  The spot pricing scheme has been considered to be resource-efficient for
providers and cost-effective for consumers in the Cloud market. Nevertheless,
unlike the static and straightforward strategies of trading on-demand and
reserved Cloud services, the market-driven mechanism for trading spot service
would be complicated for both implementation and understanding. The largely
invisible market activities and their complex interactions could especially
make Cloud consumers hesitate to enter the spot market. To reduce the
complexity in understanding the Cloud spot market, we decided to reveal the
backend information behind spot price variations. Inspired by the methodology
of reverse engineering, we developed a Predator-Prey model that can simulate
the interactions between demand and resource based on the visible spot price
traces. The simulation results have shown some basic regular patterns of market
activities with respect to Amazon's spot instance type m3.large. Although the
findings of this study need further validation by using practical data, our
work essentially suggests a promising approach (i.e.~using a Predator-Prey
model) to investigate spot market activities.
