An evolutionary controllers' placement algorithm for reliable SDN networks

International audienceSDN controllers placement in TelCo networks are generally multi-objective and multi-constrained problems. The solutions proposed in the literature usually model the placement problem by providing a mixed integer linear program (MILP). Their performances are, however, quickly limited for large sized networks, due to the significant increase in the computational delays. In order to avoid the inherent complexity of optimal approaches and the lack of flexibility of heuristics, we propose in this paper a genetic algorithm designed from the NSGA II framework that aims to deal with the controller placement problem. Genetic algorithms can, indeed, be both multi-objective, multi-constraints and can be designed to be computed in parallel. They constitute a real opportunity to find good solutions to this category of problems. Furthermore, the proposed algorithm can be easily adapted to manage dynamic placements scenarios. The goal chosen, in this work, is to maximize the clusters average connectivity and to balance the control's load between clusters, in a way to improve the networks' reliability. The evaluation results on a set of network topologies demonstrated very good performances, which achieve optimal results for small networks

Controller Placement in Vehicular Networks: A Novel Algorithm Utilizing Elite Opposition-Based Salp Swarm and an Adaptable Approach

The rapid advancement of networking technology has enabled small devices to have communication capabilities, but the current decentralized communication system is not ideal for heterogeneous networks like vehicular networks. The integration of routing, switching, and decision-making capabilities in the same network device limits innovation and impedes performance in decentralized networks, especially in vehicular networks where network topologies change frequently. To address the demands of such networks, Software-Defined Networking (SDN) provides a promising solution that supports innovation. However, SDN's single-controller-based system may restrict the network's operational capabilities, despite being programmable and flexible. This paper suggests two methods to tackle the complex problem of controller placement in SDN: an adaptable approach based on OpenFlow protocol in OpenNet and an evolutionary algorithm called Elite Opposition-Based Salp Swarm Algorithm (EO-SSA) to minimize propagation latency, load imbalance, and network resilience. Multiple controllers increase the network's capabilities and provide fault tolerance, but their placement requires a trade-off among various objectives. The proposed methods have been evaluated and analyzed to confirm their effectiveness. The current decentralized network system is not adequate for vehicular networks, and SDN offers a promising solution that supports innovation and can meet the current demands of such networks

POCO-MOEA: Using Evolutionary Algorithms to Solve the Controller Placement Problem

One of the central tenets of a Software Defined Network (SDN) is the use of controllers, which are responsible for managing how traffic flows through switches, routers, and other data-passing devices on a computer network. Most modern SDNs use multiple controllers to divide responsibility for network switches while keeping communication latency low. A problem that has emerged since approximately 2011 is the decision of where to place these controllers to create the most \u27optimum\u27 network. This is known as the Controller Placement Problem (CPP). Such a decision is subject to multiple and sometimes con_icting goals, making the CPP a type of Multi-Objective Problem (MOP). The Controller Placement Problem is NP-Hard. This means finding the \u27optimum\u27 solution can become a time-intensive process as network size increases. Multiple algorithms exist to solve MOPs using shortcut (or \u27heuristic\u27) methods which can produce a \u27near-optimal\u27 solution in times much shorter than those necessary to guarantee an \u27optimal\u27 solution. One popular class of algorithms is known as Evolutionary Algorithms (EAs); EAs designed to solve Multi-Objective problems are called Multi-Objective Evolutionary Algorithms (MOEAs). While many MOEAs exist, their application to the Controller Placement Problem is not well explored. The theory of this thesis is that an MOEA can produce solutions to the Controller Placement Problem which are \u27nearly optimal\u27 while keeping execution time low compared to an exhaustive \u27optimal\u27 search. This research extends a network modeling tool called the Pareto Optimal Controller Placement (POCO) Framework with custom designed MOEA, called POCO-MOEA. A series of full-factorial experiments is designed and executed to gather data on POCO-MOEA performance to a series of model networks. The algorithm\u27s behavior is then evaluated and compared to exhaustive search through five metrics; fraction of solution space size, average distance between pareto fronts (δ1), worst-case distance between pareto fronts (δ2), relative hypervolume (hyprel), and relative execution time (brel). Results show that performance is dependent on the size of the network, the topology of the network, and the parameters chosen for POCO-MOEA. In general, performance for POCO-MOEA improves as the size of the network increases. Given a large network (60+ nodes), POCO-MOEA can achieve within 0.4% of δ1, 3% of δ2, and 6% of hyprel while still being 500 times faster than exhaustive search. This research demonstrates and adds a valuable tool to the methods of determining optimal device placement for an SDN while providing steps to using MOEAs in real SDN applications

