Internet and graphs are very much related. The graphical structure of internet has been studied extensively to provide efficient solutions to routing and other problems. But most of these studies assume a central authority which controls and manages the internet. In the recent years game theoretic models have been proposed which do not require a central authority and the users are assumed to be routing their flows selfishly. The existence of Nash Equilibria, congestion and the amount of inefficiency caused by this selfish routing is a major concern in this field. A type of paradox in the selfish routing networks, Braess' Paradox, first discovered by Braess, is a major contributor to inefficiency. Several pricing mechanisms have also been provided which give a game theoretical model between users(consumers) and ISPs ( Internet Service Providers or sellers) for the internet. We propose a novel pricing mechanism, based on real world Internet network architecture, which reduces the severity of Braess' Paradox in selfish routing game theoretic networks. It's a pricing mechanism between combinatorial users and ISPs. We prove that Nash equilibria exists in this network and provide bounds on inefficiency . We use graphical properties of internet to prove our result. Several interesting extensions and future work have also been discussed.
Hayrapetyan et. al @cite_10 analyze among similar lines as us but for their cost function they assume a constant term for the per unit flow price charged by ISPs but in the real world scenario generally the per unit charge decreases if the flow required by the user increases i.e. ISPs provide concession for more flow. Our model captures this. They have not done any analysis of the effect of Braess' Paradox in their network, too. We show that in our model the severity of Braess' Paradox is reduced.
@cite_10
2120126835
We consider a network where each user is charged a fixed price per unit of bandwidth used, but where there is no congestion-dependent pricing. However, the transmission rate of each user is assumed to be a function of network congestion (like TCP), and the price per unit bandwidth. We are interested in answering the following question: how should the network choose the price to maximize its overall revenue? To obtain a tractable solution, we consider a single link accessed by many users where the capacity is increased in proportion to the number of users. We show the following result: as the number of users increases, the optimal price per unit bandwidth charged by the service provider may increase or decrease depending upon the bandwidth of the link. However, for all values of the link capacity, the service provider's revenue per unit bandwidth increases and the overall performance of each user (measured in terms of a function of its throughput, the network congestion and the cost incurred by the user for bandwidth usage) improves. Since the revenue per unit bandwidth increases, it provides an incentive for the service provider to increase the available bandwidth in proportion to the number of users.