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Journal articles on the topic 'Controller SDN'

Author: Grafiati
Published: 4 June 2021
Last updated: 1 February 2022

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1

Sufiev, Hadar, Yoram Haddad, Leonid Barenboim, and José Soler. "Dynamic SDN Controller Load Balancing." Future Internet 11, no. 3 (March 21, 2019): 75. http://dx.doi.org/10.3390/fi11030075.

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The software defined networking (SDN) paradigm separates the control plane from the data plane, where an SDN controller receives requests from its connected switches and manages the operation of the switches under its control. Reassignments between switches and their controllers are performed dynamically, in order to balance the load over SDN controllers. In order to perform load balancing, most dynamic assignment solutions use a central element to gather information requests for reassignment of switches. Increasing the number of controllers causes a scalability problem, when one super controller is used for all controllers and gathers information from all switches. In a large network, the distances between the controllers is sometimes a constraint for assigning them switches. In this paper, a new approach is presented to solve the well-known load balancing problem in the SDN control plane. This approach implies less load on the central element and meeting the maximum distance constraint allowed between controllers. An architecture with two levels of load balancing is defined. At the top level, the main component called Super Controller, arranges the controllers in clusters, so that there is a balance between the loads of the clusters. At the bottom level, in each cluster there is a dedicated controller called Master Controller, which performs a reassignment of the switches in order to balance the loads between the controllers. We provide a two-phase algorithm, called Dynamic Controllers Clustering algorithm, for the top level of load balancing operation. The load balancing operation takes place at regular intervals. The length of the cycle in which the operation is performed can be shorter, since the top-level operation can run independently of the bottom level operation. Shortening cycle time allows for more accurate results of load balancing. Theoretical analysis demonstrates that our algorithm provides a near-optimal solution. Simulation results show that our dynamic clustering improves fixed clustering by a multiplicative factor of 5.
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2

Haque, Muhammad Reazul, Saw Chin Tan, Zulfadzli Yusoff, Kashif Nisar, Ching Kwang Lee, Rizaludin Kaspin, BS Chowdhry, Sameer Ali, and Shuaib Memon. "A Novel DDoS Attack-aware Smart Backup Controller Placement in SDN Design." Annals of Emerging Technologies in Computing 4, no. 5 (December 20, 2020): 75–92. http://dx.doi.org/10.33166/aetic.2020.05.005.

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Security issues like Distributed Denial of Service (DDoS) attacks are becoming the main threat for Software-Defined Networking (SDN). Controller placement is a fundamental factor in the design and planning of SDN infrastructure. The controller could be seen as a single dot of failure for the whole SDN and it's the alluring point for DDoS attack. Single controller placement implies a single point of SDN control. So, there is a very high chance to fail the entire network topology as the controller associated with all switches. As a result, legitimate clients won't have the capacity to use SDN services. This is the reason why the controller is the suitable center dot of attack for the aggressor. To protect SDN from this type of single purpose of failure, it is essential to place multiple smart backup controllers to guarantee the SDN operation. In this paper, we propose a novel Integer Linear Programming (ILP) model to optimize the security issue by placing powerful smart backup controller. Result obtained from the simulation shows that our proposed novel ILP model can suggest single or multiple smart backup controller placement to support several ordinary victim controllers which has the capacity to save the cost of multiple ordinary controllers by sharing link, maximum new flows per second of controller and port, etc.
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Rowshanrad, Shiva, Vajihe Abdi, and Manijeh Keshtgari. "PERFORMANCE EVALUATION OF SDN CONTROLLERS: FLOODLIGHT AND OPENDAYLIGHT." IIUM Engineering Journal 17, no. 2 (November 30, 2016): 47–57. http://dx.doi.org/10.31436/iiumej.v17i2.615.

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Software Defined Network is new network architecture. One of its components is the controller, which is the intelligent part of SDN. Many controllers such as Floodlight, Open Daylight, Maestro, NOX, POX and many others are released. The question is which controller can perform better in which situations. Many works were done to compare controllers regarding architecture, efficiency and controllers’ features. In this paper, two of the most popular controllers, Floodlight and OpenDaylight are compared in terms of Network QoS parameters such as delay and loss in different topologies and network loads. This paper can help researchers to choose the best controller in different use cases such as clouds and multimedia. The results with 95% confidence interval show that OpenDaylight outperforms Floodlight in low loaded networks and also for tree topology in mid loaded networks in terms of latency. Floodlight can outperform OpenDaylight in heavy loaded networks for tree topology in terms of packet loss and in linear topology in terms of latency. There is no significant difference in performance of Floodlight and OpenDaylight controllers in other cases.
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Amiri, Esmaeil, Emad Alizadeh, and Mohammad Hossein Rezvani. "Controller selection in software defined networks using best-worst multi-criteria decision-making." Bulletin of Electrical Engineering and Informatics 9, no. 4 (August 1, 2020): 1506–17. http://dx.doi.org/10.11591/eei.v9i4.2393.

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Controllers are the key component of Software-defined Network (SDN) architecture. Given the diversity of open SDN controllers, the following question arises for the network administrators: How can we choose the appropriate SDN controller? Different characteristics of the controllers have greatly increased the complexity of the right decision. Multi-Criteria Decision-making Methods (MCDMs) is a family of robust mathematical tools to address complex problems regarding multiple objectives. In this paper, we study the most important features of SDN controllers. To this end, we compare the well-known SDN controllers including NOX, POX, Beacon, Floodlight, Ryu, ODL, and ONOS. Leveraging a novel MCDM technique called the Best–Worst Multi-criteria (BWM), we find the most appropriate SDN controller. We solve an optimization problem and evaluate its performance in terms of significant criteria such as throughput and latency. Initial evaluation revealed that the ONOS and ODL have the highest throughput, while the lowest throughputs belong to the NOX, POX, and Ryu. However, final evaluation concerning all criteria confirmed the robustness of the ONOS and the ODL compared to other controllers.
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5

AlShehri, Mohammed Abdul Rahman, and Shailendra Mishra. "Feature Based Comparison and Selection of SDN Controller." International Journal of Innovation and Technology Management 16, no. 05 (August 2019): 1950029. http://dx.doi.org/10.1142/s0219877019500299.

