On the Use of Double Auctions in Resource Allocation Problems in Large-scale Distributed Systems

In this thesis, we explore the use of double auction markets as a general approach to tackle resource allocation problems in large-scale distributed systems, which are traditionally solved using optimization techniques. Prevalently adopted in real-world markets, double auctions have the power of arbitrating mappings between participating players and trading commodities in a decentralized fashion, with every player trying to maximize her own utility selfishly. Through the design of prefetching strategies in peer-assisted video-on-demand systems, we show how the problem of minimizing server bandwidth costs by reallocating media contents can be solved by double auction markets gracefully. However, not every resource allocation problem satisfies requirements of double auctions. We illustrate the limitation of double auctions with an example of virtual machine migration in container-based datacenters, which is then modeled into a Nash bargaining game and solved by a Nash bargaining solution.MAS