scholarly journals Artificial Intelligence Enabled Routing in Software Defined Networking

2020 ◽  
Vol 10 (18) ◽  
pp. 6564 ◽  
Author(s):  
Yan-Jing Wu ◽  
Po-Chun Hwang ◽  
Wen-Shyang Hwang ◽  
Ming-Hua Cheng

Software defined networking (SDN) is an emerging networking architecture that separates the control plane from the data plane and moves network management to a central point, called the controller. The controller is responsible for preparing the flow tables of each switch in the data plane. Although dynamic routing can perform rerouting in case of congestion by periodically monitoring the status of each data flow, problems concerning a suitable monitoring period duration and lack of learning ability from past experiences to avoid similar but ineffective route decisions remain unsolved. This paper presents an artificial intelligence enabled routing (AIER) mechanism with congestion avoidance in SDN, which can not only alleviate the impact of monitoring periods with dynamic routing, but also provide learning ability and superior route decisions by introducing artificial intelligence (AI) technology. We evaluate the performance of the proposed AIER mechanism on the Mininet simulator by installing three additional modules, namely, topology discovery, monitoring period, and an artificial neural network, in the control plane. The effectiveness and superiority of our proposed AIER mechanism are demonstrated by performance metrics, including average throughput, packet loss ratio, and packet delay versus data rate for different monitoring periods in the system.

2020 ◽  
pp. 1-20
Author(s):  
K. Muthamil Sudar ◽  
P. Deepalakshmi

Software-defined networking is a new paradigm that overcomes problems associated with traditional network architecture by separating the control logic from data plane devices. It also enhances performance by providing a highly-programmable interface that adapts to dynamic changes in network policies. As software-defined networking controllers are prone to single-point failures, providing security is one of the biggest challenges in this framework. This paper intends to provide an intrusion detection mechanism in both the control plane and data plane to secure the controller and forwarding devices respectively. In the control plane, we imposed a flow-based intrusion detection system that inspects every new incoming flow towards the controller. In the data plane, we assigned a signature-based intrusion detection system to inspect traffic between Open Flow switches using port mirroring to analyse and detect malicious activity. Our flow-based system works with the help of trained, multi-layer machine learning-based classifier, while our signature-based system works with rule-based classifiers using the Snort intrusion detection system. The ensemble feature selection technique we adopted in the flow-based system helps to identify the prominent features and hasten the classification process. Our proposed work ensures a high level of security in the Software-defined networking environment by working simultaneously in both control plane and data plane.


2020 ◽  
Author(s):  
Hamid Nejadnik ◽  
Rasool Sadeghi ◽  
Sayed Mahdi Faghih Imani

Abstract Software Defined Networking (SDN) is a novel architecture that separates the data plane from the control plane using an external controller. Similar to traditional networks, load balancing has a great impact on the performance and availability of SDN. Therefore, the Controller Placement Problem (CPP) in SDN influences on the load balancing solutions. In this paper, various topologies of CPP including different load balancer controllers are simulated and evaluated in the SDN using the OFSwitch13 module of ns-3 network simulator. The results provide a solid comparison of the proposed topologies in different network situations.


2020 ◽  
Vol 12 (9) ◽  
pp. 147 ◽  
Author(s):  
Babangida Isyaku ◽  
Mohd Soperi Mohd Zahid ◽  
Maznah Bte Kamat ◽  
Kamalrulnizam Abu Bakar ◽  
Fuad A. Ghaleb

Software defined networking (SDN) is an emerging network paradigm that decouples the control plane from the data plane. The data plane is composed of forwarding elements called switches and the control plane is composed of controllers. SDN is gaining popularity from industry and academics due to its advantages such as centralized, flexible, and programmable network management. The increasing number of traffics due to the proliferation of the Internet of Thing (IoT) devices may result in two problems: (1) increased processing load of the controller, and (2) insufficient space in the switches’ flow table to accommodate the flow entries. These problems may cause undesired network behavior and unstable network performance, especially in large-scale networks. Many solutions have been proposed to improve the management of the flow table, reducing controller processing load, and mitigating security threats and vulnerabilities on the controllers and switches. This paper provides comprehensive surveys of existing schemes to ensure SDN meets the quality of service (QoS) demands of various applications and cloud services. Finally, potential future research directions are identified and discussed such as management of flow table using machine learning.


