  In cloud computing, users scale their resources (computational) based on
their need. There is massive literature dealing with such resource scaling
algorithms. These works ignore a fundamental constrain imposed by all Cloud
Service Providers (CSP), i.e. one has to pay for a fixed minimum duration
irrespective of their usage. Such quantization in billing cycles poses problem
for users with sporadic workload. In recent literature, Cloud Broker (CB) has
been introduced for the benefit of such users. A CB rents resources from CSP
and in turn provides service to users to generate profit. Contract between CB
and user is that of pay-what-you-use/pay-per-use. However CB faces the
challenge of Quantized Billing Cycles as it negotiates with CSP. We design two
algorithms, one fully online and the other partially online, which maximizes
the profit of the CB. The key idea is to regulate users demand using dynamic
pricing. Our algorithm is inspired by the Ski-Rental problem. We derive
competitive ratio of these algorithms and also conduct simulations using real
world traces to prove the efficiency of our algorithm.
