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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
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Tier-1 ISP Tier-2 ISP Local ISP Peering link
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Tier-2 ISP Local ISP Peering link ISP Peer ISP link ISP Peer
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Peer kPeer j Tier-2 ISP (ISP) Peer i 1. performance of the link 2. charge of the link Issues to consider: Optimization problem of peers
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Happiness obtained from sending traffic to peers Delay cost in ISP link Payment to ISP Delay costs in peering links Payments to peers
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Constraints of peers 1. 2. 3. 4.
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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
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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
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Information exchange framework ISP peer Bandwidth allocation Bid Compute resource distribution Compute optimal rates Next period
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ISP 1: Resource distribution peer1 Bid = 50MBps ??? ISP peer2 peer3 Bid = 100MBps Bid = 150MBps Bandwidth = 600MBps
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Proportional share algorithm peer1peer2 peer3 Bid = 50MBps Bid = 100MBps Bid = 150MBps ISP Bandwidth = 600MBps 100MBps200MBps300MBps
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Equal share algorithm peer1peer2 peer3 Bid = 50MBps Bid = 100MBps Bid = 150MBps ISP Bandwidth = 600MBps 150MBps200MBps250MBps
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Simulations When the happiness coefficients of peers are low PSA ESA
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When the happiness coefficients of peers are high PSA ESA
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ISP 2: Maximization of Revenue Unit priceDemand by peer i Determine the optimal price Total revenue from the peers
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Solution: Maximization of revenue Estimate the aggregate traffic ( ) from all peers in term of the price (P)
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Conclusions Utility maximization of a peer Resource distribution of ISP Revenue maximization of ISP
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Q & A
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