MystifY : A Proactive Moving-Target Defense for a Resilient SDN Controller in Software Defined CPS

The recent devastating mission Cyber–Physical System (CPS) attacks, failures, and the desperate need to scale and to dynamically adapt to changes, revolutionized traditional CPS to what we name as Software Defined CPS (SD-CPS). SD-CPS embraces the concept of Software Defined (SD) everything where CPS infrastructure is more elastic, dynamically adaptable and online-programmable. However, in SD-CPS, the threat became more immanent, as the long-been physically-protected assets are now programmatically accessible to cyber attackers. In SD-CPSs, a network failure hinders the entire functionality of the system. In this paper, we present MystifY, a spatiotemporal runtime diversification for Moving-Target Defense (MTD) to secure the SD-CPS infrastructure. In this paper, we relied on Smart Grid networks as crucial SD-CPS application to evaluate our presented solution. MystifY’s MTD relies on a set of pillars to ensure the SDN controller resiliency against failures and attacks. The 1st pillar is a grid-aware algorithm that optimally allocates the most suitable controller–deployment location in large-scale grids. The 2nd pillar is a special diversifier that dynamically relocates the controller between heterogeneously configured hosts to avoid host-based attacks. The 3rd pillar is a temporal diversifier that dynamically detours controller–workload between multiple controllers to enhance their reliability and to detect and avoid controller intrusions. Our experimental results showed the efficiency and effectiveness of the presented approach

