Software Defined Networks based Smart Grid Communication: A Comprehensive Survey

The current power grid is no longer a feasible solution due to ever-increasing user demand of electricity, old infrastructure, and reliability issues and thus require transformation to a better grid a.k.a., smart grid (SG). The key features that distinguish SG from the conventional electrical power grid are its capability to perform two-way communication, demand side management, and real time pricing. Despite all these advantages that SG will bring, there are certain issues which are specific to SG communication system. For instance, network management of current SG systems is complex, time consuming, and done manually. Moreover, SG communication (SGC) system is built on different vendor specific devices and protocols. Therefore, the current SG systems are not protocol independent, thus leading to interoperability issue. Software defined network (SDN) has been proposed to monitor and manage the communication networks globally. This article serves as a comprehensive survey on SDN-based SGC. In this article, we first discuss taxonomy of advantages of SDNbased SGC.We then discuss SDN-based SGC architectures, along with case studies. Our article provides an in-depth discussion on routing schemes for SDN-based SGC. We also provide detailed survey of security and privacy schemes applied to SDN-based SGC. We furthermore present challenges, open issues, and future research directions related to SDN-based SGC.Comment: Accepte

Multi-controller Based Software-Defined Networking: A Survey

Software-Defined Networking (SDN) is a novel network paradigm that enables flexible management for networks. As the network size increases, the single centralized controller cannot meet the increasing demand for flow processing. Thus, the promising solution for SDN with large-scale networks is the multi-controller. In this paper, we present a compressive survey for multi-controller research in SDN. First, we introduce the overview of multi-controller, including the origin of multi-controller and its challenges. Then, we classify multi-controller research into four aspects (scalability, consistency, reliability, load balancing) depending on the process of implementing the multi-controller. Finally, we propose some relevant research issues to deal with in the future and conclude the multi-controller research

Using metaheuristics to improve the placement of multi-controllers in software-defined networking enabled clouds

SDN is a model that separates the control and the data levels in an arrangement to enhance capability to program and configure the network in a more agile and efficient manner. Multiple controller modules have been used in the SDN engineering to empower programmable and adaptable configurations such as improving scalability and reliability. The distance and time calculations and other performance measures have to be considered in solving the Multi-Controller Position Problem (MCPP). This paper investigates the use of metaheuristic algorithms to build an MCPP mathematical model. Both the symmetric Harmony Search (HS) modelling and the Particle Swarm Optimization (PSO) algorithm are considered in this respect. Thus, our hybrid approach is proposed and known as Harmony Search with Particle Swarm Optimization (HSPSO) is applied and we compared the extracted results with the state-of-the-art techniques in the previous literature. Besides the development of the mathematical model, a simulation study has been done considering the relevant parameters including the link distance description and the access time between the SDN entities. The console simulation uses NetBeans with CloudsimSDN procedure files in the SDN-based cloud environment

Secure Multi-Path Selection with Optimal Controller Placement Using Hybrid Software-Defined Networks with Optimization Algorithm

The Internet's growth in popularity requires computer networks for both agility and resilience. Recently, unable to satisfy the computer needs for traditional networking systems. Software Defined Networking (SDN) is known as a paradigm shift in the networking industry. Many organizations are used SDN due to their efficiency of transmission. Striking the right balance between SDN and legacy switching capabilities will enable successful network scenarios in architecture networks. Therefore, this object grand scenario for a hybrid network where the external perimeter transport device is replaced with an SDN device in the service provider network. With the moving away from older networks to SDN, hybrid SDN includes both legacy and SDN switches. Existing models of SDN have limitations such as overfitting, local optimal trapping, and poor path selection efficiency. This paper proposed a Deep Kronecker Neural Network (DKNN) to improve its efficiency with a moderate optimization method for multipath selection in SDN. Dynamic resource scheduling is used for the reward function the learning performance is improved by the deep reinforcement learning (DRL) technique. The controller for centralised SDN acts as a network brain in the control plane. Among the most important duties network is selected for the best SDN controller. It is vulnerable to invasions and the controller becomes a network bottleneck. This study presents an intrusion detection system (IDS) based on the SDN model that runs as an application module within the controller. Therefore, this study suggested the feature extraction and classification of contractive auto-encoder with a triple attention-based classifier. Additionally, this study leveraged the best performing SDN controllers on which many other SDN controllers are based on OpenDayLight (ODL) provides an open northbound API and supports multiple southbound protocols. Therefore, one of the main issues in the multi-controller placement problem (CPP) that addresses needed in the setting of SDN specifically when different aspects in interruption, ability, authenticity and load distribution are being considered. Introducing the scenario concept, CPP is formulated as a robust optimization problem that considers changes in network status due to power outages, controller’s capacity, load fluctuations and changes in switches demand. Therefore, to improve network performance, it is planned to improve the optimal amount of controller placements by simulated annealing using different topologies the modified Dragonfly optimization algorithm (MDOA)

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