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Software defined network (SDN) controller selection in SDN is a key challenge to the network administrator. In SDN, control plane is an isolated process and operate on control layer. The controller provides a universal view of the entire network and support applications and services. The three focused parameters for controller selection are productivity, campus network and open source. In SDN, it is vital to have a good device for the efficient processing of all requests made by the switch and for good behavior of the network. For selecting best controller for the specified parameters, decision logic has to be developed that allow us to do comparison of the available controllers. Therefore, in this research we have suggested a methodology that uses analytic-hierarchy-process (AHP) to find a best controller. The approach has been studied and verified for a big organization network setup of Al-Majmaah University, Saudi Arabia. The approach is found to be more effective and increase the network performance significantly.
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6

Rajalakshmi, S., N. Deepika, Srivardhini C.S., Vignesh A.C., and Vignesh D.V. "SDN Controller for LTE Networks." International Journal of Computer Applications 133, no. 3 (January 15, 2016): 31–36. http://dx.doi.org/10.5120/ijca2016907782.

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7

SKULYSH, Mariia, and Larysa GLOBA. "Calculation Functions of SDN Controller for Wireless Backhaul Infrastructure." Acta Electrotechnica et Informatica 17, no. 4 (December 1, 2017): 14–18. http://dx.doi.org/10.15546/aeei-2017-0029.

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8

Salman et al., Mustafa I. "Software Defined Network of Video Surveillance System Based on Enhanced Routing Algorithms." Baghdad Science Journal 17, no. 1(Suppl.) (March 18, 2020): 0391. http://dx.doi.org/10.21123/bsj.2020.17.1(suppl.).0391.

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Software Defined Network (SDN) is a new technology that separate the ‎control plane from the data plane. SDN provides a choice in automation and ‎programmability faster than traditional network. It supports the ‎Quality of Service (QoS) for video surveillance application. One of most ‎significant issues in video surveillance is how to find the best path for routing the packets ‎between the source (IP cameras) and destination (monitoring center). The ‎video surveillance system requires fast transmission and reliable delivery ‎and high QoS. To improve the QoS and to achieve the optimal path, the ‎SDN architecture is used in this paper. In addition, different routing algorithms are ‎used with different steps. First, we evaluate the video transmission over the SDN with ‎Bellman Ford algorithm. Then, because the limitation of Bellman ford ‎algorithm, the Dijkstra algorithm is used to change the path when a congestion occurs. Furthermore, the Dijkstra algorithm is used with two ‎controllers to reduce the time consumed by the SDN controller. ‎ POX and Pyretic SDN controllers are used such that POX controller is ‎responsible for the network monitoring, while Pyretic controller is responsible for the ‎routing algorithm and path selection. Finally, a modified Dijkstra algorithm is further proposed and evaluated with two ‎controllers to enhance the performance. The results show that the modified Dijkstra algorithm outperformed the other approaches in the aspect of QoS parameters.
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NUGROHO, KUKUH, and DHIMAS PRABOWO SETYANUGROHO. "Analisis Kinerja RouteFlow pada Jaringan SDN (Software Defined Network ) menggunakan Topologi Full-Mesh." ELKOMIKA: Jurnal Teknik Energi Elektrik, Teknik Telekomunikasi, & Teknik Elektronika 7, no. 3 (September 30, 2019): 585. http://dx.doi.org/10.26760/elkomika.v7i3.585.

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ABSTRAKPerangkat controller dalam jaringan SDN berfungsi untuk memberikan informasi tabel flow ke perangkat switch sebagai acuan dalam menentukan informasi rute. Kecepatan dalam memproses permintaan tabel flow yang dilakukan oleh perangkat switch tergantung dari pemilihan jenis controller yang digunakan. Terdapat beberapa jenis controller yang bisa digunakan untuk mengatur aliran trafik data dalam jaringan SDN. Pada penelitian ini akan digunakan jenis controller RouteFlow dengan menggunakan algoritma routing Djikstra. Jaringan uji menggunakan topologi Full-Mesh yang menyediakan koneksi penuh ke semua switch, dimana terdapat dua protokol layer transport yang digunakan untuk mengirimkan data dalam jaringan SDN yaitu TCP dan UDP. Hasil pengukuran kualitas jaringan menunjukkan bahwa penggunaan protokol UDP menghasilkan nilai delay, jitter, dan throughput yang lebih baik dibandingkan dengan TCP. Waktu konvergensi jaringan yang dihasilkan sebesar 12,18 ms ketika ukuran data yang dipertukarkan sebesar 64 Byte.Kata kunci: Controller, Full-Mesh, RouteFlow, Software Defined Network ABSTRACTThe controller device in the SDN network is applied to provide flow table information for all switches as a reference in determining route information. The speed in processing the flow table requests that are made by the switches depends on the choice of the type of controller used. There are several types of controllers that can be used to manage the data traffic flow in the SDN network. This research utilizes the RouteFlow controller and the Djikstra routing algorithm. The test network applies the Full-Mesh topology that provides fully connections to all switches, wherein two transport protocols are used to transmit data in SDN networks, i.e., TCP and UDP. The results of network performance measurements show that the use of the UDP obtains better values in delay, jitter, and throughput than TCP. The network convergence time is 12.18 ms when the size of data exchanged is set to 64 Bytes.Keywords: Controller, Full-Mesh, RouteFlow, Software Defined Network
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10

Park, Joonseok, Jeseung Hwang, and Keunhyuk Yeom. "NSAF: An Approach for Ensuring Application-Aware Routing Based on Network QoS of Applications in SDN." Mobile Information Systems 2019 (April 23, 2019): 1–16. http://dx.doi.org/10.1155/2019/3971598.

