Topology-Awareness and Re-optimization Mechanism for Virtual Network Embedding

Abstract

Embedding of virtual network (VN) requests on top of a shared physical network poses an intriguing combination of theoretical and practical challenges. Two major problems with the state-of-the-art VN embedding algorithms are their indifference to the underlying substrate topology and their lack of re-optimization mechanisms for already embedded VN requests. We argue that topology-aware embedding together with re-optimization mechanisms can improve the performance of the previous VN embedding algorithms in terms of acceptance ratio and load balancing. The major contributions of this thesis are twofold: (1) we present a mechanism to differentiate among resources based on their importance in the substrate topology, and (2) we propose a set of algorithms for re-optimizing and re-embedding initially-rejected VN requests after fixing their bottleneck requirements. Through extensive simulations, we show that not only our techniques improve the acceptance ratio, but they also provide the added benefit of balancing load better than previous proposals. The metrics we use to validate our techniques are improvement in acceptance ratio, revenue-cost ratio, incurred cost, and distribution of utilization