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In network function virtualization, a service function chain (SFC) specifies a sequence of virtual network functions that user traffic has to traverse to realize a network service. The problem of SFC orchestration has been extensively studied in the literature. However, most existing works assume deterministic demands and resort to costly runtime resource reprovisioning to deal with dynamic demands. In this work, we formulate the deadline-aware co-located and geo-distributed SFC orchestration with demand uncertainty as robust optimization problems and develop exact and approximate algorithms to solve them. A key feature of our formulation is the consideration of end-to-end delay in service chains by carefully modeling load-independent propagation delay as well as load-dependent queueing and processing delays. To avoid frequent resource reprovisioning, our algorithms utilize uncertain demand knowledge to …