The hub location problem with single assignment is the problem of locating hubs and assigning the terminal nodes to hubs in order to minimize the cost of hub installation and the cost of routing the traffic in the network. There may also be capacity restrictions on the amount of traffic that can transit by hubs. The aim of this paper is to investigate polyhedral properties of these problems and to develop a branch and cut algorithm based on these results. © Springer-Verlag 2004

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Software‐Defined Networking and Network Function Virtualization are two paradigms that offer flexible software‐based network management. Service providers are instantiating Virtualized Network Functions, for example, firewalls, DPIs, gateways—to highly facilitate the deployment and reconfiguration of network services with reduced time‐to‐value. They use Service Function Chaining technologies to dynamically reconfigure network paths traversing physical and virtual network functions. Providing a cost‐efficient virtual function deployment over the network for a set of service chains is a key technical challenge for service providers, and this problem has recently caught much attention from both Industry and Academia. In this article, we propose a formulation of this problem as an Integer Linear Program that allows one to find the best feasible paths and virtual function placement for a set of services with respect to a total financial cost, while taking into account the (total or partial) order constraints for Service Function Chains of each service and other constraints such as end‐to‐end latency, anti‐affinity rules between network functions on the same physical node and resource limitations in terms of network and processing capacities. Furthermore, we propose a heuristic algorithm based on a linear relaxation of the problem that performs close to optimum for large scale instances. © 2017 Wiley Periodicals, Inc. NETWORKS, Vol. 71(2), 97–106 2018

Abstract-The effect of virus spreading in a telecommunication network, where a certain curing strategy is deployed, can be captured by epidemic models. In the N -intertwined model proposed and studied in [1], [2], the probability of each node to be infected depends on the curing and infection rate of its neighbors. In this paper, we consider the case where all infection rates are equal and different values of curing rates can be deployed within a given budget, in order to minimize the overall infection of the network. We investigate this difficult optimization together with a related problem where the curing budget must be minimized within a given level of network infection. Some properties of these problems are derived and several solution algorithms are proposed. These algorithms are compared on two real world network instances, while Erdös-Rényi graphs and some special graphs such as the cycle, the star, the wheel and the complete bipartite graph are also addressed.

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