scholarly journals Software Defined Networking Flow Table Management of OpenFlow Switches Performance and Security Challenges: A Survey

2020 ◽  
Vol 12 (9) ◽  
pp. 147 ◽  
Author(s):  
Babangida Isyaku ◽  
Mohd Soperi Mohd Zahid ◽  
Maznah Bte Kamat ◽  
Kamalrulnizam Abu Bakar ◽  
Fuad A. Ghaleb
Keyword(s):  
Large Scale ◽  
Network Performance ◽  
Software Defined Networking ◽  
Cloud Services ◽  
Future Research ◽  
Control Plane ◽  
Processing Load ◽  
Flow Table ◽  
Data Plane ◽  
Large Scale Networks

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.

Implementation of Network Traffic Monitoring using Software Defined Networking Ryu Controller

2021 ◽  
Vol 16 ◽  
pp. 270-277
Author(s):  
Omran M. A. Alssaheli ◽  
Z. Zainal Abidin ◽  
N. A. Zakaria ◽  
Z. Abal Abas
Keyword(s):  
Network Traffic ◽  
Network Architecture ◽  
Network Performance ◽  
Software Defined Networking ◽  
Traffic Monitoring ◽  
Cloud Services ◽  
Future Research ◽  
Mesh Topology ◽  
Network Controller ◽  
Network Traffic Monitoring

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.

An intelligent flow-based and signature-based IDS for SDNs using ensemble feature selection and a multi-layer machine learning-based classifier

2020 ◽  
pp. 1-20
Author(s):  
K. Muthamil Sudar ◽  
P. Deepalakshmi
Keyword(s):  
Machine Learning ◽  
Feature Selection ◽  
Intrusion Detection ◽  
Intrusion Detection System ◽  
Network Architecture ◽  
Detection System ◽  
Software Defined Networking ◽  
Control Plane ◽  
Control Logic ◽  
Data Plane

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.

scholarly journals A comprehensive evaluation of cache utilization characteristics in large scale WSN considering network driven cache replacement techniques

2018 ◽  
Vol 188 ◽  
pp. 05004
Author(s):  
Christos Panagiotou ◽  
Christos Antonopoulos ◽  
Stavros Koubias
Keyword(s):  
Smart City ◽  
Large Scale ◽  
Network Performance ◽  
Comprehensive Evaluation ◽  
Resource Conservation ◽  
Data Sources ◽  
Data Cache ◽  
Cache Replacement ◽  
Large Scale Networks ◽  
Result Analysis

WSNs as adopted in current smart city deployments, must address demanding traffic factors and resilience in failures. Furthermore, caching of data in WSN can significantly benefit resource conservation and network performance. However, data sources generate data volumes that could not fit in the restricted data cache resources of the caching nodes. This unavoidably leads to data items been evicted and replaced. This paper aims to experimentally evaluate the prominent caching techniques in large scale networks that resemble the Smart city paradigm regarding network performance with respect to critical application and network parameters. Through respective result analysis valuable insights are provided concerning the behaviour of caching in typical large scale WSN scenarios.

scholarly journals Load Balancing in Software-Defined Networking using Controller Placement

2020 ◽  
Author(s):  
Hamid Nejadnik ◽  
Rasool Sadeghi ◽  
Sayed Mahdi Faghih Imani
Keyword(s):  
Load Balancing ◽  
Software Defined Networking ◽  
Network Simulator ◽  
Control Plane ◽  
Placement Problem ◽  
Data Plane ◽  
Controller Placement ◽  
Controller Placement Problem ◽  
Load Balancer

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.

IMPLEMENTASI DAN ANALISIS EFEKTIVITAS FIREWALL PADA SOFTWARE DEFINED NETWORK BERBASIS OPENFLOW

2018 ◽  
Vol 4 (2) ◽  
pp. 46-57
Author(s):  
Fathul Muiin ◽  
Henry Saptono
Keyword(s):  
Software Defined Network ◽  
Control Plane ◽  
Flow Table ◽  
Data Plane

Penggunaan akses internet di dunia semakin berkembang, dan selaras dengan perkembangan teknologi jaringan komputer yang semakin kompleks. Oleh karena itu, keamanan data pada sebuah komputer menjadi salah satu bagian yang sangat penting dalam sebuah jaringan. Dan SDN merupakan sebuah solusi untuk menyediakan kebutuhan jaringan komputer saat ini. Software Defined Network (SDN) merupakan pendekatan pada teknologi jaringan yang melakukan penyederhanaan terhadap kontrol dan manajemen jaringan. Pada jaringan ini nantinya akan menggunakan protokol openflow, yang prinsip utamanya memisahkan fungsi control plane dan data plane pada perangkat. Kontrol jaringan pada sebuah controller bersifat programmable, jadi dengan adanya SDN maka jaringan akan mudah diatur dan lebih fleksibel. Implementasi dan analisis firewall ini menggunakan emulator mininet untuk membuat topologi jaringan yang sederhana. Dalam pengujian firewall menggunakan bahasa XML untuk implementasi aliran data, lalu menggunakan aplikasi postman sebagai alat untuk menambahkan flow table baru pada switch, dan controller yang digunakan adalah opendaylight.

scholarly journals Virtual Area Routing: a Scalable Intra-Domain Routing Scheme

2011 ◽  
Vol 1 ◽  
pp. 320-324
Author(s):  
Dan Zhao ◽  
Chun Qing Wu ◽  
Xiao Feng Hu ◽  
Hong Jun Liu
Keyword(s):  
Network Performance ◽  
Control Plane ◽  
Network Configuration ◽  
Large Networks ◽  
Link State ◽  
Routing Scheme ◽  
Control Overhead ◽  
Data Plane

As a distributed link state protocol, OSPF shows poor scalability when dealing with intra-domain routing in large networks. In this paper we present a new routing scheme called Virtual Area Routing (VAR) aimed to overcome the scalability problems of OSPF. The control plane is separated from data plane and is undertaken by dedicated elements in VAR. We show that VAR can simplify network configuration and management as well as avoid unnecessary route computation. Finally we conduct experiments in real topology and the result shows VAR can reduce control overhead and improve network performance.

scholarly journals Mitigation of DDoS attack instigated by compromised switches on SDN controller by analyzing the flow rule request traffic

2018 ◽  
Vol 7 (2.6) ◽  
pp. 46 ◽  
Author(s):  
Sanjeetha R ◽  
Shikhar Srivastava ◽  
Rishab Pokharna ◽  
Syed Shafiq ◽  
Dr Anita Kanavalli
Keyword(s):  
Network Architecture ◽  
Flow Rule ◽  
Software Defined Network ◽  
Ddos Attacks ◽  
Control Plane ◽  
Ddos Attack ◽  
Flow Table ◽  
Data Plane ◽  
Ddos Detection ◽  
Sdn Controller

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.

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
Keyword(s):  
Artificial Intelligence ◽  
Performance Metrics ◽  
Packet Delay ◽  
Software Defined Networking ◽  
Dynamic Routing ◽  
Learning Ability ◽  
Control Plane ◽  
Monitoring Period ◽  
Data Plane ◽  
The Impact

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.

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