Software Defined Resource Allocation for Service-Oriented Networks

To support multiple on-demand services over several fixed communication networks, the network operators must allow flexible customization and fast provision of their network resources. One effective approach is network virtualization, whereby each service is mapped to a virtual subnetwork providing dedicated on-demand support. In practice, each service consists of a pre specified sequence of functions, called a service function chain (SFC). Moreover, each function in a SFC can only be provided by some given network nodes. Thus, to support a given service, we must select network function nodes according to the SFC, and determine the routing strategy through the function nodes in the specified order. A crucial problem that needs to be addressed is how to optimally allocate the network resources while satisfying multiple service requirements specified by the service function chains, subject to link and node capacity constraints. In this paper, we formulate the problem as a mixed binary linear program and establish its NP-hardness. Furthermore, we propose an efficient penalty successive upper bound minimization algorithm to solve the problem. We also present simulation results to demonstrate the effectiveness of the proposed algorithm.