Combination Exchange Mechanisms for Efficient Bandwidth Allocation

Abstract

The size, scale and multiple ownership of communication network resources makes it important to consider an economic framework wherein we can investigate the efficiency of network operation taking agents' incentives into account. Such a framework has been considered in the design and analysis of pricing mechanisms to regulate congestion and share bandwidth over short time scales. We consider time scales of a few months over which owners of communication links lease bandwidth to network service providers. As is well-known, economic efficiency is related to how close an allocation is to a competitive equilibrium. We first show that achieving economic efficiency through a market mechanism depends on network topology. We then show that in finite networks a competitive equilibrium may not exist. But a competitive equilibrium does exist in an idealized continuum model, in which all agents are infinitesimal compared with the size of the network. This suggests that approximate competitive equilibria with good performance may be attainable in real networks. We finally introduce a market mechanism called the combinatorial seller's bid double auction whose outcome, in the continuum model, is a competitive equilibrium. 1. Introduction. Communication networks have increased in scale and hetero- geneity. There are multiple network owners and operators, each with their own hetero- geneous endowments and privately known cost and revenue models. So, an allocation of network resources efficient from an engineering perspective need not be realized in the market. Hence, it is useful to find economic mechanisms that result in efficient resource allocations among selfish agents. The efficiency of bandwidth allocation among competing users in a communica- tion network has been studied within an economic framework before. The previous research literature focuses attention on congestion that results when aggregate user demand exceeds capacity, and proposes usage-dependent pricing as a method for con- trolling congestion (23, 24). However, several difficulties must be faced in coming up with a good price-adjustment mechanism. First, congestion occurs over a very short time scale: Aggregate traffic is bursty and exceeds nominal capacity for periods of a few seconds (10). So the pricing mechanism must react very quickly to changes in aggregate demand. Second, the 'correct' congestion price depends on how much users are willing to pay for the service, which is not known. This has prompted invention of distributed price iteration algorithms that converge to the 'correct' price (16, 22). These algorithms are not practical but permit a re-interpretation of TCP-like proto-