scholarly journals P4-KBR: A Key-Based Routing System for P4-Programmable Networks

Electronics ◽  
2021 ◽  
Vol 10 (13) ◽  
pp. 1543
Author(s):  
Pilar Manzanares-Lopez ◽  
Juan Pedro Muñoz-Gea ◽  
Josemaria Malgosa-Sanahuja
Keyword(s):  
Network Management ◽  
Routing Protocol ◽  
Software Defined Networking ◽  
Packet Processing ◽  
End Points ◽  
Programmable Networks ◽  
Ip Addresses ◽  
Data Plane ◽  
Network Programmability

Software-defined networking (SDN) architecture has provided well-known advantages in terms of network programmability, initially offering a standard, open, and vendor-agnostic interface (e.g., OpenFlow) to instruct the forwarding behavior of network devices from different vendors. However, in the last few years, data plane programmability has emerged as a promising approach to extend the network management allowing the definition and programming of customized and non-standardized protocols, as well as specific packet processing pipelines. In this paper, we propose an in-network key-based routing protocol called P4-KBR, in which end-points (hosts, contents or services) are identified by virtual identifiers (keys) instead of IP addresses, and where P4 network elements are programmed to be able to route the packets adequately. The proposal was implemented and evaluated using bmv2 P4 switches, verifying how data plane programmability offers a powerful tool to overcome continuing challenges that appear in SDN networks.

scholarly journals A Review of the Control Plane Scalability Approaches in Software Defined Networking

2020 ◽  
Vol 12 (3) ◽  
pp. 49
Author(s):  
Abdelrahman Abuarqoub
Keyword(s):  
Network Management ◽  
Software Defined Networking ◽  
Research Trends ◽  
Control Plane ◽  
Recent Advances ◽  
Data Plane ◽  
Significant Research ◽  
Flexible Networks ◽  
Sdn Controller

Recent advances in information and communications cloud-based services hold the potential to overcome the scalability and complex maintenance limitations of traditional networks. Software Defined Networking (SDN) surfaced as a promising paradigm to mitigate such limitations while offering flexible networks management. Particularly, SDN separates the control plane from the data plane to achieve abstraction of lower-level functionality, hence, allowing more efficient network management and utilization. However, SDN suffers from various performance and scalability problems leading to significant research efforts on maximizing the scalability of the control plane. This paper aims at reviewing different SDN controller scalability, topology-based and mechanism-based approaches, as well as discussing and analyzing how they attempt to solve the scalability challenge. Furthermore, this paper elaborates on the promising research trends and challenges. Our insights are also discussed to stimulate further research efforts addressing the control plane scalability in SDN.

scholarly journals Software-defined networks: A walkthrough guide from occurrence To data plane fault tolerance

2019 ◽  
Author(s):  
Ali Malik ◽  
Benjamin Aziz ◽  
Ali Al-Haj ◽  
Mo Adda
Keyword(s):  
Fault Tolerance ◽  
Service Providers ◽  
Academic Research ◽  
Software Defined Networking ◽  
Network Control ◽  
Programmable Networks ◽  
Current State ◽  
Data Plane ◽  
Future Work ◽  
Near Future

In recent years, the emerging paradigm of software-defined networking has become a hot and thriving topic that grabbed the attention of industry sector as well as the academic research community. The decoupling between the network control and data planes means that software-defined networking architecture is programmable, adjustable and dynamically re-configurable. As a result, a large number of leading companies across the world have latterly launched software-defined solutions in their data centers and it is expected that most of the service providers will do so in the near future due to the new opportunities enabled by software-defined architectures. Nonetheless, each emerging technology is accompanied by new issues and concerns, and fault tolerance and recovery is one such issue that faces software-defined networking. Although there have been numerous studies that have discussed this issue, gaps still exist and need to be highlighted. In this paper, we start by tracing the evolution of networking systems from the mid 1990's until the emergence of programmable networks and software-defined networking, and then define a taxonomy for software-defined networking dependability by means of fault tolerance of data plane to cover all aspects, challenges and factors that need to be considered in future solutions. We discuss in a detailed manner current state-of-the-art literature in this area. Finally, we analyse the current gaps in current research and propose possible directions for future work.

Software-Defined Networking (SDN)

2021 ◽  
pp. 242-250
Author(s):  
L. Naga Durgaprasad Reddy
Keyword(s):  
Resource Allocation ◽  
Network Management ◽  
Software Defined Networking ◽  
Dynamic Resource Allocation ◽  
Control Plane ◽  
Application Layer ◽  
Physical Network ◽  
Data Plane ◽  
Dynamic Resource ◽  
Virtual Services

This chapter researches in the area of software-defined networking. Software-defined networking was developed in an attempt to simplify networking and make it more secure. By separating the control plane (the controller)—which decides where packets are sent—from the data plane (the physical network)—which forwards traffic to its destination—the creators of SDN hoped to achieve scalability and agility in network management. The application layer (virtual services) is also separate. SDN increasingly uses elastic cloud architectures and dynamic resource allocation to achieve its infrastructure goals.

