Benjamin Blau

Cloud Computing – A Classification, Business Models, and Research Directions

Lately, a new computing paradigm has emerged: “Cloud Computing”. It seems to be promoted as heavily as the “Grid” was a few years ago, causing broad discussions on the differences between Grid and Cloud Computing. The first contribution of this paper is thus a detailed discussion about the different characteristics of Grid Computing and Cloud Computing. This technical classification allows for a well-founded discussion of the business opportunities of the Cloud Computing paradigm. To this end, this paper first presents a business model framework for Clouds. It subsequently reviews and classifies current Cloud offerings in the light of this framework. Finally, this paper discusses challenges that have to be mastered in order to make the Cloud vision come true and points to promising areas for future research.

Business Models in the Service World

The authors provide a criteria catalogue to characterize cloud computing and their own Cloud Business Ontology Model to classify current product offerings and pricing models.

A multidimensional procurement auction for trading composite services

Recently, static value chains have gradually been giving way to highly agile service value networks. This involves novel economic and organizational challenges. Added value for customers is created by feasible compositions of distributed service components. This work focuses on the design of a multidimensional procurement auction for trading service compositions and the analysis of strategies for service providers that participate in the procurement process. The mechanism implementation is incentive-compatible, so that it results in an equilibrium in which revealing the true multidimensional type (quality of service and valuation) is a weakly-dominant strategy for all service providers. Due to combinatorial restrictions imposed by the underlying graph topology, the winner determination problem can be solved in polynomial time, in contrast to computationally-intractable combinatorial auctions which cannot be solved this way. Furthermore, we provide a simulation-based analysis based on a reinforcement learning model of bundling and unbundling strategies of service providers that participate in the auction. Based on our results we discuss strategic recommendations for service providers depending on how they are situated within the network.

How to Coordinate Value Generation in Service Networks

The fundamental paradigm shift from traditional value chains to agile service value networks implies new economic and organizational challenges. As coordination mechanisms, auctions have proven to perform quite well in situations where intangible and heterogeneous goods are traded. Nevertheless, traditional approaches in the area of multidimensional combinatorial auctions are not quite suitable to enable the trade of composite services. A flawless service execution and therefore the requester’s valuation highly depends on the accurate sequence of the functional parts of the composition, meaning that in contrary to service bundles, composite services only generate value through a valid order of their components. The authors present an abstract model as a formalization of service value networks. The model comprehends a graph-based mechanism implementation to allocate multidimensional service offers within the network, to impose penalties for non-performance and to determine prices for complex services. The mechanism and the bidding language support various types of QoS attributes and their (semantic) aggregation. It is analytically shown that this variant is incentive compatible with respect to all dimensions of the service offer (quality and price). Based on these results, the authors numerically analyze strategic behavior of participating service providers regarding possible collusion strategies.

Planning and Pricing of Service Mashups

Todays development and provision of commercially used Web services has shifted from providing static and predefined functionality to highly configurable services that can be dynamically combined by customers. This new form of composed services called service mashups integrate functionality of multiple sub-services from decentralized providers. Consequently this leads to a high configuration complexity and presents new challenges in the field of planning and pricing of service offerings such as validation of service configurations as well as price determination. Facing these challenges this paper presents an ontology framework for describing technical as well as economic interdependencies between services and shows how planning and pricing algorithms for dynamic Web scenarios can be implemented. As proof of concept we present the implementation of a service mashup planner and show how this tool can be used to construct complex services considering technical as well as economic service aspects.

Formation of Service Value Networks for Decentralized Service Provisioning

The provisioning of complex services requires tight collaboration between diverse service providers and their customers harmonizing supply and demand chains to a highly flexible, dynamic and decentralized service value network. Peers in such a network autonomously delegate (sub-)tasks which cannot be done efficiently by themselves to other more suitable peers in their community. In this paper, we propose an architecture for such service communities that features decentralized service provisioning based on current Web technologies. In this context, we present an algorithm for efficient service value network formation and show by means of a simulation that sufficiently sized service networks can fulfill practically all customer requests. When compared to the optimal (central) case, there is a modest price increase for the customers but the overall welfare decreases only insignificantly.

Towards a Model for Measuring Customer Intimacy in B2B Services

This paper proposes an approach for evaluating the relationship with a customer, leading to the creation of a Customer Intimacy Grade (CIG), across multiple levels of granularity: employee, team, business unit and whole organization. Our approach focuses on B2B service organizations which provide their customers with complex solutions and whose relationship with the customer is distributed among multiple employees and across different business units. The suggested approach should improve the systematic analysis of customer intimacy in organizations, leverage the customer knowledge scattered throughout the organization and enable benchmarking and focused investments in customer relationships.

Efficient QoS Aggregation in Service Value Networks

In recent years, the trend towards standardization, simplification and modularization in the service sector has fostered the raise of Service Value Networks where providers and consumers jointly co-create value. With many different competing services available, the user experience, which is captured by the non-functional Quality-of-Service (QoS) attributes, is an important competitive factor. QoS computation for complex Web services, i.e. the aggregation of QoS factors from atomic services, is essential for an automated an optimized Web service selection process. However, the computational complexity of QoS aggregation has often been disregarded in the respective field of research, whereas computational efficiency is inevitable for the application of optimization approaches in on-line scenarios. The threefold contribution of this paper consists of an elaboration on the computational complexity of aggregating QoS, an approximation scheme that allows for a computational efficient optimization and a broad analytical and simulation-based evaluation of this approach.

Risk-Based Decision Support in Service Value Networks

The current trend towards dynamic and highly scalable service provisioning fosters the rise of Software as a Service (SaaS) platforms and so called Compute Clouds. The on-demand provisioning of services gains more and more influence. For offering enriched services that are capable of performing complex tasks, the dynamic composition of such services becomes important. In order to enable the collaboration between different service providers, technical and economic preliminaries have to be made. This work will cover economic considerations from the viewpoint of a service provider. Therefore, the concept of Service Value Networks is presented and an agreement network as underlying legal structure is illustrated. Finally, an approach that enables a service provider to select the risk-minimal combination of contracts is elaborated and discussed.

Service Value Networks: Unleashing the Combinatorial Power of Service Mashups

The long tail phenomenon has been heavily discussed in recent years. What has been neglected so far is its striking relevance for electronic services. Whereas consumers expectations about information goods are often vague and transient, their requirements are pronounced and specific when it comes to the functional and non-functional characteristics of electronic services. Moreover, modular services can be combined and configured into service mashups that have the potential to meet complex consumer requirements. In this vein, the long tail phenomenon can be leveraged into a new dimension – the long valley, where every service exerts positive network externalities on the remaining services, thereby spurring an increase in supply and demand. The combinatorics of constructible service mashups are enabled by universally accessible service orchestration platforms known as Service Value Networks (SVNs). This article shall not only pave the way for a rising research area on a new business trend, but will also help business actors to harness the opportunities opened up by SVNs.