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Home  >  Volume 21 (2012)

A Financial Option Model for Pricing Cloud Compute Resources by Allenotor1, I.O.Oseghale2 and R. K. Thulasiram, Volume 21 (July, 2012), pp 237 – 252
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Abstract

Cloud compute resources such as managed computing power, storage, platforms, services, CPU cycles, memory, and network bandwidths exist as compute instances. We describe these cloud resources as Cloud Compute Commodities (C3). One of the specific characteristics of C3 is guaranteeing their availability since they exist as instances (or compute cycles) of C3. This specific C3 characteristic feature make pricing them a challenge. Several initiatives (GoGrid, Amazon Elastic Compute Cloud (EC2), Simple Queue Service (SQS)) have developed various frameworks for cloud resource management and cloud economies using resource optimization techniques. However, because it is believed that cloud resources usage is relatively affordable, research efforts to model a standard pricing procedure that capture the realistic priced value of cloud resources have not received attention.

This paper is positioned to develop a novel approach for pricing C3. The novelty in the model design is in the application of the theory of financial option to price instances of C3. To achieve the set objectives, we apply our three research threads; financial option (to model price movements), real option (to capture the realistic value of the priced resources), and fuzzy logic techniques (to characterize availability and hence the user satisfaction and provider profitability measured as Quality of Service (QoS)). We simulate our model using real trace data with cloudbus (a market-oriented cloud computing simulation toolkit) to validate the model.

Keywords: Financial Options, Option Pricing, Distributed Systems, Cloud Computing, Cloud Compute Commodities

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