Multi-controller Software-defined Networking Research Articles

Federated Learning-Based Security Attack Detection for Multi-Controller Software-Defined Networks

A revolutionary concept of Multi-controller Software-Defined Networking (MC-SDN) is a promising structure for pursuing an evolving complex and expansive large-scale modern network environment. Despite the rich operational flexibility of MC-SDN, it is imperative to protect the network deployment against potential vulnerabilities that lead to misuse and malicious activities on data planes. The security holes in the MC-SDN significantly impact network survivability, and subsequently, the data plane is vulnerable to potential security threats and unintended consequences. Accordingly, this work intends to design a Federated learning-based Security (FedSec) strategy that detects the MC-SDN attack. The FedSec ensures packet routing services among the nodes by maintaining a flow table frequently updated according to the global model knowledge. By executing the FedSec algorithm only on the network-centric nodes selected based on importance measurements, the FedSec reduces the system complexity and enhances attack detection and classification accuracy. Finally, the experimental results illustrate the significance of the proposed FedSec strategy regarding various metrics.

Countermeasure SDN-based IoT threats using blockchain multicontroller

The Internet of Things (IoT) is making significant progress in various fields; software-defined networks with multiple controllers have become popular because they make it easier to manage large networks. But they are open to several attacks, which makes controller topologies inconsistent. To solve this problem, we suggest a multi-controller blockchain for software-defined networking (SDN) network. This security architecture combines blockchain and multi-controller SDN and divides the network into several domains. We put forth a blockchain-based solution. This paper proposed a model blockchain-enabled SDN multi-controller architecture for IoT networks that uses a clustering algorithm and a new routing protocol that is both secure and energy-efficient. Experimental results indicate that the cluster-based routing protocol has a greater capacity, a shorter response time, and a lower overall power requirement than other protocols. It has been shown that our proposed architecture outperforms the classic blockchain.

Multi-Controllers Placement Optimization in SDN by the Hybrid HSA-PSO Algorithm

Software-Defined Networking (SDN) is a developing architecture that provides scalability, flexibility, and efficient network management. However, optimal controller placement faces many problems, which affect the performance of the overall network. To resolve the Multi-controller SDN (MC-SDN) that is deployed in the SDN environment, we propose an approach that uses a hybrid metaheuristic algorithm that improves network performance. Initially, the proposed SDN network is constructed based on graph theory, which improves the connectivity and flexibility between switches and controllers. After that, the controller selection is performed by selecting an optimal controller from multiple controllers based on controller features using the firefly optimization algorithm (FA), which improves the network performance. Finally, multi-controller placement is performed to reduce the communication latency between the switch to controllers. Here, multiple controllers are placed by considering location and distance using a hybrid metaheuristic algorithm, which includes a harmonic search algorithm and particle swarm optimization algorithm (HSA-PSO), in which the PSO algorithm is proposed to automatically update the harmonic search parameters. The simulation of multi-controller placement is carried out by the CloudsimSDN network simulator, and the simulation results demonstrate the proposed advantages in terms of propagation latency, Round Trip Time (RTT), matrix of Time Session (TS), delay, reliability, and throughput.

A protocol for cluster confirmations of SDN controllers against DDoS attacks

Software-Defined Networking (SDN) makes it easier to manage the network by separating the Data plane and Control plane, but these networks are susceptible to DDoS attacks. Most well-known algorithms for reducing the effects of DDoS attacks are based on SDN traffic analysis and prediction. Their main problems are false positive/negative results. Therefore, we propose PATGEN, a Protocol to reduce the effects of DDoS ATtacks using an advanced GENetic algorithm with optimized and new operators, thereby significantly reducing the effects of attacks and increasing the efficiency of the multi-controller SDN. Using the robust initial population procedure increases the convergence speed of the algorithm. Unlike other methods, PATGEN is possible without using external resources. Experimental results show that PATGEN increases the throughput and reduces the average delay compared to states of the art methods.

Improving the fault-tolerance of software-defined networks with dynamic overlay agreement

Software-Defined Networking (SDN) emerges as one of the leading technologies to address the pressing networking problems such as network virtualization and data center complexity issues using programmable switches and controllers. To well exchange information and have coordinated control for the SDN environment, the multi-controller SDN network has been proposed. Unfortunately, this network architecture still faces the problem of faulty controllers that may forge the command arbitrarily, and then the whole network will be broken down easily. Thus, it is important to propose the fault-tolerance scheme under the SDN network system. In this paper, a new SDN environment called the Multi-Controller Overlay Groups (MCOG) where each device is managed by the controllers is proposed. Besides, the degree of the faulty influence will be revised to define the different bounds of fault tolerance in the MCOG environment. Furthermore, the new protocol named General Dynamic Multi-Controller Agreement (GDMCA) protocol is proposed to solve the Byzantine Agreement (BA) problem in the MCOG environment. Based on the proof of complexity, it can show that the proposed GDMCA protocol is optimal under the MCOG environment.