Energy-aware routing techniques for software-defined networks

Achieving energy efficiency has recently become a key topic of networking research due to the ever-increasing power consumption and CO2 emissions generated by large data networks. This problem is becoming even more concerning and challenging given the drastic traffic increase expected over the next few years. However, the use of efficient energy-aware strategies could overturn this situation reducing the electricity consumption of Internet data transmission networks, as well as contributing to mitigate the environmental impact of other sectors. The existence of redundant network elements with high capacities is a common design practice in current network infrastructures in order to face suddenly failures or peak traffic flows. However, these additional resources remain either unused or barely used most of the time leading to an undesired energy waste. Therefore, putting into sleep mode (i.e. a low-power state) unused elements is an effective and widely-accepted strategy to decrease the consumption of data networks. In this context, SDN can be seen as an attractive solution to achieve the long-awaited energy efficiency in current communications systems, since they allow a flexible programmability suitable for this problem. This doctoral thesis tackles the problem of optimizing the power consumption in SDN through the design of energy-aware routing techniques that minimize the number of network elements required to satisfy an incoming traffic load. Different from existing related works, we focus on optimizing energy consumption in SDN with in-band control traffic in order to close this important gap in the literature and provide solutions compatible with operational backbone networks. Complementing the general aim of improving the energy efficiency in SDN, this research is also intended to cover important related features such as network performance, QoS requirements and real-time operation. Accordingly, this study gives a general perspective about the use of energy efficient routing techniques, which cover integrated routing considerations for the data and control plane traffic in SDN. By using realistic input data, significant values of switched-off links and nodes are reached, which demonstrates the great opportunity for saving energy given by our proposals. The obtained results have also validated the intrinsic trade-off between environmental and performance concerns, considering several performance indicators. These findings confirm that energy-aware routing schemes should be designed considering specific traffic requirements and performance metric bounds. Moreover, it is shown that jointly considering QoS requirements and energy awareness is an effective approach to improve, not only the power consumption, but the performance on critical parameters such as control traffic delay and blocking rate. Similarly, the proposed dynamic traffic allocation with congestion-aware rerouting is able to handle demanding traffic arrival without degrading the performance of higher priority traffic. In general, our proposals are fine-grained, easy to implement and quite balanced and effective in their results looking for a suitable and readily deployment in real-world SDN scenarios. Therefore, the conducted research and contributions reported through this document not only add to what is known about the potential of energy-aware routing techniques, but also stand as a valuable solution on the road to a sustainable networking.L'assoliment de l'eficiència energètica s'ha convertit recentment en un tema clau de recerca de xarxes a causa dels creixents nivells de consum d'energia i emissions de CO2 generats per les xarxes de dades. Aquest problema es torna cada vegada més preocupant i desafiant, donat el dràstic augment del trànsit esperat en els propers anys. No obstant això, l'ús d'estratègies energètiques eficients podria invertir aquesta situació, reduint el consum d'electricitat de les xarxes de dades d'Internet i contribuint a mitigar l'impacte ambiental d'altres sectors. L'existència d'elements de xarxa redundants i amb grans capacitats és una pràctica de disseny habitual en les infraestructures de xarxes actuals per afrontar fallades sobtades o fluxos de trànsit més elevats. Tanmateix, aquests recursos addicionals romanen poc o gens utilitzats la major part del temps, generant un desaprofitament d'energia no desitjat. Per tant, posar en mode de repòs (és a dir, un estat de baixa potència) elements no utilitzats és una estratègia efectiva i àmpliament acceptada per disminuir el consum en xarxes de dades. En aquest context, les xarxes definides per programari (SDN) es poden considerar una solució atractiva per aconseguir l'esperada eficiència energètica en els sistemes de comunicacions actuals, ja que permeten una flexible programabilitat idònia per a aquest problema. Aquesta tesi doctoral aborda el problema d'optimitzar el consum d'energia en SDN a través del disseny de tècniques d'encaminament conscients de l'energia que minimitzen la quantitat d'elements de xarxa necessaris per satisfer una càrrega de trànsit entrant. Diferent dels treballs existents, aquesta tesi es centra a optimitzar el consum d'energia en SDN amb el control de tràfic dins de banda per tancar aquesta important bretxa en la literatura i proporcionar solucions compatibles amb xarxes troncals operatives. Complementant l'objectiu general de millorar l'eficiència energètica en SDN, aquesta recerca també pretén cobrir altres importants paràmetres relacionats, com ara el rendiment de la xarxa, els requisits de qualitat de servei (QoS) i el funcionament en temps real. En conseqüència, aquest estudi ofereix una perspectiva general sobre l'ús de tècniques d'encaminament eficients energèticament, que contempla consideracions integrades per al tràfic de dades i del pla de control en SDN. Prenent dades d'entrada realistes, es van aconseguir desconnectar significatives quantitats d'enllaços i nodes, la qual cosa demostra la gran oportunitat d'estalvi d'energia que ofereixen les nostres propostes. Els resultats obtinguts també validen el estret compromís entre les preocupacions ambientals i les qüestions de rendiment de la xarxa, considerant diversos indicadors de rendiment. Aquests resultats confirmen que els esquemes d'encaminament conscients de l'energia s'han de dissenyar tenint en compte els requisits de tràfic específics i els límits desitjats de les mètriques de rendiment. A més, es demostra que, considerant conjuntament els requisits de QoS i de l'energia necessària, és un enfocament eficaç per millorar, no només el consum d'energia, sinó també el rendiment en paràmetres crítics, com la latència del tràfic de control i la probabilitat de bloqueig. De manera semblant, l'assignació dinàmica de tràfic proposta, amb re-encaminament conscient de la congestió, permet gestionar grans volums de trànsit sense degradar el rendiment de les demandes de major prioritat. En general, les nostres propostes són precises, fàcils d'implementar i bastant equilibrades i efectives en els seus resultats, buscant un desplegament adequat i fàcil en escenaris pràctics de SDN. Per tant, la recerca realitzada i les contribucions contingudes en aquest document no només afegeixen el que es coneix sobre el potencial de les tècniques d'encaminament conscients de l'energia, sinó que també representen una valuosa solució en el camí cap a una xarxa sostenibl

Control plane optimization in Software Defined Networking and task allocation for Fog Computing

