Network function virtualization foresees the virtualization of service functions and their execution on virtual machines. Any service is represented by a service function chain (SFC) that is a set of VNFs to be executed according to a given order. The running of VNFs needs the instantiation of VNF Instances (VNFIs) that in general are software modules executed on virtual machines. The virtualization challenges include: 1) where to instantiate VNFIs; ii) how many resources to allocate to each VNFI; iii) how to route SFC requests to the appropriate VNFIs in the right sequence; and iv) when and how to migrate VNFIs in response to changes to SFC request intensity and location. We develop an approach that uses three algorithms that are used back-to-back resulting in VNFI placement, SFC routing, and VNFI migration in response to changing workload. The objective is to first minimize the rejection of SFC bandwidth and second to consolidate VNFIs in as few servers as possible so as to reduce the energy consumed. The proposed consolidation algorithm is based on a migration policy of VNFIs that considers the revenue loss due to QoS degradation that a user suffers due to information loss occurring during the migrations. The objective is to minimize the total cost given by the energy consumption and the revenue loss due to QoS degradation. We evaluate our suite of algorithms on a test network and show performance gains that can be achieved over using other alternative naive algorithms

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The Network Function Virtualization (NFV) technology aims at virtualizing the network service with the execution of the single service components in Virtual Machines activated on Commercial-off-the-shelf (COTS) servers. Any service is represented by the Service Function Chain (SFC) that is a set of VNFs to be executed according to a given order. The running of VNFs needs the instantiation of VNF instances (VNFI) that in general are software components executed on Virtual Machines. In this paper we cope with the routing and resource dimensioning problem in NFV architectures. We formulate the optimization problem and due to its NP-hard complexity, heuristics are proposed for both cases of offline and online traffic demand. We show how the heuristics works correctly by guaranteeing a uniform occupancy of the server processing capacity and the network link bandwidth. A consolidation algorithm for the power consumption minimization is also proposed. The application of the consolidation algorithm allows for a high power consumption saving that however is to be paid with an increase in SFC blocking probability.

The definition of a virtual router layer allows the application of energy saving techniques based on the migration of virtual routers within the physical infrastructure as traffic conditions change. As traffic decreases, physical resources can be vacated through virtual router migration, thus, saving energy. Such resources can be reclaimed if needed because of traffic increase. Unfortunately, the migration of virtual routers involves reconfiguration costs depending on implementation details and characterized, for instance, by the revenue loss due to Quality-of-Service (QoS) degradation during the migration process. In this paper, we propose a methodology based on the Markov decision processes for the evaluation of optimal migration policies taking into account both the operation (in terms of energy consumption) and reconfiguration costs

The power consumption of the network equipment has increased significantly and some strategies to contain the power used in the IP network are needed. Among the green networking strategies, the virtualization class and in particular the deployment of migrating virtual routers can lead to a high energy saving. It consists in migrating virtual routers in fewer physical nodes when the traffic decreases allowing for a power consumption saving. In this paper we formulate the problem of minimizing the power consumption as a Mixed Integer Linear Programming (MILP) problem. Due to the hard complexity of the introduced MILP problem, we propose a heuristic for the migration of virtual routers among physical devices in order to turn off as many nodes as possible and save power according to the compliance with network node and link capacity constraints. We show that 50% of nodes may be turned off in the case of a real provider network when traffic percentage reduction of 80% occurs. Finally we also perform a feasibility study by means of an experimental test-bed to evaluate migration time of a routing plane based on QUAGGA routing software.