Scalable Cost-Efficient Placement and Chaining of Virtual Network Functions
While Network Function Virtualization (NFV) is increasingly gaining momentum, with promising beneﬁts of ﬂexible service function deployment and reduced operations and management costs, there are several challenges that remain to be properly tackled, so that it can realize its full potential. One of these challenges, which has a signiﬁcant impact on the NFV production chain, is effectively and (cost) efﬁciently deploying service functions, while ensuring that service level agreements are satisﬁed and making wise allocations of network resources. Despite recent research activity in the ﬁeld, little has been done towards scalable and cost-efﬁcient placement & chaining of virtual network functions (VNFs) – a key feature for the effective success of NFV. In this thesis, we approach VNF placement and chaining as an optimization problem in the context of Interand Intra-datacenter. We formalize the Virtual Network Function Placement and Chaining (VNFPC) problem and propose a mathematical model to solve it. Our model has established one of the ﬁrst baseline comparison in the ﬁeld of resource management in NFV and has been widely used in the recent literature. We also address scalability of VNFPC problem to solve large instances by proposing a novel ﬁx-and-optimize-based heuristic algorithm for tackling it. Further, we extensively measure the performance limitations of realistic NFV deployments. Based on that, we propose an analytical model that accurately predict incurred operational costs. Then, we develop an optimal Intra-datacenter service chain deployment mechanism based on our cost model. Finally, we tackle the problem of monitoring service chains in NFV-based environments efﬁciently.
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