text: As the Software Defined Networking (SDN) paradigm gains momentum, every network operator faces the obvious dilemma: when and how to migrate from existing IP routers to SDN compliant equipments. A single step complete overhaul of a fully functional network is impractical, while at the same time, the immediate benefits of SDN are obvious. A viable solution is thus a gradual migration over time, where questions of which routers should migrate first, and whether the order of migration makes a difference, can be analyzed from techno economic and traffic engineering perspective. In this paper, we address these questions from the techno economic perspective, and establish the importance of migration scheduling. We propose optimization techniques and greedy algorithms to plan an effective migration schedule, based on various techno economic aspects, such as technological gains in combinations with CapEx limitations. We demonstrate the importance of an effective migration sequence through two relevant network management metrics, namely, number of alternative paths availed by a node on migration, and network capacity savings. Our results suggest that the sequence of migration plays a vital role, especially in the early stages of network migration to SDN.
  @cite_8: Network architectures such as Software-Defined Networks (SDNs) move the control logic off packet processing devices and onto external controllers. These network architectures with decoupled control planes open many unanswered questions regarding reliability, scalability, and performance when compared to more traditional purely distributed systems. This paper opens the investigation by focusing on two specific questions: given a topology, how many controllers are needed, and where should they go? To answer these questions, we examine fundamental limits to control plane propagation latency on an upcoming Internet2 production deployment, then expand our scope to over 100 publicly available WAN topologies. As expected, the answers depend on the topology. More surprisingly, one controller location is often sufficient to meet existing reaction-time requirements (though certainly not fault tolerance requirements).
  @cite_1: In dynamic environments, decisions about adopting or replacing new equipment or processes are influenced by the expectation of further innovations in technology. This paper examines the issue of the time at which an equipment (vointage one) currently in use is to be replaced with better equipment (vintage two), in the face of uncertain future availability of even better equipment (vintage three). We present an operational model useful in making adoption timing decisions and then present results that offer interesting insights into the impact of uncertainty and output expansion on the adoption time of vintage two. First, we characterize the optimal adoption time of vintage two in terms of the operating costs of various vintages, switching costs between vintages, and the hazard rate for the time of appearance of vintage three. We indicate the conditions under which it is optimal to follow a "now or never" or a "wait and adopt" policy with respect to adoption of vintage two. Second, it is shown that output expansion need not always spur the adoption of innovations. In fact, under certain conditions, output expansion may delay adoption of vintage two, even though vintage two has a higher operating cost savings per unit fixed cost than vintage three. We indicate how important factors such as benefits of new technologies other than operating cost reductions, learning effects, changes in costs over time, and fixed operating costs can be incorporated in the model.
  @cite_15: This paper describes the basic concepts of the network migration problem, as well as its cost optimal solution with an ant colony algorithm. Generally there are many possible approaches to calculate network migration strategies. One of those is to consider the migration as a Shortest Path Problem, which can be solved using meta heuristics. In this paper it will be analyzed how ant colony optimization can be used to calculate migration sequences with minimized costs. Results of our investigation are information about the speed of convergence of ant colony algorithms towards an optimal cost value. The used resource utilization to cover increasing network demands will be presented also.
  @cite_10: The planning of today's telecommunication networks is a very complex task, because the users and the demanded services as well as the costs to deploy and operate the network are evolving over time. Because of this reason, forecasts are made, which are inaccurate in nature. The dynamic and uncertain character of the input parameters needs to be taken into account during the network planning process. This PhD dissertation studies some important techno-economic aspects of the planning process, focusing on optical telecommunication networks, which form the basis of a lot of core networks of important telecom operators. Concerning the dynamic character of network traffic and equipment costs, our research compares the use of single period planning, anticipated planning and multi-period planning and their relation with investment selection techniques. Concerning the uncertain character of traffic demand and equipment costs, the well-known techniques using safety margins is evaluated and the use of Real Options thinking (originating from a stock option valuation technique) is illustrated. Furthermore, a lot of attention is given to the development of a cost model for a network operator, paying special attention to operational expenses. An activity-based cost model allows to quantify the operational expenses of the network operator. Therefore, different operational processes like maintenance, repair, service provisioning and pricing billing are distinguished. The process-based operational expenditures together with the continuous costs of infrastructure (costs for floor space rental, energy consumption, etc.) constitute the total operational expenditures for the telecom operator. Finally, we indicate how the suggested cost models can be applied in a liberalized telecom market.
  @cite_12: For long-term operated networks, pre-planning is a challenging task due to uncertainty in future demand requests. In this paper we first address the question of how severe the impact of demand uncertainty on the network costs really is. Results indicate that only for special cases, uncertainty is interesting to be addressed in the planning process itself. Additionally, we introduce a Stochastic Programming model in order to handle the influence of such a special case. It can be observed that including an improbable demand development into the planning process leads to cost efficient network solutions for all considered scenarios.
summary: A choice of the prediction interval for the demand and cost forecast has been studied in @cite_10 , where it was shown that short prediction intervals may not be able to sufficiently account for future evolutions, while long prediction intervals may be uncertain. An efficient ant colony meta heuristic for the multi-layer, multi-period migration problem formulated as a path-finding problem is proposed in @cite_15 . Stochastic programming approaches have also been proposed to better handle the uncertainties, as in @cite_12 . Timing issues of migration to a new technology have also been studied, and it was shown that demand growth, migration cost, and cost savings from the new technology must be considered @cite_1 . @cite_8 , the number and location of SDN controllers is studied, which is an important related aspect, but outside the scope of this paper.