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The advent of software-defined networking (SDN) has led to the paradigm of programmable network environments. Conceptually, the structure of SDN is divided into three layers: application, control, and infrastructure. The SDN controller in the control layer can configure and execute the routing of applications to the infrastructure layer consisting of network devices, including hosts and switches. Current studies on SDN have predominantly focused on control layer aspects, such as controller development, performance aspects of the controller, and interaction among different controllers and between controllers and network devices. However, to provide seamless network services and efficiently manage network environments, application-aware routing is essential because applications may have different quality of service (QoS) requirements, such as maximum bandwidth and minimum delay. This study proposes the Network Situation-Aware Framework (NSAF) to more efficiently handle application routing based on the QoS requirements and changing network status. A mechanism for supporting the NSAF consisting of application registration, network status monitoring, violation detection, and routing control is also presented. The applicability and feasibility of the proposed NSAF are verified by implementing a prototype. The NSAF may be used as a reference model for efficiently managing SDN-based networks to ensure application QoS.
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11

Muluye, Worku. "A Review on Software-Defined Networking Distributed Controllers." International Journal of Engineering and Computer Science 9, no. 2 (February 15, 2020): 24953–61. http://dx.doi.org/10.18535/ijecs/v9i2.4439.

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A computer network is a critical issue in our day to day activity; however, today it works under various problems. Since in the current network architecture the control plane and data plane are vertically bundled on the same device. To solve this problem programmable Software-Defined Network is released. OpenFlow is a protocol that vertically separates control plane and data plane of the network devices. In SDN the controllers are the brains of the network that controls the network devices. Today’s network required successful integration of distributed controllers to make the network more consistent. SDN distributed controller is a controller that we can add or remove the controllers according to the number of devices change. Distributed controller architecture has investigated and compared the 6 recent distributed controllers by using 26 criteria. Orion is the first best controller and ONOS is the second best controller.
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12

Gaur, Puru, Amish Tandon, Nupur Goyal, Gitanjali Chandwani, and Mangey Ram. "An Analysis of Hierarchical Software-Defined Network Control Plane: A Reliability Approach." International Journal of Reliability, Quality and Safety Engineering 27, no. 03 (October 2, 2019): 2050010. http://dx.doi.org/10.1142/s0218539320500102.

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Present-day computer systems have drastically transformed from the ones in days of basic file sharing, peripheral sharing or the hosting of companywide applications on a server to much more sophisticated, small and faster systems. These systems have further expanded to include cloud-based networks, virtualized desktops, servers, etc. The capabilities of evolving heterogeneous computer systems require advanced control plane. Software-defined networking (SDN) proposes to control the network from a centralized controller instead of a distributed configuration. SDN makes it easier for network operators to evolve network capabilities. Even though SDN proposes a logically centralized system, the controllers may not represent a single, centralized device, instead the control plane may consist of logically centralized but physically distributed controllers wherein each controller manages different administrative domains of the network or different parts of the flow space. There are mainly two types of control plane architecture: flat control plane and hierarchical control plane. In this paper, we have analyzed the reliability and availability of the hierarchical SDN control plane. We take into consideration work-load capacities of the controllers, link failures, node failures and controller-end failures to determine the reliability of the system.
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13

Aly, Wael Hosny Fouad. "Generic Controller Adaptive Load Balancing (GCALB) for SDN Networks." Journal of Computer Networks and Communications 2019 (December 1, 2019): 1–9. http://dx.doi.org/10.1155/2019/6808693.

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Fault tolerance is an important aspect of network resilience. Fault-tolerance mechanisms are required to ensure high availability and high reliability in different environments. The beginning of software-defined networking (SDN) has both presented new challenges and opened a new era to develop new strategies, standards, and architectures to support fault tolerance. In this paper, a study of fault tolerance is performed for two architectures: (1) a single master with multiple slave controllers and (2) multiple slave controllers. The proposed model is called a Generic Controller Adaptive Load Balancing (GCALB) model for SDNs. GCALB adapts the load among slave controllers based on a GCALB algorithm. Mininet simulation tool is utilized for the experimentation phase. Controllers are implemented using floodlights. Experiment results were conducted using GCALB when master controller is taking the responsibility of distributing switches among four and five slave controllers as a case study. Throughput and response time metrics are used to measure performance. GCALB is compared with two reference algorithms: (1) HyperFlow (Kreutz et al., 2012), and (2) Enhanced Controller Fault Tolerant (ECFT) (Aly and Al-anazi, 2018). Results are promising as the performance of GCALB increased by 15% and 12% when compared to HyperFlow and by 13% and 10% when compared to ECFT in terms of throughput and response time.
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14

Kim, Won-Suk, and Sang-Hwa Chung. "Proxy SDN Controller for Wireless Networks." Mobile Information Systems 2016 (2016): 1–14. http://dx.doi.org/10.1155/2016/7172187.

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Management of wireless networks as well as wired networks by using software-defined networking (SDN) has been highlighted continually. However, control features of a wireless network differ from those of a wired network in several aspects. In this study, we identify the various inefficient points when controlling and managing wireless networks by using SDN and propose SDN-based control architecture called Proxcon to resolve these problems. Proxcon introduces the concept of a proxy SDN controller (PSC) for the wireless network control, and the PSC entrusted with the role of a main controller performs control operations and provides the latest network state for a network administrator. To address the control inefficiency, Proxcon supports offloaded SDN operations for controlling wireless networks by utilizing the PSC, such as local control by each PSC, hybrid control utilizing the PSC and the main controller, and locally cooperative control utilizing the PSCs. The proposed architecture and the newly supported control operations can enhance scalability and response time when the logically centralized control plane responds to the various wireless network events. Through actual experiments, we verified that the proposed architecture could address the various control issues such as scalability, response time, and control overhead.
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Llerena, Yarisley Pena, and Paulo R. L. Gondim. "SDN-Controller Placement for D2D Communications." IEEE Access 7 (2019): 169745–61. http://dx.doi.org/10.1109/access.2019.2955434.