As the next generation of mobile wireless standard, the fifth generation (5G) of cellular/wireless network has drawn worldwide attention during the past few years. Due to its promise of higher performance over the legacy 4G network, an increasing number of IT companies and institutes have started to form partnerships and create 5G products. Emerging techniques such as Software Defined Networking and Mobile Edge Computing are also envisioned as key enabling technologies to augment 5G competence. However, as popular and promising as it is, 5G technology still faces several intrinsic challenges such as (i) the strict requirements in terms of end-to-end delays, (ii) the required reliability in the control plane and (iii) the minimization of the energy consumption. To cope with these daunting issues, we provide the following main contributions. As first contribution, we address the problem of the optimal placement of SDN controllers. Specifically, we give a detailed analysis of the impact that controller placement imposes on the reactivity of SDN control plane, due to the consistency protocols adopted to manage the data structures that are shared across different controllers. We compute the Pareto frontier, showing all the possible tradeoffs achievable between the inter-controller delays and the switch-to-controller latencies. We define two data-ownership models and formulate the controller placement problem with the goal of minimizing the reaction time of control plane, as perceived by a switch. We propose two evolutionary algorithms, namely Evo-Place and Best-Reactivity, to compute the Pareto frontier and the controller placement minimizing the reaction time, respectively. Experimental results show that Evo-Place outperforms its random counterpart, and Best-Reactivity can achieve a relative error of <= 30% with respect to the optimal algorithm by only sampling less than 10% of the whole solution space. As second contribution, we propose a stateful SDN approach to improve the scalability of traffic classification in SDN networks. In particular, we leverage the OpenState extension to OpenFlow to deploy state machines inside the switch and minimize the number of packets redirected to the traffic classifier. We experimentally compare two approaches, namely Simple Count-Down (SCD) and Compact Count-Down (CCD), to scale the traffic classifier and minimize the flow table occupancy. As third contribution, we propose an approach to improve the reliability of SDN controllers. We implement BeCheck, which is a software framework to detect ``misbehaving'' controllers. BeCheck resides transparently between the control plane and data plane, and monitors the exchanged OpenFlow traffic messages. We implement three policies to detect misbehaving controllers and forward the intercepted messages. BeCheck along with the different policies are validated in a real test-bed. As fourth contribution, we investigate a mobile gaming scenario in the context of fog computing, denoted as Integrated Mobile Gaming (IMG) scenario. We partition mobile games into individual tasks and cognitively offload them either to the cloud or the neighbor mobile devices, so as to achieve minimal energy consumption. We formulate the IMG model as an ILP problem and propose a heuristic named Task Allocation with Minimal Energy cost (TAME). Experimental results show that TAME approaches the optimal solutions while outperforming two other state-of-the-art task offloading algorithms