2014 ◽  
Vol 11 (2) ◽  
pp. 55-64 ◽  
Author(s):  
Qingyun Zuo ◽  
Ming Chen ◽  
Ke Ding ◽  
Bo Xu

Author(s):  
Do Van Khoa ◽  
Tran Ngo Nhu Khanh

Kiến trúc mạng thế hệ mới Software-defined networking (SDN) cho phép đơn giản hóa và cải tiến việc quản lý mạng bằng cách tách biệt hai thành phần điều khiển mạng (Control plane) với chức năng vận chuyển dữ liệu (Data plane). Tuy nhiên, do đang trong quá trình nghiên cứu, việc ứng dụng SDN vào thực tế còn chưa nhiều. Phần lớn các thiết bị chuyển mạch và định tuyến mạng hiện nay có hỗ trợ SDN có giá thành cao. Một giải pháp để nghiên cứu và thử nghiệm các tính năng của SDN là dùng các công cụ giả lập. Nghiên cứu thực hiện đánh giá triển khai SDN trên các môi trường khác nhau sử dụng công cụ mô phỏng Mininet. Kết quả cho thấy môi trường mô phỏng ảnh hưởng đến thời gian thực thi mô hình mạng


2014 ◽  
Author(s):  
Χρήστος Αργυρόπουλος

Η παρούσα Διδακτορική Διατριβή πραγματεύεται το πρόβλημα διασύνδεσης ετερογενών υποδομών εικονικών υπολογιστικών πόρων στο επίπεδο προώθησης πακέτων και τον εμπλουτισμό των δομών του επιπέδου ελέγχου και του επιπέδου διαχείρισης σε περιβάλλοντα εικονικής δικτύωσης οριζόμενης από λογισμικό (Software Defined Networking – SDN) πολλαπλών χρηστών/ενοικιαστών.Το σύνολο της μελέτης επικεντρώνεται σε τρεις βασικούς άξονες με κριτήριο το επίπεδο λειτουργίας δικτύου:Επίπεδο προώθησης πακέτων (data-plane)Δημιουργία μηχανισμού διασύνδεσης (stitching) πολλαπλών εικονικών υπολογιστικών πόρων ετερογενών ομόσπονδων υποδομών με μικρή χρονική επιβάρυνση και μικρή μείωση του ρυθμού μετάδοσης των δεδομένων. Η δυναμική απόδοση των απαιτούμενων πόρων γίνεται με κριτήριο την κλιμακοθετησιμότητα (scalability).Επίπεδο διαχείρισης (management-plane)Μελέτη εγγενών δυνατοτήτων/αδυναμιών του OpenFlow για παθητική παρακολούθηση και δημιουργία μηχανισμού για την αποδοτική παρακολούθηση σε περιβάλλοντα SDN υψηλού ρυθμού ροής δεδομένων, βασιζόμενο στο OpenFlow και το sFlow. Γίνεται πειραματική μελέτη των επιπτώσεων των τεχνικών δειγματοληψίας του sFlow στον εντοπισμό δικτυακών ανωμαλιών καθώς και των επιδράσεων που έχουν οι τελευταίες στο επίπεδο κεντρικοποιημένου ελέγχου δικτύων OpenFlow.Επίπεδο ελέγχου (control-plane)Δημιουργία μηχανισμού ανάθεσης ροών ανά εικονικό δίκτυο χρήστη σε περιβάλλοντα δικτύων μεγάλης κλίμακας κεντρικοποιημένου ελέγχου που κάνουν χρήση του πρωτοκόλλου OpenFlow. Γίνεται πειραματική σύγκριση των προτεινόμενων πολιτικών διαμοιρασμού του επιπέδου ελέγχου και απομόνωσης των εικονικών δικτύων, με κριτήριο απόδοσης την αύξηση των αποδεκτών αιτημάτων χρηστών και την κατανάλωση πόρων. Το κριτήριο απομόνωσης εξασφαλίζεται από τις προτεινόμενες μεθόδους διαμοιρασμού και τις αντίστοιχες αρχιτεκτονικές διαμοιρασμού του επιπέδου ελέγχου που προτείνονται.Αρχικά μελετώνται τα επίπεδα λειτουργιών σε μοντέλα αναφοράς αρχιτεκτονικής δικτύου και δίνεται βάρος στο κεντρικοποιημένο επίπεδο ελέγχου, όπως αυτό έχει διαμορφωθεί με την χρήση του πρωτοκόλλου OpenFlow σε δίκτυα οριζόμενα από λογισμικό (SDN). Ακολουθεί αναφορά στην εικονικοποίηση δικτύων υπολογιστών και μελετώνται οι σχεδιαστικές ελλείψεις των πρώιμων υλοποιήσεων εικονικοποίησης καθώς και η εξέλιξή τους.Η μελέτη και η δημιουργία πρωτότυπου μηχανισμού διασύνδεσης (stitching) πολλαπλών εικονικών υπολογιστικών πόρων ετερογενών ομόσπονδων υποδομών περιγράφεται στη συνέχεια και αποτελεί το πρώτο μέρος της συνεισφοράς. Τα αποτελέσματα των πειραματικών μετρήσεων της πρωτότυπης υλοποίησης δείχνουν την επίτευξη μικρής χρονικής επιβάρυνσης και μικρής μείωσης του ρυθμού μετάδοσης των δεδομένων στα εικονικά δίκτυα των χρηστών. Στη συνέχεια, μελετάται η μέθοδος παθητικής παρακολούθησης με χρήση των εγγενών δυνατοτήτων του πρωτοκόλλου OpenFlow και των μειονεκτημάτων που παρουσιάζει η παρακολούθηση της δικτυακής κίνησης με την χρήση ενός πρωτοκόλλου κεντρικοποιημένου ελέγχου. Ακολουθεί η περιγραφή πλαισίου παθητικής παρακολούθησης υποδομών δικτυακής εικονικοποίησης που κάνει χρήση των πρωτοκόλλων OpenFlow και sFlow και έχει ως στόχο την ικανότητα χειρισμού μεγαλύτερου αριθμού ροών και ρυθμών μετάδοσης δεδομένων, σε σχέση με λύσεις που βασίζονται αποκλειστικά στο OpenFlow. Παρουσιάζονται πειραματικές μετρήσεις που προσφέρει ο μηχανισμός παθητικής παρακολούθησης δικτύων οριζόμενων από λογισμικό (προγραμματιζόμενα δίκτυα) με και χωρίς την συνδρομή του sFlow στον εντοπισμό και εξομάλυνση των δικτυακών ανωμαλιών. Βαρύτητα δίνεται στην αποτελεσματικότητα του sFlow (ευστοχία εντοπισμού δικτυακών ανωμαλιών, κατανάλωση πόρων του επιπέδου ελέγχου) και στην κλιμακοθετησιμότητα.Το τελευταίο μέρος της εργασίας αφορά μηχανισμό ανάθεσης ροών ανά εικονικό δίκτυο χρήστη σε περιβάλλοντα SDN κεντρικοποιημένου ελέγχου που κάνουν χρήση του πρωτοκόλλου OpenFlow. Ιδιαίτερη μελέτη, μέσω της υλοποίησης πρωτότυπης μηχανής διαμοιρασμού του πεδίου ορισμού των ροών (flowspace) και πειραματικών μετρήσεων, γίνεται για να διαπιστωθεί πως περιβάλλοντα SDN κεντρικοποιημένου ελέγχου μεγάλης κλίμακας μπορούν να κάνουν χρήση του πρωτοκόλλου OpenFlow για την παροχή προηγμένων υπηρεσιών εικονικής δικτύωσης.Εν κατακλείδι, αναφέρονται τα συμπεράσματα καθώς και οι επιστημονικές προεκτάσεις που αξιολογήθηκαν ως υψηλής ερευνητικής αξίας κατά τη συγγραφή της παρούσας Διδακτορικής Διατριβής


