Cloud computing represents a major change in how resources of information technology are delivered and consumed and will influence the telecom industry, its future services, business offerings and economics of the telecommunication. New revenues potentials from mediating cloud‐based services are however less discussed, as well as the commonly accepted and completed methodology for this purpose is lacking. The objective of this paper is to clearly identify recommended roles for telecommunication companies (telcos) in the cloud value chain and to present a model for assessing and optimising innovative business opportunities. In particular, we show how the portfolio theory of modern investment science supports risk management in operation of telecom company‐based cloud carriers for service brokering.We recommend a combined broker and carrier role to be a preferred cloud business model for a telco. Such combination is expected to represent the best value proposition for competing against cloud providers and ICT integrators. Further quantitative analysis indicates significant business benefits from differentiating and optimising provision of carrier grade and best effort network connectivity types for a given bundle of cloud services. This implies an efficient use of telco assets and satisfies an increasing demand for network performance in the business market.The novelty of the paper is the developed quantitative optimisation model as well as the analytical identification of the preferred telco role in cloud value network. Practical application of the research may improve dimensioning of technological assets, leading to higher cost efficiency and possibly higher degree of customer satisfaction. Copyright © 2013 John Wiley & Sons, Ltd.

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Process models represent valuable resources for integration and alignment of business processes. Nowadays, due to networked business and tighter integration along a value chain, the number of enterprises that need to orchestrate their workflows is increasing. These circumstances urge companies to improve management of process models and templates. Machine-readable and interoperable semantics of the process templates facilitate retrieval and reuse. However, the heterogeneity of both model representations and modeling languages makes it difficult to retrieve, comprehend, compare, and reuse the templates. Therefore, in this chapter we elaborate on the semantic annotation of process model templates consisting of three basic parts: meta-model, domain, and goal annotations. For this purpose, we use ontologies representing generic constructs of process models, concepts from a business domain, and business goals. We illustrate application of the approach in OWL and provide a case study with exemplary semantic queries.

Effective discovery and sharing of process models within and/or across enterprises are important in process model management. A semantic annotation approach has been applied for specifying process semantic heterogeneity in the semantic process model discovery in our previous work. In this paper, the approach is further developed into a complete and systematic semantic annotation framework. Four perspectives are tackled in our framework: basic description of process models (profile annotation), process modeling languages (meta-model annotation), process models (model annotation) and the purpose of the process models (goal annotation). Ontologies, including modeling ontology, domain specific ontology and goal ontology, are used for annotation of process models to achieve semantic interoperability. A set of mapping strategies are defined to guide users to annotate process models.

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This paper develops models for the analysis of a cloud brokering platform under conditions of risk and demand uncertainty, focusing on controlling the risk of not delivering the quality of service required by users. Such risk can occur as a result of inherent limitations of the best-effort connectivity. We take the approach of modern portfolio theory and show how the trade-off between risk and profit can be chosen by selecting efficient connectivity portfolios that combine the best-effort connectivity of different grades with premium-grade connectivity. We provide theoretical analysis of connectivity portfolio models and related insights delivered by numerical experiments that utilize the measurements of Internet traffic.