SDN Network Research Articles

Optimizing the Response Time in SDN-Fog Environments for Time-Strict IoT Applications

The rise of the Internet of Things (IoT) has opened new research lines that focus on applying IoT applications to domains further beyond basic user-grade applications, such as Industry or Healthcare. These domains demand a very high Quality of Service (QoS), mainly a very short response time. In order to meet these demands, some works are evaluating how to modularize and deploy IoT applications in different nodes of the infrastructure (edge, fog, cloud), as well as how to place the network controllers, since these decisions affect the response time of the application. Some works in the literature have approached this problem by providing separate plans for deployment and placing of controllers. However, this approach makes sub-optimal decisions, that complicate guaranteeing the demanded response time. To guarantee an optimal response time, it is crucial to solve the problem in a single effort that considers both, the networking and computing dimensions. In this work, we analyze the influences between the response time of computing and networking in edge computing environments with SDN networks, merging both optimization efforts into a single one and proposing a solution to the joint problem. Our evaluation shows that our proposal can shorten response time by up to 28.97%

Multipath resilient routing for endogenous secure software defined networks

SDN improves the flexibility and programmability of the network. However, malicious attacks caused by potential vulnerabilities and backdoors can easily lead to data and rule tampering in the network. To address this problem, this paper proposes an endogenous secure SDN network framework based on multipath resilient routing (MRR). MRR includes multipath comparing forwarding, multipath weighted forwarding, and multipath random forwarding. The framework ensures the correctness of flow rules and data content by dynamically comparing the consistency of multi-heterogeneous path data within a certain period, and multipath can also achieve load balance by weighted forwarding. In the MRR framework, we also present an intermediate information feedback mechanism based on encryption authentication and give a mathematical model to evaluate it. This mechanism can accurately identify and dynamically repair malicious switches. Simulation evaluation and prototype system test show that this framework can achieve high accuracy of flow transmission and high availability of system. At the same time, multipath comparing forwarding will bring some performance costs such as delay, bandwidth, and jitter at initial and attacking time. However, when the appropriate forwarding mode and reasonable period T are selected, the proportion of delay introduced by comparing and ruling can be less than 10%, and the average bandwidth of mixed forwarding is almost the same as traditional multipaths', such as we can guarantee 25% multipath comparing forwarding when the bandwidth requirement is 250 M in prototype system.

Encrypted Network Traffic Classification and Resource Allocation with Deep Learning in Software Defined Network

The climate has changed absolutely in every area in just a few years as digitized, making high-speed internet service a significant need in the future. Future Internet is supposed to face exponential growth in traffic, and highly complicated infrastructure, threatening to make conventional NTC approaches unreliable and even counterproductive. In recent days, AI Stimulated state-of-the-art breakthroughs with the ability to tackle extensive and multifarious challenges, and the network community is initiated by considering the NTC prototype from legacy rule-based towards a novel AI-based. Design and execution are applied to interdisciplinary become more essential. A smart home network supports various applications and smart devices within the proposed work, including e-health devices, regular computing devices, and home automation devices. Many devices accessible through the Internet by Home GateWay for Congestion (HGC) in a smart home. Throughout this paper, a Software-Defined Network Home GateWay for Congestion (SDNHGC) architecture for improved management of remote smart home networks and protection of the significant network's SDN controller. It enables effective network capacity regulation, focused on real-time traffic analysis and core network resource allocation. It cannot control the Network in dispersed smart homes. Our innovative SDNHGC expands power across the connectivity network, a smart home network enabling improved end-to-end monitoring of networks. The planned SDNHGC directly will gain centralized device identification by classifying traffic through a smart home network. Several of the current traffic classifications approach, checking deep packets, cannot have this real-time device knowledge for encrypted data to solve this issue.

Analysis of promising approaches and research on traffic flow classification for maintaining QoS by ML methods in SDN networks

One of the most important tasks that exist in modern networks is to maintain the Quality-of-Service QoS at the appropriate level which can be achieved by applying various traffic management mechanisms. In order to maintain the QoS parameters in the proper state, you need to know the types of traffic passing through the network. Given high-tech and high-performance networks such as SDN networks, traffic classification by conventional methods becomes almost impossible. Data mining methods, including Machine Learning methods, come to the rescue. The article analyzes the main promising approaches to real-time traffic classification for maintaining QoS in SDN networks by ML methods as well as provides a comparative overview of the most outstanding works in this field.

