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_9: ■ Abstract Sociologists often model social processes as interactions among variables. We review an alternative approach that models social life as interactions among adaptive agents who influence one another in response to the influence they receive. These agent-based models (ABMs) show how simple and predictable local interactions can generate familiar but enigmatic global patterns, such as the diffusion of information, emergence of norms, coordination of conventions, or participation in collective action. Emergent social patterns can also appear unexpectedly and then just as dramatically transform or disappear, as happens in revolutions, market crashes, fads, and feeding frenzies. ABMs provide theoretical leverage where the global patterns of interest are more than the aggregation of individual attributes, but at the same time, the emergent pattern cannot be understood without a bottom up dynamical model of the microfoundations at the relational level. We begin with a brief historical sketch of the shift from “factors” to “actors” in computational sociology that shows how agent-based modeling differs fundamentally from earlier sociological uses of computer simulation. We then review recent contributions focused on the emergence of social structure and social order out of local interaction. Although sociology has lagged behind other social sciences in appreciating this new methodology, a distinctive sociological contribution is evident in the papers we review. First, theoretical interest focuses on dynamic social networks that shape and are shaped by agent interaction. Second, ABMs are used to perform virtual experiments that test macrosociological theories by manipulating structural factors like network topology, social stratification, or spatial mobility. We conclude our review with a series of recommendations for realizing the rich sociological potential of this approach.
  @cite_13: New network technologies constantly seek to displace incumbents. Their success depends on technological superiority, the size of the incumbent's installed base, users' adoption behaviors, and various other factors. The goal of this paper is to develop an understanding of competition between network technologies and identify the extent to which different factors, in particular converters (a.k.a. gateways), affect the outcome. Converters can help entrants overcome the influence of the incumbent's installed base by enabling cross-technology interoperability. However, they have development, deployment, and operations costs and can introduce performance degradations and functionality limitations, so that if, when, why, and how they help is often unclear. To this end, the paper proposes and solves a model for adoption of competing network technologies by individual users. The model incorporates a simple utility function that captures key aspects of users' adoption decisions. Its solution reveals a number of interesting and at times unexpected behaviors, including the possibility for converters to reduce overall market penetration of the technologies and to prevent convergence to a stable state, something that never arises in their absence. The findings were tested for robustness, e.g., different utility functions and adoption models, and found to remain valid across a broad range of scenarios.
  @cite_6: With a cryptographic root-of-trust for Internet routing(RPKI [17]) on the horizon, we can finally start planning the deployment of one of the secure interdomain routing protocols proposed over a decade ago (Secure BGP [22], secure origin BGP [37]). However, if experience with IPv6 is any indicator, this will be no easy task. Security concerns alone seem unlikely to provide sufficient local incentive to drive the deployment process forward. Worse yet, the security benefits provided by the S*BGP protocols do not even kick in until a large number of ASes have deployed them. Instead, we appeal to ISPs' interest in increasing revenue-generating traffic. We propose a strategy that governments and industry groups can use to harness ISPs' local business objectives and drive global S*BGP deployment. We evaluate our deployment strategy using theoretical analysis and large-scale simulations on empirical data. Our results give evidence that the market dynamics created by our proposal can transition the majority of the Internet to S*BGP.
  @cite_11: The rate of deployment and adoption issues of new network technologies, IPv6 in particular, have recently been hotly debated in the research community. However, the question of how protocols migrate, especially the dynamics of migration, to new paradigms is still largely open. In this paper, we address the issue from a game theoretic point of view. We model and analyze the profit maximizing strategies of Autonomous Systems (ASes); both the properties of ASes and the topology of the Internet is considered. The contribution of our work is threefold. First, we propose an economic model of the ASes and their relations from the IPv4-IPv6 migration viewpoint. Second, we apply the findings of evolutionary dynamics on the problem of migration by incorporating Internet-specific properties to the evolutionary model, namely the size of the ASes and the cost of migration. The analyses show that even if IPv6 has higher payoff than IPv4, the whole migration does not happen always fast. Finally, extensive simulations are carried out based on the proposed models to illustrate the impacts of different parameters on the IPv6 migration dynamics in realistic scenarios.
summary: Network migration has been studied using and models. In the system dynamics approach, the migration problem is treated as a dynamic system @cite_13 , where the rate of migration depends on number of migrated agents in the system. On the other hand, in an agent-based approach @cite_9 , the system consists of an ensemble of agents, each trying to increase its own utility. Such studies have mostly been conducted for IPv6 @cite_11 and secure BGP @cite_6 .