Abstract
Cloud computing, where the use of resources is seen as a service (Resources-as-a-Service (RaaS)) has developed extensively for executing computationally resource-intensive applications. As a result, commercial services of such resources are becoming norm of the day and pricing them have become an important problem in finance. Only a few economic models have been reported for pricing cloud resources. In this paper, a novel application of financial option pricing theory to the management of distributed computing resources especially for pricing is addressed. First, the importance of finance models for the given problem is highlighted following an explain on how option theory fits well to price the distributed computing cloud resources. Various cloud resources such as memory, storage, software, and compute cycles are seen as individual commodities and pricing of the resources is done in isolation and in combination of various resources. Second, `we design and develop pricing model and generate pricing results for usage of such commodities for various resources. In the absence of cloud resource pricing benchmarks/standards, firstly, cloud resources usage is simulated in order to justify the pricing model using CloudSim toolkit. In this part of the work, the integration of a financial option-based pricing model with CloudSim framework is implemented using a cloud simulation tool to price cloud compute resources. Secondly, the model is evaluated using cloud metadata obtained from Amazon Web services. The analysis of cloud resources utilization from simulation and real cloud trace data shows the feasibility of a financial option-based model for pricing cloud resources. With a large number of experiments carried out, a justification of the pricing model is obtained by comparing a simulated system to real cloud trace data based on the spot price for the cloud resources. Keywords: Financial Option, Strike Price, CloudSim, Quality of Service, Compute Commodities
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