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Network Function Virtualization (NFV) is a promising virtualizationtechnology that has the potential to significantly reduce the expenses andimprove the service agility. NFV makes it possible for Internet ServiceProviders (ISPs) to employ various Virtual Network Functions (VNFs) withoutinstalling new equipments. One of the most attractive approaches in NFVtechnology is a so-called Joint Placement and Allocation of Virtual NetworkFunctions (JPA-VNF) which considers the balance between VNF investment withQuality of Services (QoS). We introduce a novel capability function to measurethe potential of locating VNF instances for each server in the proposed OJPA-HSmodel. This model allows the servers in the network to be heterogeneous, at thesame time combines and generalizes many classical JPA-VNF models. Despite itsNP-hardness, we present a provable best-possible deterministic online algorithmbased on dynamic programming (DP). To conquer the high complexity of DP, wepropose two additional randomized heuristics, the Las Vegas (LV) and MonteCarlo (MC) randomized algorithms, which performs even as good as DP with muchsmaller complexity. Besides, MC is a promising heuristic in practice as it hasthe advantage to deal with big data environment. Extensive numericalexperiments are constructed for the proposed algorithms in the paper.

Online Joint Placement and Allocation of Virtual Network Functions with Heterogeneous Servers