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Dixit, Advait, Fang Hao, Sarit Mukherjee, T. V. Lakshman, and Ramana Kompella. "Towards an elastic distributed SDN controller." ACM SIGCOMM Computer Communication Review 43, no. 4 (September 19, 2013): 7–12. http://dx.doi.org/10.1145/2534169.2491193.

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17

Derhab, Abdelouahid, Mohamed Guerroumi, Mohamed Belaoued, and Omar Cheikhrouhou. "BMC-SDN: Blockchain-Based Multicontroller Architecture for Secure Software-Defined Networks." Wireless Communications and Mobile Computing 2021 (April 21, 2021): 1–12. http://dx.doi.org/10.1155/2021/9984666.

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Multicontroller software-defined networks have been widely adopted to enable management of large-scale networks. However, they are vulnerable to several attacks including false data injection, which creates topology inconsistency among controllers. To deal with this issue, we propose BMC-SDN, a security architecture that integrates blockchain and multicontroller SDN and divides the network into several domains. Each SDN domain is managed by one master controller that communicates through blockchain with the masters of the other domains. The master controller creates blocks of network flow updates, and its redundant controllers validate the new block based on a proposed reputation mechanism. The reputation mechanism rates the controllers, i.e., block creator and voters, after each voting operation using constant and combined adaptive fading reputation strategies. The evaluation results demonstrate a fast and optimal detection of fraudulent flow rule injection.
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Jo, Hyeonseong, Jaehyun Nam, and Seungwon Shin. "NOSArmor: Building a Secure Network Operating System." Security and Communication Networks 2018 (2018): 1–14. http://dx.doi.org/10.1155/2018/9178425.

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Software-Defined Networking (SDN), controlling underlying network devices (i.e., data plane) in a logically centralized manner, is now actively adopted in many real world networking environments. It is clear that a network administrator can easily understand and manage his networking environments with the help of SDN. In SDN, a network operating system (NOS), also known as an SDN controller, is the most critical component because it should be involved in all transactions for controlling network devices, and thus the security of NOS cannot be highly exaggerated. However, in spite of its importance, no previous works have thoroughly investigated the security of NOS. In this work, to address this problem, we present the NOSArmor, which integrates several security mechanisms, named as security building block (SBB), into a consolidated SDN controller. NOSArmor consists of eight SBBs and each of them addresses different security principles of network assets. For example, while role-based authorization focuses on securing confidentiality of internal storage from malicious applications, OpenFlow protocol verifier protects availability of core service in the controller from malformed control messages received from switches. In addition, NOSArmor shows competitive performance compared to existing other controllers (i.e., ONOS, Floodlight) with secureness of network assets.
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Sminesh, C. N., E. Grace Mary Kanaga, and A. G. Sreejish. "Augmented Affinity Propagation-Based Network Partitioning for Multiple Controllers Placement in Software Defined Networks." Journal of Computational and Theoretical Nanoscience 17, no. 1 (January 1, 2020): 228–33. http://dx.doi.org/10.1166/jctn.2020.8655.

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Software Defined Networks (SDN) divide network intelligence and packet forwarding functionalities between control plane and data plane devices respectively. Multiple controllers need to be deployed in the control plane in large SDN networks to improve performance and scalability. In a multi-controller scenario, finding the adequate number of controllers and their load distribution are open research challenges. In a large-scale network, the control plane load balancing is termed a controller placement problem (CPP). It is observed that of the existing solutions for the CPP, clustering-based approaches provide computationally less intensive solutions. The proposed augmented affinity propagation (augmented-AP) clustering identifies the required number of network partitions and places the controllers such that the distribution of switches to the controller is much better than with existing algorithms. The simulation results show that the computed controller imbalance factor of augmented-AP algorithm outperforms the existing k-means algorithm.
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Gull, Mawra, and Jasdeep Singh. "Convergence Time Monitoring Algorithm in Hybrid Software Defined Networks." International Journal of Computer Science and Mobile Computing 10, no. 8 (August 30, 2021): 23–31. http://dx.doi.org/10.47760/ijcsmc.2021.v10i08.004.

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Network consummation especially dependent on traffic monitoring. Therefore, Software Defined Network (SDN) technology is submitted to support the flow control suitable monitoring by providing a global view of the network. Unfortunately, replacing the entire traditional network to SDN is complex, which leads to the need of SDN switches deployment to the current network. Thus, a hybrid network environment has emerged which consists of centralized controller, SDN switch and legacy routers. Hence, the advantage of the integration of traditional network and SDN will take place. The controller can collect SDN data instantly, while it waits for a long time to obtain the legacy network data. On the other hand, the rest of paths cannot be processed directly by the controller. Therefore, legacy path load data is estimated for the past time to support the controller for obtaining the current data. The convergence time of the proposed algorithm takes more convergence time than the full SDN by only 12%. Therefore, the proposed algorithm provides installing the minimum possible number of SDN switches that reduce the infrastructure cost.
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Wu, Zehui, and Qiang Wei. "Quantitative Analysis of the Security of Software-Defined Network Controller Using Threat/Effort Model." Mathematical Problems in Engineering 2017 (2017): 1–11. http://dx.doi.org/10.1155/2017/8740217.