scholarly journals IMPLEMENTING NDN USING SDN: A REVIEW ON METHODS AND APPLICATIONS

2016 ◽  
Vol 17 (2) ◽  
pp. 11-20 ◽  
Author(s):  
Shiva Rowshanrad ◽  
Mohamad Reza Parsaei ◽  
Manijeh Keshtgari
Keyword(s):  
Computer Networks ◽  
Network Architecture ◽  
Software Defined Networking ◽  
Network Architectures ◽  
Control Plane ◽  
Network Resources ◽  
End Points ◽  
Important Requirement ◽  
Data Plane ◽  
Data Networking

In recent years many claims about the limitations of todays’ network architecture, its lack of flexibility and ability to response to ongoing changes and increasing users demands. In this regard, new network architectures are proposed. Software Defined Networking (SDN) is one of these new architectures which centralizes the control of network by separating control plane from data plane. This separation leads to intelligence, flexibility and easier control in computer networks. One of the advantages of this framework is the ability to implement and test new protocols and architectures in actual networks without any concern of interruption.Named Data Networking (NDN) is another paradigm for future network architecture. With NDN the network becomes aware of the content that is providing, rather than just transferring it among end-points. NDN attracts researchers’ attention and known as the potential future of networking and internet. Providing NDN functionalities over SDN is an important requirement to enable the innovation and optimization of network resources. In this paper first we describe about SDN and NDN, and then we introduce methods for implementing NDN using SDN. We also point out the advantages and applications of implementing NDN over SDN.

scholarly journals Software-defined networks: A walkthrough guide from occurrence To data plane fault tolerance

2019 ◽  
Author(s):  
Ali Malik ◽  
Benjamin Aziz ◽  
Ali Al-Haj ◽  
Mo Adda
Keyword(s):  
Fault Tolerance ◽  
Service Providers ◽  
Academic Research ◽  
Software Defined Networking ◽  
Network Control ◽  
Programmable Networks ◽  
Current State ◽  
Data Plane ◽  
Future Work ◽  
Near Future

In recent years, the emerging paradigm of software-defined networking has become a hot and thriving topic that grabbed the attention of industry sector as well as the academic research community. The decoupling between the network control and data planes means that software-defined networking architecture is programmable, adjustable and dynamically re-configurable. As a result, a large number of leading companies across the world have latterly launched software-defined solutions in their data centers and it is expected that most of the service providers will do so in the near future due to the new opportunities enabled by software-defined architectures. Nonetheless, each emerging technology is accompanied by new issues and concerns, and fault tolerance and recovery is one such issue that faces software-defined networking. Although there have been numerous studies that have discussed this issue, gaps still exist and need to be highlighted. In this paper, we start by tracing the evolution of networking systems from the mid 1990's until the emergence of programmable networks and software-defined networking, and then define a taxonomy for software-defined networking dependability by means of fault tolerance of data plane to cover all aspects, challenges and factors that need to be considered in future solutions. We discuss in a detailed manner current state-of-the-art literature in this area. Finally, we analyse the current gaps in current research and propose possible directions for future work.

scholarly journals AccelSDP: A Reconfigurable Accelerator for Software Data Plane Based on FPGA SmartNIC

Electronics ◽  
2021 ◽  
Vol 10 (16) ◽  
pp. 1927
Author(s):  
Xiaoying Huang ◽  
Zhichuan Guo ◽  
Mangu Song ◽  
Yunfei Guo
Keyword(s):  
Software Defined Networking ◽  
Network Capacity ◽  
Reconfigurable Hardware ◽  
Software Implementation ◽  
Packet Processing ◽  
Evaluation Result ◽  
Processing Capability ◽  
Implementation Approach ◽  
Data Plane ◽  
Commercial Off The Shelf

Software-defined networking (SDN) has attracted much attention since it was proposed. The architecture of the SDN data plane is also evolving. To support the flexibility of the data plane, the software implementation approach is adopted. The software data plane of SDN is commonly implemented on a commercial off-the-shelf (COTS) server, executing an entire processing logic on a commodity CPU. With sharp increases in network capacity, CPU-based packet processing is overwhelmed. However, completely implementing the data plane on hardware weakens the flexibility. Therefore, hybrid implementation where a hardware device is adopted as the accelerator is proposed to balance the performance and flexibility. We propose an FPGA SmartNIC-based reconfigurable accelerator to offload some of the operation-intensive packet processing functions from the software data plane to reconfigurable hardware, thus improving the overall data plane performance while retaining flexibility. The accelerated software data plane has a powerful line-rate packet processing capability and flexible programmability at 100 Gbps and higher throughput. We offloaded a cached-rule table to the proposed accelerator and tested its performance with 100 GbE traffic. Compared with the software implementation, the evaluation result shows that the throughput can achieve a 600% improvement when processing small packets and a 100% increase in large packet processing, and the latency can be reduced by about 20× and 100×, respectively, when processing small packets and large packets.

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 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.

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