Flexible architecture for the future internet scalability of SDN control plane

Software-Defined Networking (SDN) separates the control plane from the data plane. The initial SDN approach involves a single centralized controller, which may not scale properly as a network grows in size. Distributed controllers have emerged to address the disadvantages of a single centralized controller. The control architecture needs to be distributed with traffic control between switches and controllers and among the controllers in order to allow SDNs for several thousand switches. One of the most significant research challenges for distributed controller architectures is to effectively manage controllers, which includes allocating enough controllers to appropriate network locations. To address these daunting issues, we make the following major contributions: This thesis expands the method of solving the Control Placement Problem (CPP) based on the K-means and K-center algorithms to include a Hierarchical Controller Placement Problem (HCPP), located at a high level of Super Controller (SC), a middle level of Master Controllers (MCs), and the lowest level of domain controllers (DCs). The optimization metric addresses latency between the controller and the switches assigned to it.. The proposed architecture and methodology are implemented using the topology of Western European NRENs from the Internet Topology Zoo. The entire network topology is divided into clusters, and the optimal number of controllers (DCs) and their placement are determined for each cluster. MC placement optimization determines the optimal number of MCs and their optimal placement. As a second contribution, an accumulated latency is defined to solve CPP, which takes into account both the latency between the controller and its associated switches and the latency between controllers. Under the constraint of latency, an optimization problem is formulated as per mixed-integer linear programming (MILP). The goal of the research is to reduce accumulated latency while also reducing the number of network controllers and optimizing their placement to achieve an optimal balance. The performance of the developed method is evaluated on Internet2 OS3E real network topology. To achieve the third objective, a metric was developed that includes reliability. The communication latency between controllers should also be considered because a low controller-switch delay does not always imply a short controller-controller delay for a particular controller placement. As the third contribution, we propose a novel metric for CPP to improve the reliability of controllers that takes into account both communication latency and communication reliability between switches and controllers, as well as between controllers. When a single link fails, reliability is taken into account. This aspect concluded by identifying the optimal controller placement to achieve low latencies in control plane traffic. The goal of this project is to reduce the average latency. As the fourth contribution, this study evaluates the Joint Latency and Reliability-aware Controller Placement (LRCP) optimization model. As the evaluation metric, control plane latency (CPL) is defined as the sum of the average switch-to-controller latency and average inter-controller latency. The latency of the control plane, utilizing the actual latencies of the real network topology, is calculated for every optimum placement in the network. In the case of a failure of the single link, the actual CPL for LRCP placements is calculated and evaluated to determine how good LRCP placements are. CPL metrics are used to compare latency and reliability metrics with other models. This study provides proof that the developed methodologies for large-scale networks are highly powerful in terms of searching for all feasible controller placements while assessing the outcomes. In addition, compared to previous work including latency among controllers and reliability for an event of single-link failure.La xarxa definida per programari (SDN) separa el pla de control del pla de dades. L’enfocament SDN inicial implica un únic controlador centralitzat, que pot no escalar correctament a mesura que la xarxa creixi de mida. Els controladors distribuïts han sorgit per abordar els inconvenients d’un únic controlador centralitzat. . Un dels reptes de recerca més importants per a les arquitectures de controladors distribuïts és gestionar de manera eficaç els controladors, que inclou l’assignació de controladors suficients a les ubicacions de xarxa adequades. Per abordar aquests problemes, fem les següents contribucions. Aquesta tesi amplia el mètode de resolució del Problema de Col·locació de Control (CPP) basat en els algorismes de K-means i K-center per incloure un Problema de Col·locació de Controladors Jeràrquics (HCPP), situat a un nivell alt de Super Controller (SC), un nivell de controladors mestres (MC) i el nivell més baix de controladors de domini (DC). La mètrica d’optimització és la latència entre el controlador i els commutadors assignats a aquest. L’arquitectura i la metodologia proposades s’implementen utilitzant la topologia de NREN d’Europa occidental de l’Internet Topology Zoo. La topologia de la xarxa es divideix en clústers i es determina el nombre òptim de controladors de domini (DC) i la seva ubicació per a cada clúster. L’optimització de la ubicació de MC determina el nombre òptim de MC i la seva col·locació òptima. Com a segona contribució, es defineix una latència acumulada per resoldre el CPP, que té en compte tant la latència entre el controlador i els seus commutadors associats com la latència entre controladors. Sota la restricció de la latència, es formula un problema d’optimització segons la programació lineal de nombres enters mixts (MILP). L’objectiu de la investigació és reduir la latència acumulada alhora que es redueix el nombre de controladors de xarxa i optimitza la seva col·locació per aconseguir un equilibri òptim. El rendiment del mètode desenvolupat s’avalua en la topologia