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SDN-based controller, which is responsible for the configuration and management of the network, is the core of Software-Defined Networks. Current methods, which focus on the secure mechanism, use qualitative analysis to estimate the security of controllers, leading to inaccurate results frequently. In this paper, we employ a quantitative approach to overcome the above shortage. Under the analysis of the controller threat model we give the formal model results of the APIs, the protocol interfaces, and the data items of controller and further provide our Threat/Effort quantitative calculation model. With the help of Threat/Effort model, we are able to compare not only the security of different versions of the same kind controller but also different kinds of controllers and provide a basis for controller selection and secure development. We evaluated our approach in four widely used SDN-based controllers which are POX, OpenDaylight, Floodlight, and Ryu. The test, which shows the similarity outcomes with the traditional qualitative analysis, demonstrates that with our approach we are able to get the specific security values of different controllers and presents more accurate results.
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Yeo, Sangho, Ye Naing, Taeha Kim, and Sangyoon Oh. "Achieving Balanced Load Distribution with Reinforcement Learning-Based Switch Migration in Distributed SDN Controllers." Electronics 10, no. 2 (January 13, 2021): 162. http://dx.doi.org/10.3390/electronics10020162.

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Distributed controllers in software-defined networking (SDN) become a promising approach because of their scalable and reliable deployments in current SDN environments. Since the network traffic varies with time and space, a static mapping between switches and controllers causes uneven load distribution among controllers. Dynamic migration of switches methods can provide a balanced load distribution between SDN controllers. Recently, existing reinforcement learning (RL) methods for dynamic switch migration such as MARVEL are modeling the load balancing of each controller as linear optimization. Even if it is widely used for network flow modeling, this type of linear optimization is not well fitted to the real-world workload of SDN controllers because correlations between resource types are unexpectedly and continuously changed. Consequently, using the linear model for resource utilization makes it difficult to distinguish which resource types are currently overloaded. In addition, this yields a high time cost. In this paper, we propose a reinforcement learning-based switch and controller selection scheme for switch migration, switch-aware reinforcement learning load balancing (SAR-LB). SAR-LB uses the utilization ratio of various resource types in both controllers and switches as the inputs of the neural network. It also considers switches as RL agents to reduce the action space of learning, while it considers all cases of migrations. Our experimental results show that SAR-LB achieved better (close to the even) load distribution among SDN controllers because of the accurate decision-making of switch migration. The proposed scheme achieves better normalized standard deviation among distributed SDN controllers than existing schemes by up to 34%.
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Tran, Anh Khoa, Md Jalil Piran, and Chuan Pham. "SDN Controller Placement in IoT Networks: An Optimized Submodularity-Based Approach." Sensors 19, no. 24 (December 12, 2019): 5474. http://dx.doi.org/10.3390/s19245474.

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Software-Defined Networking (SDN) has opened a promising and potential approach for future networks, which mostly requires the low-level configuration to implement different controls. With the high advantages of SDN by decomposing the network control plane from the data plane, SDN has become a crucial platform to implement Internet of Things (IoT) services. However, a static SDN controller placement cannot obtain an efficient solution in distributed and dynamic IoT networks. In this paper, we investigate an optimization framework under a well-known theory, namely submodularity optimization, to formulate and address different aspects of the controller placement problem in a distributed network, specifically in an IoT scenario. Concretely, we develop a framework that deals with a series of controller placement problems from basic to complicated use cases. Corresponding to each use case, we provide discussion and a heuristic algorithm based on the submodularity concept. Finally, we present extensive simulations conducted on our framework. The simulation results show that our proposed algorithms can outperform considered baseline methods in terms of execution time, the number of controllers, and network latency.
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Mishra, Shailendra. "SDN-Based Secure Architecture for IoT." International Journal of Knowledge and Systems Science 11, no. 4 (October 2020): 1–16. http://dx.doi.org/10.4018/ijkss.2020100101.

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Internet of things (IoT) means connecting things through the internet. The growing market for IoT also attracts malicious individuals trying to gain access to the marketplace. Security issues are among the most significant worries in companies that rely on the cloud of things to do business. SDN-based architecture has improved the security of IoT networks. The centralized controller is responsible for managing the critical network's operations, and growing the network size increases the network load in the controller. Controllers in SDN-based architecture are still facing security challenges such as unauthorized access, configuration issues, distributed denial of service (DDoS) attacks, and a man-in-the-middle (MITM) attacks. The attack scenario and security of SDN-based IoT networks are evaluated in this research. The simulation results show that the proposed approach and security solutions are fast and effective in mitigating the attacks.
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R, Sanjeetha, Shikhar Srivastava, Rishab Pokharna, Syed Shafiq, and Dr Anita Kanavalli. "Mitigation of DDoS attack instigated by compromised switches on SDN controller by analyzing the flow rule request traffic." International Journal of Engineering & Technology 7, no. 2.6 (March 11, 2018): 46. http://dx.doi.org/10.14419/ijet.v7i2.6.10065.

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Software Defined Network (SDN) is a new network architecture which separates the data plane from the control plane. The SDN controller implements the control plane and switches implement the data plane. Many papers discuss about DDoS attacks on primary servers present in SDN and how they can be mitigated with the help of controller. In our paper we show how DDoS attack can be instigated on the SDN controller by manipulating the flow table entries of switches, such that they send continuous requests to the controller and exhaust its resources. This is a new, but one of the possible way in which a DDoS attack can be performed on controller. We show the vulnerability of SDN for this kind of attack. We further propose a solution for mitigating it, by running a DDoS Detection module which uses variation of flow entry request traffic from all switches in the network to identify compromised switches and blocks them completely.
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Shafique, Ayesha, Guo Cao, Muhammad Aslam, Muhammad Asad, and Dengpan Ye. "Application-Aware SDN-Based Iterative Reconfigurable Routing Protocol for Internet of Things (IoT)." Sensors 20, no. 12 (June 22, 2020): 3521. http://dx.doi.org/10.3390/s20123521.

