491 research outputs found
Heuristic resource allocation algorithm for controller placement in multi-control 5G based on SDN/NFV architecture
The integration of Software Defined Networking (SDN) and Network Function Virtualization (NFV) is considered to be an efficient solution that enables the forecasting of highly scalable, optimal performance of 5G networks by providing an effective means of network functionality. The distributed multi-controller architecture approach is an emerging strategy that primarily aims to support network functions performed through the application of a control plane, to provide versatile network traffic management. However, the management of resource allocations across multiple data centers is an important issue that still affects 5G core networks. Using such a strategy in 5G core networks requires the controllers to be correctly located, in order to improve network reliability and cost-effectiveness. Thus, to address the controller placement problem (CPP) in a distributed 5G network, we proposed an efficient, heuristic multi-objective optimization approach, using dynamic capacitated controller placement problem (DCCPP). It is based on the K-center problem, to solve the capacitated controller placement problem (CCPP), which acts as a resource location problem, in which the location and number of controllers can be allocated to maximize resources. A Greedy Randomized Search (GRS) algorithm was used to solve the dynamic assignment of nodes to controllers to achieve load balancing. The design of the heuristic method provides proper load balancing, efficient cost management, and network resource management, as compared to the basic CCPP model. The results indicate that the allocation and the optimum number of controllers under an effective decentralized policy could achieve a higher degree of efficiency through resource assignment in such a densified network
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
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
Controller placement mechanism in software defined network using k-median algorithm
Software Defined Network (SDN) decouples the control plane and the data plane, and moves the control plane to an external entity. The decoupling raises many challenges, and one of these is the placement of the controller in the network. This study aims to address controller placement problem in SDN. k-median is used to determine the placement of the controllers, and the placement with the lowest value of average propagation latency will be chosen. The placement compares two resulted placements. First, comparing to greedy algorithm that computes the combinations according to the order of the nodes and calculates the best values at each step, and the results were identical. The second comparison was with the combinations results from considering the placement from specific nodes, and the results showed that it gives higher results than depending on the lowest values resulted from the k-median. Finally, three controllers are chosen as the minimum number of controllers, they were evaluated in terms of delay and load, and as results it was found that three controllers are suitable number of controllers as long as there is no delay or load in the network. Combining the two algorithms for finding the placement and the number results in Controller Placement Mechanism (CPM
An Effective Approach to Controller Placement in Software Defined Wide Area Networks
This is the author accepted manuscript.
The final version is available from Institute of Electrical and Electronics Engineers via the DOI in this record.One grand challenge in Software Defined
Networking (SDN) is to select appropriate locations for
controllers to shorten the latency between controllers and
switches in wide area networks. In the literature, the
majority of approaches are focused on the reduction of
packet propagation latency, but propagation latency is
only one of the contributors of the overall latency between
controllers and their associated switches. In this paper, we
explore and investigate more possible contributors of the
latency, including the end-to-end latency and the queuing
latency of controllers. In order to decrease the end-to-end
latency, the concept of network partition is introduced and
a Clustering-based Network Partition Algorithm (CNPA)
is then proposed to partition the network. The CNPA can
guarantee that each partition is able to shorten the maximum
end-to-end latency between controllers and switches.
To further decrease the queuing latency of controllers,
appropriate multiple controllers are then placed in the
subnetworks. Extensive simulations are conducted under
two real network topologies from the Internet Topology
Zoo. The results verify that the proposed algorithm can
remarkably reduce the maximum latency between controllers
and their associated switches
The Role of Inter-Controller Traffic for Placement of Distributed SDN Controllers
We consider a distributed Software Defined Networking (SDN) architecture
adopting a cluster of multiple controllers to improve network performance and
reliability. Besides the Openflow control traffic exchanged between controllers
and switches, we focus on the control traffic exchanged among the controllers
in the cluster, needed to run coordination and consensus algorithms to keep the
controllers synchronized. We estimate the effect of the inter-controller
communications on the reaction time perceived by the switches depending on the
data-ownership model adopted in the cluster. The model is accurately validated
in an operational Software Defined WAN (SDWAN). We advocate a careful placement
of the controllers, that should take into account both the above kinds of
control traffic. We evaluate, for some real ISP network topologies, the delay
tradeoffs for the controllers placement problem and we propose a novel
evolutionary algorithm to find the corresponding Pareto frontier. Our work
provides novel quantitative tools to optimize the planning and the design of
the network supporting the control plane of SDN networks, especially when the
network is very large and in-band control plane is adopted. We also show that
for operational distributed controllers (e.g. OpenDaylight and ONOS), the
location of the controller which acts as a leader in the consensus algorithm
has a strong impact on the reactivity perceived by switches.Comment: 14 page
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