In emerging domains such as Cloud-based Industrial Control Systems (ICSs) and SCADA systems where data-intensive and high performance computing are needed, a higher degree of flexibility is being demanded to meet new stakeholder requirements, context changes and intrinsic complexity. In this light, Dynamic Software Product Lines (DSPLs) provide a way to build self-managing systems exploiting traditional product line engineering concepts at runtime. Although context-awareness is widely perceived to be a firstclass concern in such runtime variability mechanisms, existing approaches do not provide the necessary level of formalization to model and enact context variability for DSPLs. This is crucial for operational analytics processes since variant configuration could di↵er from context to context depending on diverse data values linked to context features and cross-tree constraints in a feature model. In this paper, we propose a context variability modeling approach, demonstrate its applicability and usability via a wind farm use case, and present the fundamental building blocks of a framework for enabling context variability in service-based DSPLs which provide Workflow as a Service (WFaaS).

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The variability scale in large-scale Cyber-Physical Systems (CPSs) is high and complex due to the voluminousness, dynamicity and diversity of available computing resources (people, things and software services), domain-specific processes, domain-specific elements (stakeholders, assets and contracts), and their relationships. This requires us to go beyond current variability modeling and management techniques which neglect the complexity and the diversity of relevant stakeholders, data and assets, and thus cannot cope with intelligent business and analytics requirements in dynamic environments, such as smart city management. In this paper, we present a comprehensive analysis for understanding the multi-perspective variability in processes atop people, data and things in CPSs, particularly, for the sustainability governance of Smart Green Buildings (SGBs). We examine domain-specific processes and domainspecific elements and their relationships to derive a multipleperspective variability management for SGBs. On the basis of this, we conceptualize a novel model for the multi-perspective process variability representation.

The proposed framework lets developers model and manage process variability by composing base models, fragments, and variability models and by deferring binding to run time. Base models