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