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The central intelligence offered by Software Defined Networking (SDN) promise the smart and reliable reconfiguration which enables the scalability of dynamic enterprise networks. The decoupled forwarding plane and control plane of SDN infrastructure is a key feature that supports the SDN controller to extract the physical network topology information at runtime to formulate network reconfigurations. This SDN-based network reconfiguration enables application-aware routing capability for Internet of Thing (IoT). However, these IoT enabled SDN-based routing protocols face some performance limitations in iterative reconfiguration process due to complete centralized path selection mechanism To this end, in this paper, we propose SDN-Based Application-aware Distributed adaptive Flow Iterative Reconfiguring (SADFIR) routing protocol. The proposed routing protocol enables the distributed SDN iterative solver controller to maintain the load-balancing between flow reconfiguration and flow allocation cost. In particular, the proposed routing protocol of SADFIR implements multiple SDN controllers that collaborate with network devices at forwarding plane to develop appropriate clustering strategy for routing the sensed information. This distributed SDN controllers are assisted to clustering topology that successfully map the residual network resources and also enable unique multi-hop application-aware data transmission. In addition, the proposed SADFIR monitor the iterative reconfiguration settings according to the network traffic of heterogeneity-aware network devices. The simulation experiments are conducted in comparison with the state-of-the-art routing protocols which demonstrates that SADFIR is heterogeneity-aware which is able to adopt the different scales of network with maximum network lifetime.
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Djeldjeli, Y., and M. Zoubir. "CP-SDN: A New Approach for the Control Operation of 5G Mobile Networks to Improve QoS." Engineering, Technology & Applied Science Research 11, no. 2 (April 11, 2021): 6857–63. http://dx.doi.org/10.48084/etasr.4016.

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Today, the Software Defined Network (SDN) technology gives more efficiency and flexibility to the 5G mobile networks that are expected to support an enormous amount of data relating to various constrained services. The 5G network should implement newer approaches and technologies that allow supporting the scalability and mobility of the network. The SDN approach consists of decoupling between the control operation and the networking operation, where the control operation is held by the SDN controller that is responsible for defining the management and the control rules. Data forwarding is performed by switches that apply rules defined by their controllers. In the current study, we have proposed and defined a new approach named CP-SDN: Cooperative Protocol-SDN, as an extension to the existing Software Defined Networks, especially when the network experiences saturation due to the huge amount of exchanged data. This congestion may affect the constrained flow and leads to an undesired delay that affects the network Quality of Service (QoS). CP-SDN consists of a cooperation technique between neighboring controllers that aims to relieve the congested centers and redirect the extra flow through neighbors. CP-SDN processing keeps controller databases updated and assures the optimized path for the extra flow when network congestion occurs. The performed simulations on calculating the e-Mbb and M-iOT delay performances for various probability densities show that CP-SDN brings more reliability and efficiency in reducing the transmission delay and overcome the existing SDN scheme. This makes it a prime candidate for the evolved high scalable 5G networks.
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Wytrębowicz, Jacek, Thorsten Ries, Khoa Truong Dinh, and Sławomir Kukliński. "SDN Controller Mechanisms for Flexible and Customized Networking." International Journal of Electronics and Telecommunications 60, no. 4 (December 23, 2014): 299–307. http://dx.doi.org/10.2478/eletel-2014-0039.

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Abstract Software-Defined Networking (SDN) is seen as the most promising networking technology today. The spread of a new technology depends on the acceptance of the engineers implementing the networks. Typically, when engineers start the conceptualization of new network devices that work with a new paradigm, and that should provide expected business values, they must identify and utilize technical enablers for the defined business use cases. This paper tries to summarize essential SDN applications and defines the technical enablers for advanced and efficient SDN networking. To this end, we identify the core technical mechanisms, expecting to provide a useful analysis for the design of new SDN networks.
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Suh, Dongeun, and Sangheon Pack. "Low-Complexity Master Controller Assignment in Distributed SDN Controller Environments." IEEE Communications Letters 22, no. 3 (March 2018): 490–93. http://dx.doi.org/10.1109/lcomm.2017.2787590.

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Model, M., V. Kovalenko, A. Volkov A., and A. Muthanna. "Implementation Methods for SDN Controllers in a UAV Network." Telecom IT 8, no. 4 (December 23, 2020): 23–34. http://dx.doi.org/10.31854/2307-1303-2020-8-4-23-34.

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Research subject. The division of the performed functions between all UAVs of the same cluster, a comparison of the methods for implementing the SDN controller into the UAV network, a description of the sequence of actions implemented in the UAV cluster, depending on a specific application scenario. Method. Analysis of standards and recommendations in the field of SDN technologies and construction of UAV networks; Comparison of SDN controller implementation methods: outside the cluster, on the head node, on all UAVs of the same cluster, and implementation using two controllers (one outside the cluster, and the second on the head node). Core results. 4 ways of using the UAV are described in de-tail, as well as the sequence of actions performed by the UAV cluster for each method; Compared 4 ways to implement the SDN controller in the UAV network; A method for dividing the performed func-tions between UAVs of one cluster is presented. Practical relevance. The sequences of actions pre-sented for each method of application will allow in the future to implement the execution of these scenar-ios using a UAV cluster; The article details the advantages and disadvantages of all four ways to imple-ment an SDN controller; the presented method of dividing functions between UAVs has less resource consumption for individual UAVs and for the entire cluster as a whole, than with the method with the im-plementation of all functions on each UAV of the cluster.
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Prasad, B. V. V. S., and Sd Salman Ali. "Software – defined networking based secure rout-ing in mobile ad hoc network." International Journal of Engineering & Technology 7, no. 1.2 (December 28, 2017): 229. http://dx.doi.org/10.14419/ijet.v7i1.2.9288.