A Hybrid Mechanism to Detect DDoS Attacks in Software Defined Networks

DDoS (Distributed Denial-of-Service) attacks are among the cyberattacks that are increasing day by day and have caused problems for computer network servers. With the advent of SDN networks, they are not immune to these attacks, and due to the software-centric nature of these networks, this type of attack can be much more difficult for them, ignoring effective parameters such as port and Source IP in detecting attacks, providing costly solutions which are effective in increasing CPU load, and low accuracy in detecting attacks are of the problems of previously presented methods in detecting DDoS attacks. Given the importance of this issue,the purpose of this paper is to increase the accuracy of DDoS attack detection using the second order correlation coefficient technique based on ∅-entropy according to source IP and selection of optimal features.To select the best features, by examining the types of feature selection algorithms and search methods, the WrapperSubsetEval feature selection algorithm, the BestFirst search method, and the best effective features were selected. This study was performed on CTU-13 and ISOT datasets and the results were compared with other methods. The accuracy of the detection in this work indicates the high efficiency of the proposed approach compared to other similar methods.  

EHDDP: Enhanced Hybrid Domain Discovery Protocol for network topologies with both wired/wireless and SDN/non-SDN devices

Handling efficiently both wired and/or wireless devices in SDN networks is still an open issue. eHDDP comes as an enhanced version of the Hybrid Domain Discovery Protocol (HDDP) that allows the SDN control plane to discover and manage hybrid topologies composed by both SDN and non-SDN devices with wired and/or wireless interfaces, thus opening a path for the integration of IoT and SDN networks. Moreover, the proposal is also able to detect both unidirectional and bidirectional links between wireless devices. eHDDP has been thoroughly evaluated in different scenarios and exhibits good scalability properties since the number of required messages is proportional to the number of existing links in the network topology. Moreover, the obtained discovery and processing times give the opportunity to support scenarios with low mobility devices since the discovery times are in the range of hundreds of milliseconds.

Resilient Control Plane Design for Virtual Software Defined Networks

Control plane survivability in virtual software-defined networks (vSDN) – where multiple tenants share the same physical infrastructure – is even more critical than in normal SDN networks. A reliable communication channel from the switches through the network hypervisor to the virtual controller is inevitable in order to avoid state inconsistencies, tenant isolation and security issues on the virtual switches. Although reliable controller placement and control plane design was thoroughly investigated in SDNs, there was a lack of attention for resilient hypervisor placement and control path design for vSDNs. Therefore, in this paper we make a two-fold contribution towards a survivable vSDN control plane. First, we propose an approximation algorithm for (hypervisor) placement which – in contrast with traditional approaches which minimize the average latency to the hypervisors as an objective function – focuses on finding the appropriate number of hypervisor instances to satisfy the control path length constraints declared in the service level agreements, leaving enough options open for self-driving network designs and intelligent algorithms. Second, we propose a general dynamic program that calculates minimum length paths traversing specific type of nodes in a given order, and apply it to find control paths from the virtual controller of the slice to the virtual switches traversing the corresponding hypervisor location. We conduct thorough simulations on real-world topologies to demonstrate the effectiveness of our approaches in no failure and single link failure scenarios.

Enhanced Routing Schedule - Imbalanced Classification Algorithm for IOT based Software Defined Networks

Route scheduling optimization is important in SDN network. The SDN network needs the best solution for route optimization. Limited networking of software is the most interesting development in this field as it is important to provide a fast and reliable routing path based on its need. The IoT supports software defined applications interface in the overall networks. The SDN is recommended by enhancing the SDN architecture's benefits in improving research network quality. SDN network information exchange is one of the most important factor. It is important to plan the information accordingly and adjust a load of information to the SDN. A Maximum throughput scheduling process is proposed, which is upgraded using the Imbalanced Classification Algorithm. SDN has shown the advantage in many ways compared to the traditional network. But the problem of load inconstancy still occurs in SDN. The imbalanced classification method supports the maximum throughput schedule function and integrates load balancing strategies to improve SDN networks' Performance. Classification is to be proposed based on machine command in QoS. An imbalanced classification learning method is used for improving the QoS requirements and shows that the simulated results of the identified traffic load balance and maximum throughputs in the proposed solutions. Functionality has been improved much better than previous functions in the same area.

Network Management in Software-Defined Network: A Survey

SDNs are developed networks that focus on the separation of control aircraft and data. This new model is designed to simplify network management and enable research innovations. It explains the traditional system of SDNs and issues related to the traditional system. This paper explains the background of SDN technology and architecture. At the end of the research, SDN enhances scalability, flexibility, reliability, high availability, security and performance. This paper has tried to simplify and explain every problem with the SDN network and provided an overview of the SDN network general structure, the basics of network management in SDN, and the main challenges in SDN.

