http://www.hpl.hp.com/personal/Thomas_Sandholm/sandholm2007a.pdf Applying Occam's razor to statistics to enable risk preference multiplexing. We study stochastic models to mitigate the risk of poor Quality-of-Service (QoS) in computational markets. Consumers who purchase services expect both price and performance guarantees. They need to predict future demand to budget for sustained performance despite price fluctuations. Conversely, providers need to estimate demand to price future usage. The skewed and bursty nature of demand in large-scale computer networks challenges the common statistical assumptions of symmetry, independence, and stationarity. This discrepancy leads to underestimation of investment risk. We confirm this non-normal distribution behavior in our study of demand in computational markets. Thomas Sandholm and Kevin Lai 2007-07-12 14:08:00 tycoon risk qos