A Fast Local Search Algorithm for Virtual Network Embedding

• Main Authors: Wang, Wei Yi, 王偉一
• Other Authors: Chang, Cheng Shang
• Format: Others
• Language: en_US
• Published: 2016
• Online Access: http://ndltd.ncl.edu.tw/handle/66124207234591887052

碩士 === 國立清華大學 === 通訊工程研究所 === 104 === Network virtualization is a popular topic about providing next-generation Internet services. It primarily virtualizes the resources managed by the Infrastructure Provider (InP) and the demands claimed by the Service Provider (SP) to make the concepts of the resource allocation and the user isolation to be more clearly. We inspired by the insight of the pricing problem, so that we set the price of virtual requests on the objective function. Then we focuses on a relatively fast algorithm for solving the VNE than exact solutions. We propose the Permutation Swap Method (PSM) to nd a local optimal solution in a reasonable computation time (few seconds). The PSM represents a network mapping by a node permutation, and it iteratively swaps two nodes' permutation to obtain a lower objective value until reaching a local minimum. We apply four different algorithms: Best Fit with Greedy Selection (BF-GS), Best Fit with Random Selection (BF-RS), Mixed Random Fit with Greedy Selection (MRF-GS) and Mixed Random Fit with Random Selection (MRF-RS) in the PSM, and we conduct experiments to compare the performance and efficiency of these algorithms in three data center networks: Fat-Tree, BCube, VL2 and an inter-data-center network: Cogent. The experimental results are that the algorithm without random factor has the worst performance, and the performance gain by using the greedy selection is less than the one by using the mixed random t solution. Hence to take into account both the performance and efficiency, the MRF-RS method is the best algorithm.