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Service function chaining (SFC), consisting of a sequence of virtual network functions (VNFs), is the de-facto service provisioning mechanism in VNF-enabled data centers (VDCs). However, for the SFC, the dynamic and diverse virtual machine (VM) traffic must traverse a sequence of VNFs possibly installed at different locations at VDCs, resulting in prolonged network delay, redundant network traffic, and large consumption of cloud resources (e.g., bandwidth and energy). Such adverse effects of the SFC, which we refer to as SFC traffic storm, significantly impede its efficiency and practical implementation.In this paper, we solve the SFC traffic storm problem by proposing AggVNF, a framework wherein the VNFs of an SFC are implemented into one aggregate VNF while multiple instances of aggregate VNFs are available in the VDC. AggVNF adaptively allocates and migrates aggregate VNFs to optimize cloud resources in dynamic VDCs while achieving the load balance of VNFs. At the core of the AggVNF are two graph-theoretical problems that have not been adequately studied. We solve both problems by proposing optimal, approximate, and heuristic algorithms. Using real traffic patterns in Facebook data centers, we show that a) our VNF allocation algorithms yield traffic costs 56.3% smaller than the latest research using the SFC design, b) our VNF migration algorithms yield 84.2% less traffic than the latest research using the SFC design, and c) VNF migration is an effective technique in mitigating dynamic traffic in VDCs, reducing the total traffic cost by up to 24.8%.