R P Sundarraj

Cloud computing offers computing and storage services which can be dynamically developed, composed and deployed on virtualized infrastructure. Cloud providers holding excess spare capacity, incentivize customers to purchase it by selling them in a market (spot market), where the prices are derived dynamically based on supply and demand. The cloud providers allow clients to bid on this excess capacity by allocating resources to bidders while their bids exceed a intermittently changing dynamic spot price. In this paper we have used game theory to model the bidding strategies of bidders in a spot market who are attempting to procure the cloud instances, as a prisoner dilemma game. We then analyze real time data from Amazon EC2 spot market to validate this model. In a single shot prisoner dilemma game mutual defection is the Nash equilibrium. We find that a majority (approx. 85%) of bidders choose to Defect which is in-line with the single shot classical prisoner dilemma game. However considering that most bidders in a spot market are repetitive bidders, we propose a Co-operation strategy which is in-line with the Iterated Prisoner Dilemma Game. © 2012 IEEE.

Utility computing models such as cloud computing provide a variety of computing services using several pricing options. Flexibility of requirements and availability of pricing options, enable a consumer to make trade-offs between cost and time. These trade-offs are governed by consumers' behavior with respect to how they discount price vis-à-vis time of delivery. In this paper, we study this trade-off for the cloud-computing context, based on theoretical models from the time-discounting (intertemporal) literature. We test this model using an experimental study with 162 participants.

Cloud-computing facilitates consumers to source online storage-services on a pay-as-you-go basis. The sourcing of storage-as-a-service (STaaS) requires a decision maker to contend with several elements such as pricing structure, application characteristics and quality-of-service requirements, in addition to tactical considerations such as risk propensity and supplier diversification. This makes STaaS sourcing a complex task. Discussion on STaaS sourcing models addressing these aspects and their utility to decision-makers is, however, scant. In this paper, we propose a two-stage holistic approach based on Data Envelopment Analysis (DEA) and Goal programming (GP). We derive insights provided by these models from 10800 runs using market-based data. We also use an experiment to assess our hypothesis concerning the impact of task complexity on decision-quality. Both these experiments have implications for different business scenarios in the STaaS market, and for decision-making. We discuss these managerial implications, and present a prototype Decision Support System (DSS) to aid STaaS selection.

Purpose – This study aims to investigate the decisions related to business aspects of cloud computing and discuss the research density, models/techniques used and identify opportunities for future work. Design/methodology/approach – In this paper, 155 research articles shortlisted through a systematic review were analyzed and a classification framework was developed. Using this framework, the research density is discussed and a detailed review of four widely researched decision themes is provided. Findings – It was found that current research on business aspects is spread across 23 decision themes. The distribution, however, is skewed with 50 per cent pertaining to just four themes, namely, pricing, markets, sourcing and adoption. Simulation appears to be the preferred modeling approach. Decision themes in consumer behavior, sustainability, auditing and culture offer opportunities for future research. Research limitations/implications – The classification framework organizes extant research on applied models and allows researchers to identify potential avenues for application, improvement and development of models to support business decisions. The review is limited to academic articles and does not include industry reports. Practical implications – Practitioners can readily understand various perspectives relevant to a decision theme such as pricing or sourcing, seek and use associated models such as simulation, optimization and game theory to support their decision-making. Originality/value – Most of the extant review paper deal with cloud computing technology. This study is the first systematic review on the models applied to business aspects of cloud computing. This study provides a classification framework and explicitly lists associated decision themes, models/ techniques and opportunities.

Cloud computing has transformed the decision-making processes involved in the procurement of information-technology services. Not only has it brought about tremendous speed-ups to computing jobs, but also, the flexibility it provides in terms of availability and pricing options now enables a consumer to make trade-offs between price and time, based on the situation on-hand and the turnaround-time requirements. These price-time trade-offs have been studied in the behavioral-economic literature, but have not been considered formally in the procurement and the cloud-system bodies of literature. We fill this gap, by taking up the question of how the impatience characteristics of the procurer (and in turn his/her procurement decisions) get affected by two behavioral factors, namely, delay horizon and situational involvement. We test the model using a factorial experiment with 180 participants and find that impatience degree and type are affected by delay horizon and situational involvement. We discuss practical implications for a cloud-service provider, as well as implications for the intertemporal and IS literature.

Cloud computing has emerged as a key information technology and systems model over the last few years. Major organizations have developed and delivered cloud computing solutions and continue to do so. Consequently, a number of strides were made in the advancement of technology leading to a growth in the adoption of cloud computing. The growing recognition of cloud computing services necessitates a focus on the business aspects of cloud. However, we feel that research in this area is scant. To this effect, we performed a systematic review of cloud computing literature and reviewed 2891 abstracts and 157 articles published until the year 2012. Based on the findings of the review, we establish a framework for organising the extant research on cloud business aspects. Using the framework, we find cloud economics to be the most widely researched business aspect. In this paper, we provide a detailed review of the application of decision models in the context of cloud economics, with a specific focus on pricing and markets. The proposed framework and review results serve as a reference to IS researchers and practitioners to understand decision situations, models and opportunities. © Springer International Publishing Switzerland 2014.

Cloud computing offers information technology resources like infrastructure, platform and software in the form of on-demand services. Adoption of cloud yields several benefits to the consumer and these benefits could be realized to their fullest potential in a market based mechanism. At present, commercial marketplaces for cloud-based services are in their infancy. Nevertheless, we are gradually moving towards marketplaces like Amazon AWS. In future, electronic agents would negotiate on the behalf of consumers in procuring a service from cloud markets. In negotiating a cloud-service, the agents should be capable of representing their principals' preferences. These preferences help the agents to improve the outcome of a negotiation. The possibility of a successful outcome can be enhanced by exploiting trade-offs that are driven by preferences among multiple issues. One such preference is time preference which can modeled using time discount functions and is useful in generating price and time trade-offs. In this paper, we propose a hyperbolic discounting model based on the theory of intertemporal choice to generate price and time trade-offs. Further, we provide an algorithm to integrate hyperbolic discounting function based trade-off model with a time dependent tactic (TDT) based concession model in the negotiation process. © 2012 IEEE.