de xarxa real d’Internet2 OS3E. Per aconseguir el tercer objectiu, es va desenvolupar una mètrica que inclou la fiabilitat. També s’ha de tenir en compte la latència de comunicació entre controladors perquè un retard baix entre el commutador i el controlador no sempre implica un retard curt del controladorcontrolador per a una ubicació concreta dels controladors. Com a tercera contribució, proposem una nova mètrica per al CPP per millorar la fiabilitat dels controladors que tingui en compte tant la latència de la comunicació com la fiabilitat de la comunicació entre commutadors i controladors, així com entre controladors. La fiabilitat es té en compte quan falla un únic enllaç identificant la col·locació òptima dels controladors per aconseguir baixes latències en el trànsit del pla de control. L’objectiu d’aquest projecte és reduir la latència mitjana. Com a quarta contribució, aquest estudi avalua el model d’optimització Joint Latency and Reliability-aware Controller Placement (LRCP). Com a mètrica d’avaluació, la latència del pla de control (CPL) es defineix com la suma de la latència mitjana de commutador a controlador i la latència mitjana entre controladors. La latència del pla de control, utilitzant les latències reals de la topologia de xarxa real, es calcula per a cada col·locació òptima a la xarxa. En el cas d’una fallida en un únicenllaç, es calcula i s’avalua el CPL real de les ubicacions LRCP per determinar com de bones són les ubicacions LRCP. Les mètriques CPL s’utilitzen per comparar les mètriques de latència i fiabilitat amb altres models. Aquest estudi proporciona la prova que les metodologies desenvolupades per a xarxes a gran escala són molt potents pel que fa a la recerca de totes les ubicacions de controladors factibles mentre s’avaluen els resultats. A més, en comparació amb el treball anterior, inclou la latència entre els controladors i la fiabilitat per a un esdeveniment de fallada d’un enllaç únic.Las redes definidas por software (SDN) separan el plano de control del plano de datos. El enfoque inicial de SDN implica un único controlador centralizado, que puede no escalar adecuadamente a medida que una red crece en tamaño. Los controladores distribuidos han surgido para abordar las desventajas de un único controlador centralizado. Uno de los retos de investigación más importantes para las arquitecturas de controladores distribuidos es la gestión eficaz de los controladores, que incluye la asignación de suficientes controladores en las ubicaciones adecuadas. Para hacer frente a estos problemas, realizamos las siguientes contribuciones principales: Esta tesis amplía el método de resolución del Problema de Colocación de Controles (CPP) basado en los algoritmos K-means y K-center para incluir un Problema de Colocación de Controladores Jerárquicos (HCPP), situado en un nivel alto de Super-controladores (SC), un nivel medio de Controladores Maestros (MC), y el nivel más bajo de controladores de dominio (DC). La métrica de optimización es la latencia entre el controlador y los conmutadores asignados al mismo. . La arquitectura y la metodología propuestas se implementan utilizando la topología de las NREN de Europa Occidental del TopologyZoo. La topología completa de la red se divide en clústeres, y se determina el número óptimo de controladores de dominio (CD) y su colocación para cada clúster. La optimización de la colocación de los MC determina el número óptimo de MC y su colocación óptima. Como segunda contribución, se define una latencia acumulada para resolver el CPP, que tiene en cuenta tanto la latencia entre el controlador y sus conmutadores asociados como la latencia entre los controladores. Bajo la restricción de la latencia, se formula un problema de optimización según la programación lineal de enteros mixtos (MILP). El objetivo es reducir la latencia acumulada al tiempo que se reduce el número de controladores de la red y se optimiza su ubicación para lograr un equilibrio óptimo. El rendimiento del método desarrollado se evalúa en la topología de Internet2 OS3E. Para lograr el tercer objetivo, se desarrolló una métrica que incluye la fiabilidad. La latencia de la comunicación entre controladores también debe tenerse en cuenta, ya que un bajo retardo entre controladores y conmutadores no siempre implica un corto retardo entre controladores para una determinada ubicación de los mismos. Como tercera contribución proponemos una nueva métrica para el CPP para mejorar la fiabilidad de los controladores que tiene en cuenta tanto la latencia de la comunicación como la fiabilidad de la comunicación entre los conmutadores y los controladores, así como entre los controladores. Se tiene en cuenta la fiabilidad cuando falla un solo enlace. Este aspecto concluye con la identificación de la ubicación óptima de los controladores para lograr bajas latencias en el tráfico del plano de control. El objetivo es reducir la latencia media. Como cuarta contribución, este estudio evalúa el modelo de optimización Joint Latency and Reliability-aware Controller Placement (LRCP). Como métrica de evaluación, la latencia del plano de control (CPL) se define como la suma de la latencia media entre conmutadores y controladores y la latencia media entre controladores. La latencia del plano de control, utilizando las latencias reales de la topología de la red, se calcula para cada ubicación óptima en la red. En el caso de un fallo de un enlace, se calcula y evalúa la CPL real para las colocaciones de LRCP con el fin de determinar lo buenas que son las colocaciones de LRCP. Las métricas CPL se utilizan para comparar las métricas de latencia y fiabilidad con otros modelos. Este estudio demuestra que las metodologías desarrolladas para redes a gran escala son muy potentes en cuanto a la búsqueda de todas las ubicaciones factibles de los controladores mientras se evalúan los resultados. Además, en comparación con los trabajos anteriores, que incluyen la latencia entre controladores y la fiabilidad para un caso de fallo de un solo enlacePostprint (published version