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Traditional communication networks can be leveraged by separating controlling functions from forwarding functions using emerging technology known as Software Defined Networking (SDN). Though SDN has been around for some years, it was mostly limited to wired networks. Of late, it is being adapted to wireless networks. The programmable interface with decoupled controller can be used with MANET to integrate with other networks besides controlling it well. Both control and security are inevitable for the successful implementation of SDN in wireless networks. Towards this end, in this paper we implemented SDN based MANET for secure routing. Open Flow is used for implementing SDN controller while IDC is used for securing communications. Our framework is evaluated with NS3 simulations that reveal significant performance improvement when compared with traditional ad hoc networks that do not use SDN. This is achieved as SDN controller can quickly adapt to changed topologies due to node mobility.
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Kovalenko, V., A. A. Alzaghir, and A. Muthanna. "Building a UAV network with support for SDN / NFV technologies." Telecom IT 8, no. 3 (September 30, 2020): 71–85. http://dx.doi.org/10.31854/2307-1303-2020-8-3-71-85.

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Research Subject - integration of software-defined networks (SDN) and network functions virtualization (NFV) technologies in the unmanned aerial vehicle networks. Method – analysis of standards and recommendations in the field of SDN, NFV technologies and construction of UAV networks. Core results – presents the main advantages of introducing SDN and NFV technologies into the UAV networks, two ways of organizing the UAV network architecture with SDN technology support: when the Base Station performs the functions of an SDN controller, and when air baluns are used as SDN controllers. This paper also compared the technologies of software-defined networking and virtualization of network functions. Practical relevance – this paper provides a detailed description of the structure and application possibilities of UAV networks, functional diagrams of SDN and NFV. The network architectures presented in this paper using SDN controllers in the flying (air balloon) and ground (Base stations) segment are examples of the implementation of SDN technology in a UAV network.of SDN and NFV technologies, and also considers the application of these technologies in UAV networks.
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Yu, Haisheng, Keqiu Li, and Heng Qi. "An Active Controller Selection Scheme for Minimizing Packet-In Processing Latency in SDN." Security and Communication Networks 2019 (October 13, 2019): 1–11. http://dx.doi.org/10.1155/2019/1949343.

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In software-defined network, the use of distributed controllers to control forwarding devices has been proposed to solve the issues of scalability and load balance. However, the forwarding devices are statically assigned to the controllers in these distributed systems, which can overload some controllers while others are underutilized. In this paper, we propose an architecture named ASLB (active controller selection load balance), which proactively selects appropriate controllers for load balancing and minimize packet processing delays. We also present a novel active controller selection algorithm (ACS) for ASLB that efficiently schedules traffic from the switch to the controller and designs an intermediate coordinator for actively selecting a controller to serve a request. We built a system and evaluated it on a physical platform. The results show that ASLB is much better than the static allocation scheme in terms of minimizing latency, bandwidth utilization, and throughput.
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Iryani, Nanda, Afifah Dwi Ramadhani, and Mayang Karmila Sari. "Analisis Performansi Routing OSPF menggunakan RYU Controller dan POX Controller pada Software Defined Networking." Jurnal Telekomunikasi dan Komputer 11, no. 1 (April 1, 2021): 73. http://dx.doi.org/10.22441/incomtech.v11i1.10187.

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Software Defined Networking (SDN) adalah teknologi baru yang dikembangkan untuk mengatasi masalah kompleksitas konfigurasi jaringan dengan pengelolaan lebih terpusat karena memisahkan antara control plane dan data plane. Penelitian ini menganalisis perbandingan performansi SDN menggunakan ryu controller dan pox controller. Protocol yang digunakan adalah protocol TCP dan UDP sedangkan routingnya menggunakan OSPF. Penerapan algoritma dijkstra dari perutean OSPF ke topologi fat tree pada SDN akan diukur unjuk kerjanya berdasarkan parameter Quality of Service yaitu delay, jitter, dan packet loss pada skenario tanpa background traffic. Transmisi data menggunakan traffic protocol TCP dengan RYU controller dan protokol UDP lebih baik karena memiliki delay sebesar 49.44% dan delay yang lebih stabil sebesar 0.01 %. Jitter yang dihasilkan adalah 27.59% lebih baik daripada POX controller sebesar 72.41% dan untuk protokol UDP menggunakan POX controller 99.97% sedangkan traffic protocol UDP menggunakan RYU controller lebih baik sebesar 0.03%. Packet loss dari kedua controller didapatkan hasil protokol TCP sangat bagus sebesar 0% sedangkan protokol UDP menggunakan POX controller 83.13%, menggunakan RYU controller 16.87%.
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Vybornova, A. "A Survay on the Swarm Intelligence Approaches to Controller Placement Problem in the Software Defined Networks Design and Optimization." Telecom IT 8, no. 4 (December 23, 2020): 83–92. http://dx.doi.org/10.31854/2307-1303-2020-8-4-83-92.

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This article is dedicated to the overview and analysis of the existing approaches to the controller placement problem for the multi-controller Software Defined Networks (SDN) with a focus on the swarm intelligence methods. For this purpose, the controller placement problem is defined, as well as possible optimization functions and constraints. Research subject of this article is a controller placement problem for the multi-controller SDN. As a research method a comparative analysis is used. Core results of the work is a comparison of different approaches based on the different optimality criteria and constraints. Practical relevance of the work is that the results can be used in the SDN design and optimization.
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Alssaheli, Omran M. A., Z. Zainal Abidin, N. A. Zakaria, and Z. Abal Abas. "Implementation of Network Traffic Monitoring using Software Defined Networking Ryu Controller." WSEAS TRANSACTIONS ON SYSTEMS AND CONTROL 16 (May 25, 2021): 270–77. http://dx.doi.org/10.37394/23203.2021.16.23.

