Networking plays a crucial role in cloud computing especially in an inter-cloud environment, where data communications among data centers located at different geographical sites form the foundation of inter-cloud federation. Data transmissions required for inter-cloud federation in the complex inter-cloud networking system are often point-to-multi points, which calls for a more effective and efficient multicast routing algorithm in complex networking systems. In this paper, we investigate the multicast routing problem in the inter-cloud context with K constraints where K ≥ 2. Unlike most of existing algorithms that are too complex to be applied in practical scenarios, a novel and fast algorithm for establishing multicast routing tree for interclouds is proposed. The proposed algorithm leverages an entropybased process to aggregate all weights into a comprehensive metric, and then uses it to search a multicast tree(MT) on the basis of the shortest path tree(SPT). We conduct complexity analysis and extensive simulations for the proposed algorithm from the approximation perspective. Both analytical and experimental results demonstrate that the algorithm is more efficient than a representative multi-constrained multicast routing algorithm in terms of both speed and accuracy, and thus we believe that the proposed algorithm is applicable to the inter-cloud environment.
网络的性能在云服务交付过程中发挥着至关重要的作用。对于终端用户,所获得的服务实质是一种网络-云的组合服务,即云计算用户所得到的服务既包含云服务还包含网络服务。如何从众多候选服务中选出最佳的服务提供给用户已成为云计算研究领域的重要课题。解决该问题需要综合考虑网络和云的诸多服务质量参数,例如延迟、价格和计算能力等。针对该问题将其描述为一类多准则决策(multi-criteria decision making,MCDM)问题,并对比了TOPSIS(technique for order preference by similarity to an ideal solution),ELECTRE(elimination and choice expressing reality)和AHP(analytic hierarchy process)3种常见的多准则决策算法。利用理论分析和数值计算方法对3种算法在网络-云服务选择的优劣展开了对比和探讨。