Software defined networks: Current problems and future solutions

Software Defined Networking (SDN) is state-of-the-art network architecture conceptual framework that is based on the decoupling of physical plane and control plane which manage the networks by means of software. The most vital component of this SDN enable network is controller which is also considered to be the brain of SDN. These network architectures with separated control planes, generates many queries regarding network reliability, scalability, and network performance with contrast to more traditional distributed systems. This paper focuses on one of the primary drawback that is placement of controllers in multi-controller SDN architecture in Future Applications. There are several techniques to solve this problem on different parameters like reliability, latency, availability which we are going to explore in this paper. We will consider mainly two accepts in our research to solve the problem of placing the Controller in future applications first one is reliability of the Network and the second one is propagation delay between the controllers and switches.

Fractional switch migration in multi-controller software-defined networking

Mapping switches to controllers in multi-controller software-defined networking (SDN) is still a hot research topic. Many factors have to be considered when establishing this mapping. Among them are the load balancing and mapping stability. Load balancing is important to improve resources utilization, and mapping stability reduces the control plane overhead created when exchanging information triggered by new mappings. This article presents a model for dynamic switch-controller mapping to achieve load balancing and minimize the number of new switch-controller assignments. To that end, for load balancing, flows from a switch are allowed to be handled by multiple controllers, and to increase assignment stability, the assignments at time t−1 are taken into consideration when calculating the assignments at time t. The model is formulated as a convex quadratic programming problem, and the properties and feasibility of this model are mathematically analyzed. In addition, a heuristic algorithm is developed to deal with large-scale networks. The experimental results show the effectiveness of the proposed approach when compared to recent academic work, where the proposed model leads to a slight improvement in the load balancing and increases the stability of the switch-controller assignment by ≈ 91%.

On Load Balancing via Switch Migration in Software-Defined Networking

Switch-controller assignment is an essential task in multi-controller software-defined networking. Static assignments are not practical because network dynamics are complex and difficult to predetermine. Since network load varies both in space and time, the mapping of switches to controllers should be adaptive to sudden changes in the network. To that end, switch migration plays an important role in maintaining dynamic switch-controller mapping. Migrating switches from overloaded to underloaded controllers brings flexibility and adaptability to the network but, at the same time, deciding which switches should be migrated to which controllers, while maintaining a balanced load in the network, is a challenging task. This work presents a heuristic approach with solution shaking to solve the switch migration problem. Shift and swap moves are incorporated within a search scheme. Every move is evaluated by how much benefit it will give to both the immigration and outmigration controllers. The experimental results show that the proposed approach is able to outweigh the state-of-art approaches, and improve the load balancing results up to ≈ 14% in some scenarios when compared to the most recent approach. In addition, the results show that the proposed work is more robust to controller failure than the state-of-art methods.

$\text{E}^{3}$ MC: Improving Energy Efficiency via Elastic Multi-Controller SDN in Data Center Networks

Energy consumed by network constitutes a significant portion of the total power budget in modern data centers. Thus, it is critical to understand the energy consumption and improve the power efficiency of data center networks (DCNs). In doing so, one straightforward and effective way is to make the size of DCNs elastic along with traffic demands, i.e., turning off unnecessary network components to reduce the energy consumption. Today, software defined networking (SDN), as one of the most promising solutions for data center management, provides a paradigm to elastically control the resources of DCNs. However, to the best of our knowledge, the features of SDN have not been fully leveraged to improve the power saving, especially for large-scale multi-controller DCNs. To address this problem, we propose $\text{E}^{3}$ MC, a mechanism to improve DCN’s energy efficiency via the elastic multi-controller SDN. In $\text{E}^{3}$ MC, the energy optimizations for both forwarding and control plane are considered by utilizing SDN’s fine-grained routing and dynamic control mapping. In particular, the flow network theory and the bin-packing heuristic are used to deal with the forwarding plane and control plane, respectively. Our simulation results show that $\text{E}^{3}$ MC can achieve more efficient power management, especially in highly structured topologies such as Fat-Tree and BCube, by saving up to 50% of network energy, at an acceptable level of computation cost.

Improving the performance of load balancing in software-defined networks through load variance-based synchronization

Software-Defined Networking (SDN) is a new network technology that decouples the control plane logic from the data plane and uses a programmable software controller to manage network operation and the state of network components. In an SDN network, a logically centralized controller uses a global network view to conduct management and operation of the network. The centralized control of the SDN network presents a tremendous opportunity for network operators to refactor the control plane and to improve the performance of applications. For the application of load balancing, the logically centralized controller conducts Real-time Least loaded Server selection (RLS) for multiple domains, where new flows pass by for the first time. The function of RLS is to enable the new flows to be forwarded to the least loaded server in the entire network. However, in a large-scale SDN network, the logically centralized controller usually consists of multiple distributed controllers. Existing multiple controller state synchronization schemes are based on Periodic Synchronization (PS), which can cause undesirable situations. For example, frequent synchronizations may result in high synchronization overhead of controllers. State desynchronization among controllers during the interval between two consecutive synchronizations could lead to forwarding loops and black holes. In this paper, we propose a new type of controller state synchronization scheme, Load Variance-based Synchronization (LVS), to improve the load-balancing performance in the multi-controller multi-domain SDN network. Compared with PS-based schemes, LVS-based schemes conduct effective state synchronizations among controllers only when the load of a specific server or domain exceeds a certain threshold, which significantly reduces the synchronization overhead of controllers. The results of simulations show that LVS achieves loop-free forwarding and good load-balancing performance with much less synchronization overhead, as compared with existing schemes.