2014 ◽  
Vol 644-650 ◽  
pp. 2854-2856 ◽  
Author(s):  
Dong Ming Yuan ◽  
Rong Wei Ren

With the rapidly development of the space-sky information network, more and more satellites have been involved in the network. Adding the aerospace crafts which may be flexible and changeable, the network should be focused on the problem of heterogeneous compatibility and self-organizing network. The emerging Software Defined Networking may solve these problems. As the control plane and the data plane are separated in the architecture, the network can adapt to different protocols and can be flexible in equipment maintenance. In this paper, we propose an improving program of the space-sky network based on the SDN. This program can solve the existing problem of space network to some certain.


2016 ◽  
Vol 2016 ◽  
pp. 1-8 ◽  
Author(s):  
Othmane Blial ◽  
Mouad Ben Mamoun ◽  
Redouane Benaini

Software-defined networking offers several benefits for networking by separating the control plane from the data plane. However, networks’ scalability, reliability, and availability remain as a big issue. Accordingly, multicontroller architectures are important for SDN-enabled networks. This paper gives a comprehensive overview of SDN multicontroller architectures. It presents SDN and its main instantiation OpenFlow. Then, it explains in detail the differences between multiple types of multicontroller architectures, like the distribution method and the communication system. Furthermore, it provides already implemented and under research examples of multicontroller architectures by describing their design, their communication process, and their performance results.


2020 ◽  
Vol 9 (2) ◽  
pp. 24953-24961
Author(s):  
Worku Muluye

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.


In traditional network the coupling of data plane and control plane makes the data forwarding, processing and managing of the network hard and complex. Here each switch takes its own decision, makes the network logically decentralized. To overcome the limitations in traditional network the Engineers developed a new model network known as Software Defined Network (SDN). This network the control plane is decoupled from the data plane making it less complex. It moreover has a logically centralized approach unlike the existing network. This separation enables the network control to be directly programmable and the architecture to be abstracted for applications and network services. SDN platform provides advantages like programmability, task virtualization and easy management of the network. However, it faces new challenges towards scalability and performances. It is a must to understand and analyze the performances of SDN for implementation and deployment in live network environments. SDN working with POX is studied. This paper analyses the working of POX controller and evaluates the performance metrics of POX controller for SDN environment. The emulation is done using the Emulation software


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