Distrinet

Networks have become complex systems that combine various concepts, techniques, and technologies. As a consequence, modelling or simulating them now is extremely complicated and researchers massively resort to prototyping techniques. Mininet is the most popular tool when it comes to evaluate SDN propositions. Mininet allows to emulate SDN networks on a single computer but shows its limitations with resource intensive experiments as the emulating host may become overloaded. To tackle this issue, we propose Distrinet , a distributed implementation of Mininet over multiple hosts, based on LXD/LXC, Ansible, and VXLAN tunnels. Distrinet uses the same API than Mininet, meaning that it is compatible with Mininet programs. It is generic and can deploy experiments on Linux clusters (e.g., Grid'5000), as well as on the Amazon EC2 cloud platform.

A Table Overflow LDoS Attack Defending Mechanism in Software-Defined Networks

In order to achieve requirements such as fast search of flow entries and mask matching, OpenFlow hardware switches usually use TCAM to store flow entries. Limited by the capacity of TCAM, the current commercial OpenFlow switches can only support hundreds of thousands of flow entries, which makes SDN network using OpenFlow hardware switches vulnerable to the threat of flow table overflow attack. Among them, low-rate DoS (LDoS) attack against table overflow poses a serious threat to SDN networks due to its high attack efficiency and concealed flow, and it is also difficult to detect. In this regard, this paper analyzed two types of LDoS attack flow against table overflow and proposed an attack detection and defense mechanism named SAIA (Small-flow Analysis and Inport-flow Analysis) through the design of table overflow prediction and flow entries deletion strategy. Experiments conducted through the SDN network environment showed that SAIA can effectively detect and suppress LDoS attack flows in the flow table in large-scale network conditions and verified that the deployment of SAIA is lightweight. At the same time, SAIA implemented the flow entry deletion strategy based on LRU when the flow table overflows in a nonattack situation, which further enhances the stability of the network.

Method for Overflow Attack Defense of SDN Network Flow Table Based on Stochastic Differential Equation

In order to avoid the overflow problem of network flow table caused by hackers attacking the network in the process of using the network, a method for overflow attack defense of SDN network flow table based on stochastic differential equation is proposed. In this method, the stochastic differential equation is first proposed, and the drift coefficient and diffusion coefficient of the equation are expanded and adjusted by Taylor. By using the limit theorem, the spillover attack of SDN network is weakly converged to an approximate two-dimensional Markov diffusion process, and the improved stochastic differential equation is obtained. Then, according to the stochastic nature of SDN network attack, the stochastic differential equation is transformed into an amplitude equation, which is based on the amplitude. The equation establishes a SDN attack detection scheme based on flow table statistics, which detects the spillover attacks of SDN network flow tables. Finally, according to the test results, it is proposed to use other switches instead of network flow table overflow switches to control the data upload rate, thus reducing the possibility of network crash and meeting the attack defense requirements of flow table overflow. The simulation results show that the proposed method has better detection performance and shorter running time, and can provide help for network security related work.

An Approach to Improve the Quality of Service in DTN and Non-DTN based VANET

Nowadays, with attention to soar in the number of network users, it is necessary to find new approaches to revolutionize network operation. Vehicular ad-hoc networks are bound to play a pivotal role in communication, therefore raising the traffic in the network, using only WiFi is unlikely to address this problem. Vehicles could use SDN and other networks such as 4G as well as 5G to distribute traffic to different networks. Moreover, many approaches for handling different data types are inappropriate due to the lack of attention to the data separation idea. In this paper, we proposed a control scheme called Improve Quality of Service in DTN and Non-DTN (IQDN) which works based on vehicle communication infrastructure using SDN idea. IQDN separates data to Delay-Tolerant Data (DTD), and Delay-Intolerant Data (DID) where the former buffers in a vehicle till the vehicle enters an RSU range and sends DTD using IEEE 802.11p. DID packets are sent by cellular networks and LTE. To transmit DTD via IEEE 802.11p, the network capacity is evaluated by SDN. If that network has room to transmit the data, SDN sends a control message to inform the vehicle. Simulations show that sending data over RSU and LTE increases the throughput and decreases the congestion, so the quality of service improves.