Legacy Network Integration with SDN-IP Implementation towards a Multi-Domain SoDIP6 Network Environment

[EN] The logical separation of the data plane and the control plane of the network device conceptually defined by software-defined networking (SDN) creates many opportunities to create smart networking with better efficiency for network management and operation. SDN implementation over telecommunications (Telcos) and Internet service provider (ISP) networks is a challenging issue due to the lack of a high maturity level of SDN-based standards and several other critical factors that are considered during the real-time migration of existing legacy IPv4 networks. Different migration approaches have been studied; however, none of them seem to be close to realizing implementation. This paper implements the SDN-IP and Open Network Operating System (ONOS) SDN controller to migrate legacy IPv4 networks to multi-domain software-defined IPv6 (SoDIP6) networks and experimentally evaluate the viability of joint network migration in the ISP networks. We present results using extensive simulations for the suitable placement of the master ONOS controller during network migration by considering minimum control path latency using optimal path routing and the breadth first router replacement (BFR) technique. Our empirical analysis and evaluations show that the identification of the median router to attach the master controller and router migration planning using BFR give better results for carrier-grade legacy networks' migration to SoDIP6 networks.This research was partially funded by the Norwegian University of Science and Technology, Trondhiem, Norway (NTNU) under Sustainable Engineering Education Project (SEEP) financed by EnPE, University Grant Commission (grant-ID: FRG7475Engg01), Bhaktapur, Nepal, Nepal academy of Science and Technology (NAST), Kathmandu, Nepal, and U.S. National Science Foundation (NSF). The work of Danda B. Rawat was partly supported by the U.S. National Science Foundation (NSF) under grants CNS 1650831 and HRD 1828811. Any opinions, findings, and conclusions or recommendations expressed in this article are those of the authors and should not be interpreted as necessarily representing the official policies, either expressed or implied, of the NSF. We are thankful to the ERASMUS+ KA107 project and the GRC lab team members at Universitat Politècnica De València for the research support and facilitation.Dawadi, BR.; Rawat, DB.; Joshi, SR.; Manzoni, P. (2020). Legacy Network Integration with SDN-IP Implementation towards a Multi-Domain SoDIP6 Network Environment. Electronics. 9(9):1-22. https://doi.org/10.3390/electronics9091454S12299Dawadi, B. R., Rawat, D. B., & Joshi, S. R. (2019). Software Defined IPv6 Network: A New Paradigm for Future Networking. Journal of the Institute of Engineering, 15(2), 1-13. doi:10.3126/jie.v15i2.27636Dawadi, B. R., Rawat, D. B., Joshi, S. R., & Manzoni, P. (2020). Evolutionary gaming approach for decision making of Tier‐3 Internet service provider networks migration to SoDIP6 networks. International Journal of Communication Systems, 33(11). doi:10.1002/dac.4399Gu, D., Su, J., Xue, Y., Wang, D., Li, J., Luo, Z., & Yan, B. (2020). Modeling IPv6 adoption from biological evolution. Computer Communications, 158, 166-177. doi:10.1016/j.comcom.2020.02.081IPv6 Capability Measurement https://stats.labs.apnic.net/ipv6Dawadi, B. R., Rawat, D. B., Joshi, S. R., & Keitsch, M. M. (2018). Joint Cost Estimation Approach for Service Provider Legacy Network Migration to Unified Software Defined IPv6 Network. 