica
 7: l’j,c =i∈α(j’) αij,c · xi,c
 8: total_distance =i∈α(j’)αij,c · xi,c · di,j’
 9: if (l’j’,c < best_served) ∨
 10: (l’j’,c = best_served ∧
 11: total_distance < best_distance) then
 12: best_distance = total_distance
 13: best_served = l’j’,c
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Cloning of a replica
 14: best_vr = j’
 15: end if
 16: end for
 17: if best_vr = undefined then
 18: exit
 19: end if
 20: ask best_vr to add a replica
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Cloning of a replica
 21: compute l’’bestvr,c = min(i∈α(bestvr) αij,c · xi,c, 1)
 22: lj,c = lj,c − l’’bestvr,c
 23: remove from the set of requests those that can
be offloaded
 24: end while
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Replica removal
 A replica can be removed if (and only if) it serves no
requests
 A replica is removed only when it has not been
serving requests for a time long enough to bring the
exponential average down to zero.
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Redirection
 Based on this feedback users requests are directed
away from a replica in response to threshold events
(if the replica load exceeds Umax or falls below Ulow)
 As an example, an underloaded replica informs the
redirection system which then tries to offload
requests to some other replicas (if possible)
 A perfect load balancing may be impossible due to
the distance constraint
 Page 19
Redirection
Fig. A model for the redirection scheme
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OUTLINE
 CDN introduce
 Distributed Dynamic Replica Placement

Cloning of a replica

Replica removal

Redirection
 Future work
 Reference
 Page 21
Future Work
 comparison of different settings of the Umid
 observe dmax and add remove replica relationship
 Page 22
Reference
 [1] N. Bartolini, F. Lo Presti, and C. Petrioli, “Optimal dynamic
replica placement in Content Delivery Networks,” in
Proceedings of the 11th IEEE International Conference on
Networks, ICON 2003, Sydney, Australia, September 28–
October 1 2003, pp. 125–130.
 [2] F. Lo Presti, C. Petrioli, and C. Vicari, “Dynamic replica
placement in content delivery networks,” in Proceedings of
MASCOTS 05, September 2005.
 [3] F. Lo Presti, C. Petrioli, and C. Vicari, “Distributed Dynamic
Replica Placement and Request Redirection in Content
Delivery Networks ,” in Proceedings of MASCOTS 07, 2008.
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