Efficient Network Resource Preallocation on Demand in Multitenant Cloud Systems

Fair bandwidth guarantee has always been a problem in cloud center networks. Normally, tenants are selfish and their selfishness is not well controlled by existing network resource allocation methods, which usually results in link congestion and unfair allocation. Thus, it is critical for cloud providers to balance and at the same time maximize the network resource utilization rate to fairly provide bandwidth for tenants on demand. Inspired by this, this paper proposes a network resource preallocation model, which could be applied in cloud centers using software-defined network technology. Based on network model and tenants’ bandwidth demands, cloud providers could generate enormous resource preallocation strategies and choose the optimal one from them. As an issue of computational time consumption, we further use a genetic algorithm in the optimal strategy choosing procedure. The experiment results show that our method has maximally 15% improvement on the decrease of unsatisfied bandwidth demands of tenants comparing with common equal cost multipaths method.