2018 IEEE 4th International Conference on Collaboration and Internet Computing (CIC). doi:10.1109/cic.2018.00056Csikor, L., Szalay, M., Retvari, G., Pongracz, G., Pezaros, D. P., & Toka, L. (2020). Transition to SDN is HARMLESS: Hybrid Architecture for Migrating Legacy Ethernet Switches to SDN. IEEE/ACM Transactions on Networking, 28(1), 275-288. doi:10.1109/tnet.2019.2958762Sandhya, Sinha, Y., & Haribabu, K. (2017). A survey: Hybrid SDN. Journal of Network and Computer Applications, 100, 35-55. doi:10.1016/j.jnca.2017.10.003Mostafaei, H., Lospoto, G., Di Lallo, R., Rimondini, M., & Di Battista, G. (2020). A framework for multi‐provider virtual private networks in software‐defined federated networks. International Journal of Network Management, 30(6). doi:10.1002/nem.2116Dawadi, B. R., Rawat, D. B., & Joshi, S. R. (2019). Evolutionary Dynamics of Service Provider Legacy Network Migration to Software Defined IPv6 Network. Advances in Intelligent Systems and Computing, 245-257. doi:10.1007/978-3-030-19861-9_24Salsano, S., Ventre, P. L., Lombardo, F., Siracusano, G., Gerola, M., Salvadori, E., … Prete, L. (2016). Hybrid IP/SDN Networking: Open Implementation and Experiment Management Tools. IEEE Transactions on Network and Service Management, 13(1), 138-153. doi:10.1109/tnsm.2015.2507622Vissicchio, S., Tilmans, O., Vanbever, L., & Rexford, J. (2015). Central Control Over Distributed Routing. Proceedings of the 2015 ACM Conference on Special Interest Group on Data Communication. doi:10.1145/2785956.2787497Rizvi, S. N., Raumer, D., Wohlfart, F., & Carle, G. (2015). Towards carrier grade SDNs. Computer Networks, 92, 218-226. doi:10.1016/j.comnet.2015.09.029Risdianto, A. C., Tsai, P.-W., Ling, T. C., Yang, C.-S., & Kim, J. (2017). Enhanced Onos Sdn Controllers Deployment For Federated Multi-Domain Sdn-Cloud With Sd-Routing-Exchange. Malaysian Journal of Computer Science, 30(2), 134-153. doi:10.22452/mjcs.vol30no2.5Ventre, P. L., Salsano, S., Gerola, M., Salvadori, E., Usman, M., Buscaglione, S., … Snow, W. (2017). SDN-Based IP and Layer 2 Services with an Open Networking Operating System in the GÉANT Service Provider Network. IEEE Communications Magazine, 55(4), 71-79. doi:10.1109/mcom.2017.1600194SDN-IP Arhitecture https://wiki.onosproject.org/display/ONOS/SDN-IP+ArchitectureLee, H.-L., Liu, T.-L., & Chen, M. (2019). Deploying SDN-IP over Transnational Network Testbed. 2019 IEEE International Conference on Consumer Electronics - Taiwan (ICCE-TW). doi:10.1109/icce-tw46550.2019.8991776Das, T., Sridharan, V., & Gurusamy, M. (2020). A Survey on Controller Placement in SDN. IEEE Communications Surveys & Tutorials, 22(1), 472-503. doi:10.1109/comst.2019.2935453Chen, W., Chen, C., Jiang, X., & Liu, L. (2018). Multi-Controller Placement Towards SDN Based on Louvain Heuristic Algorithm. IEEE Access, 6, 49486-49497. doi:10.1109/access.2018.2867931Qi, Y., Wang, D., Yao, W., Li, H., & Cao, Y. (2019). Towards Multi-Controller Placement for SDN Based on Density Peaks Clustering. ICC 2019 - 2019 IEEE International Conference on Communications (ICC). doi:10.1109/icc.2019.8761814Lu, J., Zhang, Z., Hu, T., Yi, P., & Lan, J. (2019). A Survey of Controller Placement Problem in Software-Defined Networking. IEEE Access, 7, 24290-24307. doi:10.1109/access.2019.2893283Singh, A. K., Maurya, S., Kumar, N., & Srivastava, S. (2019). Heuristic approaches for the reliable SDN controller placement problem. Transactions on Emerging Telecommunications Technologies, 31(2). doi:10.1002/ett.3761Das, T., & Gurusamy, M. (2018). Resilient Controller Placement in Hybrid SDN&#x002F;Legacy Networks. 2018 IEEE Global Communications Conference (GLOBECOM). doi:10.1109/glocom.2018.8647566Heller, B., Sherwood, R., & McKeown, N. (2012). The controller placement problem. ACM SIGCOMM Computer Communication Review, 42(4), 473-478. doi:10.1145/2377677.2377767SDN Control Plane Performance: Raising the Bar on SDN Performance, Scalability, and High Availability https://wiki.onosproject.org/download/attachments/13994369/Whitepaper-%20ONOS%20Kingfisher%20release%20performance.pdf?version=