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Interaction of ISPs: Distributed Resource Allocation and Revenue Maximization Sam C.M. Lee, Joe W.J. Jiang, John C.S. Lui The Chinese University of Hong Kon g

Interaction of ISPs: Distributed Resource Allocation and Revenue Maximization

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Interaction of ISPs: Distributed Resource Allocation and Revenue Maximization. Sam C.M. Lee, Joe W.J. Jiang, John C.S. Lui The Chinese University of Hong Kong. Tier-1 ISP. Tier-2 ISP. Local ISP. Peering link. ISP. Tier-2 ISP. Peer. Local ISP. Peering link. ISP link. Peer. Peer. ISP. - PowerPoint PPT Presentation

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Page 1: Interaction of ISPs: Distributed Resource Allocation and Revenue Maximization

Interaction of ISPs: Distributed Resource Allocation and Revenue Maximization

Sam C.M. Lee, Joe W.J. Jiang, John C.S. LuiThe Chinese University of Hong Kong

Page 2: Interaction of ISPs: Distributed Resource Allocation and Revenue Maximization

Tier-1 ISP

Tier-2 ISP

Local ISP

Peering link

Page 3: Interaction of ISPs: Distributed Resource Allocation and Revenue Maximization

Tier-2 ISP

Local ISP

Peering link

ISP

PeerISP link

ISP

Peer

Peer

PeerPeer

Peer

Page 4: Interaction of ISPs: Distributed Resource Allocation and Revenue Maximization

Peer kPeer j

Tier-2 ISP(ISP)

Peer i

1. performance of the link2. charge of the link

Issues to consider:

Optimization problem of peers

Page 5: Interaction of ISPs: Distributed Resource Allocation and Revenue Maximization

Optimization problem of peersHappiness obtained from sending traffic to peers

Delay cost in ISP link

Payment to ISP

Delay costs in peering links

Payments to peers

Page 6: Interaction of ISPs: Distributed Resource Allocation and Revenue Maximization

Constraints of peers

1.2.3.4.

Page 7: Interaction of ISPs: Distributed Resource Allocation and Revenue Maximization

Solution to the peers

• Objective function is strictly concave in every transmission rate

• The optimal transmission rates and maximum utility are unique and can be found by Lagrangian method

Page 8: Interaction of ISPs: Distributed Resource Allocation and Revenue Maximization

Problems for an ISP

• Maximization of revenue– How to determine the optimal value of unit price

• Resource distribution– How to determine the capacity for the peers

Page 9: Interaction of ISPs: Distributed Resource Allocation and Revenue Maximization

Information exchange framework

ISP peer

Bandwidthallocation Bid

Compute resourcedistribution

Computeoptimalrates

Next period

Page 10: Interaction of ISPs: Distributed Resource Allocation and Revenue Maximization

ISP 1: Resource distribution

peer1

Bid = 50MBps

? ? ?

ISP

peer2 peer3

Bid = 100MBps Bid = 150MBps

Bandwidth = 600MBps

Page 11: Interaction of ISPs: Distributed Resource Allocation and Revenue Maximization

Proportional share algorithm

peer1 peer2 peer3

Bid = 50MBps Bid = 100MBps Bid = 150MBps

ISP Bandwidth = 600MBps

100MBps 200MBps 300MBps

Page 12: Interaction of ISPs: Distributed Resource Allocation and Revenue Maximization

Equal share algorithm

peer1 peer2 peer3

Bid = 50MBps Bid = 100MBps Bid = 150MBps

ISP Bandwidth = 600MBps

150MBps 200MBps 250MBps

Page 13: Interaction of ISPs: Distributed Resource Allocation and Revenue Maximization

Simulations

• When the happiness coefficients of peers are low

PSA ESA

Page 14: Interaction of ISPs: Distributed Resource Allocation and Revenue Maximization

• When the happiness coefficients of peers are high

PSA ESA

Page 15: Interaction of ISPs: Distributed Resource Allocation and Revenue Maximization

ISP 2: Maximization of Revenue

Unit price Demand by peer i

Determine the optimal price

Total revenue from the peers

Page 16: Interaction of ISPs: Distributed Resource Allocation and Revenue Maximization

Solution: Maximization of revenue

•Estimate the aggregate traffic ( ) from all peers in term of the price (P)

Page 17: Interaction of ISPs: Distributed Resource Allocation and Revenue Maximization

Conclusions

• Utility maximization of a peer• Resource distribution of ISP• Revenue maximization of ISP

Page 18: Interaction of ISPs: Distributed Resource Allocation and Revenue Maximization

Q & A