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Network traffic monitoring is vital for enhancing the overall network performance and for optimizing the traffic flows. However, an emerging growth of use in cloud services, internet-of-things, block-chain and data analytics, demand the hardware-based-network-controller to provide more features for expanding network architecture. Therefore, Software Defined Networking (SDN) offers a new solution in terms of scalability, usability and programmable software-based-network-controller for the legacy network infrastructure. In fact, SDN provides a dynamic platform for the network traffic monitoring using international standard. In this study, SDN setup and installation method uses a Mininet emulator containing a controller Ryu with switching hub component, OpenFlow switches, and nodes. The number of nodes is adding until reaches to 16 nodes and evaluated through different network scenarios (single, linear and tree topology). Findings show that the single topology gives a winning criterion compared to other topologies. SDN implementation is measured with performance parameters such as Throughput, Jitter, Bandwidth and Round-Trip Time between scenarios using the Ryu controller. Future research explores on the performance of SDN in larger network and investigates the efficiency and effectiveness of SDN implementation in mesh topology.
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Isong, Bassey, Tebogo Kgogo, and Francis Lugayizi. "Trust Establishment in SDN: Controller and Applications." International Journal of Computer Network and Information Security 9, no. 7 (July 8, 2017): 20–28. http://dx.doi.org/10.5815/ijcnis.2017.07.03.

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Krishnamohan, Theviyanthan, Kugathasan Janarthanan, Peramune P.R.L.C, and Ranaweera A.T. "BlockFlow: A decentralized SDN controller using blockchain." International Journal of Scientific and Research Publications (IJSRP) 10, no. 3 (March 24, 2020): p9991. http://dx.doi.org/10.29322/ijsrp.10.03.2020.p9991.

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Bera, Samaresh, Sudip Misra, and Niloy Saha. "Traffic-Aware Dynamic Controller Assignment in SDN." IEEE Transactions on Communications 68, no. 7 (July 2020): 4375–82. http://dx.doi.org/10.1109/tcomm.2020.2983168.

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Isong, Bassey, Reorapetse Ramoliti Samuel Molose, Adnan M. Abu-Mahfouz, and Nosipho Dladlu. "Comprehensive Review of SDN Controller Placement Strategies." IEEE Access 8 (2020): 170070–92. http://dx.doi.org/10.1109/access.2020.3023974.

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V T, Noora, and S. Vinila Jinny Dr. "DESIGN OF DIFFERENT TOPOLOGIES IN SDN CONTROLLER." Indian Journal of Computer Science and Engineering 11, no. 5 (October 31, 2020): 582–92. http://dx.doi.org/10.21817/indjcse/2020/v11i5/201105203.

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Das, Tamal, Vignesh Sridharan, and Mohan Gurusamy. "A Survey on Controller Placement in SDN." IEEE Communications Surveys & Tutorials 22, no. 1 (2020): 472–503. http://dx.doi.org/10.1109/comst.2019.2935453.

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Tupakula, Udaya, Vijay Varadharajan, and Preeti Mishra. "Securing SDN controller and switches from attacks." International Journal of High Performance Computing and Networking 14, no. 1 (2019): 77. http://dx.doi.org/10.1504/ijhpcn.2019.099746.

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Mishra, Preeti, Udaya Tupakula, and Vijay Varadharajan. "Securing SDN controller and switches from attacks." International Journal of High Performance Computing and Networking 14, no. 1 (2019): 77. http://dx.doi.org/10.1504/ijhpcn.2019.10021108.

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Dvir, Amit, Yoram Haddad, and Aviram Zilberman. "The controller placement problem for wireless SDN." Wireless Networks 25, no. 8 (July 4, 2019): 4963–78. http://dx.doi.org/10.1007/s11276-019-02077-5.

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Yang, Ze, and Kwan L. Yeung. "Minimum weight controller tree design in SDN." Computer Networks 165 (December 2019): 106949. http://dx.doi.org/10.1016/j.comnet.2019.106949.

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Benamrane, Fouad, Mouad Ben Mamoun, and Redouane Benaini. "New method for controller-to-controller communication in distributed SDN architecture." International Journal of Communication Networks and Distributed Systems 19, no. 3 (2017): 357. http://dx.doi.org/10.1504/ijcnds.2017.086493.

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Benamrane, Fouad, Mouad Ben Mamoun, and Redouane Benaini. "New method for controller-to-controller communication in distributed SDN architecture." International Journal of Communication Networks and Distributed Systems 19, no. 3 (2017): 357. http://dx.doi.org/10.1504/ijcnds.2017.10007319.

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Das, Tamal, and Mohan Gurusamy. "Controller Placement for Resilient Network State Synchronization in Multi-Controller SDN." IEEE Communications Letters 24, no. 6 (June 2020): 1299–303. http://dx.doi.org/10.1109/lcomm.2020.2979072.

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Latah, Majd, and Levent Toker. "A novel intelligent approach for detecting DoS flooding attacks in software-defined networks." International Journal of Advances in Intelligent Informatics 4, no. 1 (March 31, 2018): 11. http://dx.doi.org/10.26555/ijain.v4i1.138.

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Software-Defined Networking (SDN) is an emerging networking paradigm that provides an advanced programming capability and moves the control functionality to a centralized controller. This paper proposes a two-stage novel intelligent approach that takes advantage of the SDN approach to detect Denial of Service (DoS) flooding attacks based on calculation of packet rate as the first step and followed by Support Vector Machine (SVM) classification as the second step. Flow concept is an essential idea in OpenFlow protocol, which represents a common interface between an SDN switch and an SDN controller. Therefore, our system calculates the packet rate of each flow based on flow statistics obtained by SDN controller. Once the packet rate exceeds a predefined threshold, the system will activate the packet inspection unit, which, in turn, will use the (SVM) algorithm to classify the previously collected packets. The experimental results showed that our system was able to detect DoS flooding attacks with 96.25% accuracy and 0.26% false alarm rate.
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