In hybrid cloud computing, cloud users have the ability to procure
resources from multiple cloud vendors, and furthermore also the option
of selecting different combinations of resources. The problem of
procuring a single resource from one of many cloud vendors can be
modeled as a standard winner determination problem, and there are
mechanisms for single item resource procurement given different QoS
and pricing parameters. There however is no compatible approach that
would allow cloud users to procure arbitrary bundles of resources from
cloud vendors. We design the $\mathcal{CA}$ algorithm to solve the
multiple resource procurement problem in hybrid clouds. Cloud users
submit their requirements, and in turn vendors submit bids containing
price, QoS and their offered sets of resources. The approach is
scalable, which is necessary given that there are a large number of
cloud vendors, with more continually appearing. We perform
experiments for procurement cost and scalability efficacy on the
$\mathcal{CABOB}$ algorithm using various standard distribution
benchmarks like random, uniform, decay and CATS. Simulations using
our approach with prices procured from several cloud vendors' datasets
show its effectiveness at multiple resource procurement.