Automatic repair of pollution attacks in SDN topology network based on SOM algorithm

When using the current method to recover the vulnerabilities caused by pollution attacks in SDN network, there are some problems, such as low coverage, low accuracy of vulnerability detection results and low repair efficiency. To this end, an automatic repair method for topology pollution attacks in SDN network based on SOM algorithm is proposed. This paper analyses the security vulnerabilities in SDN architecture and SDN network, and extracts the attack flow characteristics of topology pollution attacks in SDN network. The extracted attack flow features are input into SOM algorithm to detect and identify vulnerabilities caused by pollution attacks. Combining the theory of vertex concavity and convexity and geometric triangle, the detected vulnerabilities are repaired to realise the automatic repair of topology pollution attacks in SDN network. The experimental results show that the proposed method has high coverage, high accuracy of vulnerability detection and high efficiency of vulnerability repair.

Energy savings in SDN networks

Energy savings in SDN networks

Dynamic quality of service for different flow types in SDN networks

Dynamic quality of service for different flow types in SDN networks

Machine learning in SDN networks for secure industrial cyber physical systems: a case of detecting link flooding attack

Machine learning in SDN networks for secure industrial cyber physical systems: a case of detecting link flooding attack

СУЧАСНА ІНФРАСТРУКТУРА КОМУНІКАЦІЙНИХ ТЕХНОЛОГІЙ У БІЗНЕС-СЕРЕДОВИЩІ: МОДЕЛЮВАННЯ МЕТОДУ «ЖИВОЇ МІГРАЦІЇ»

In order to meet data and service requirements, network operators are constantly expanding and improving their network infrastructure, resulting in increased capital and operating costs. However, due to intense competition and falling prices, the average income per user does not increase proportionally, which leads to a decrease in return on investment. Thus, to reduce costs and increase revenue, mobile networks need to make the next evolutionary leap towards 5G, which now applies not only to the mobile border, but also to the core network. The 5G micro-operator service architecture must also be developed together with various technologies such as SDN and NFV. SDN abstracts network architecture by separating network management and redirection functions, allowing network management to become directly programmable and the underlying infrastructure to be abstracted for applications and network services. The interaction between SDN and NFV allows the 5G network to abstractly build the system infrastructure and further increase network flexibility. Therefore, the article substantiates the possibility of market commercialization of the use of technologies of live migration of traffic flow, which allows to give the product unique characteristics. The existing approaches to the solution of the problem of load balancing of the network of 5G micro operators are analyzed. A number of advantages of the live migration method have been identified, namely the possibility of its application for the micro operator's network and efficient use of network resources. According to the results of the experiment, it was found that the method of live migration has better values µO_num (68.1% of traffic flow) than the mechanism of MLF (29.8% of traffic flow). It is proved that the mechanism of live migration can determine the priority of the user traffic flow according to the servers in the zone µO, and therefore it is expedient to apply in terms of optimizing the distribution of traffic flow. The proposed method should increase the utilization of network resources and traffic flow efficiency and lead to a higher level of experience quality (QoE) for network users.

Research on the on-demand scheduling algorithm of intelligent routing load based on SDN

Aiming at the traditional on-demand scheduling method of routing load, there are many problems, such as long time to complete the total task and high energy consumption. An on-demand scheduling method of routing load based on multiple SINKs is proposed. The total routing load task is sent from multiple SINK nodes to SDN network. After receiving the sub-tasks sent by SINK, the intra-cluster nodes begin to collect network data together. After the cluster heads fuse the network data transmitted by the nodes, the results are sent to SINK nodes. As a result, the shortest total task completion time is obtained, and the shortest total task completion time is used as the objective function of routing load scheduling on demand. Ant colony algorithm is used to solve the problem and complete the scheduling. Experimental results show that the proposed method has shorter completion time and lower energy consumption of total task.

The Influence of Failover on Software-Defined Network and Conventional Network

The growing use of the Internet resulted in the number of agencies that use two or more internet gateway paths or so-called Internet Service Providers (ISPs) to maintain network availability. Using two or more gateway paths allows break-up of connections on one of the gateway paths. This study aims to determine the effect of failover on SDN and conventional networks that are integrated with load balancing method of ECMP on MikroTik RB951-2n router device. The controller used on the SDN network is OpenDaylight. Testing is done by doing failover test which then data of bandwidth traffic from both network architecture recorded using Graphing tool from MikroTik. For average traffic efficiency without failover influence on conventional network better with difference of 9.8%. And with the difference in efficiency of 0.5% menunujukkan that the effect of failover on the SDN network is still better than the conventional network.