OpenFlow Switch Research Articles

Evaluation of Routing Performance using OSPF and Multi-Controller Based Network Architecture

Newer mobile applications are increasingly being defined using Internet Protocol, resulting in increased use of Internet Protocol and subsequent upsurge of smartphones. However, many communication service provider core networks continue to use classical routing protocols and single controller-based networks if deployed. Controller-based networks built on the foundation of software-defined networks include centralization and separation of control plane and data plane, which can address the challenges experienced with the classical routing protocols. When single controllers are used, they tend to get overloaded with traffic. The ability to use multi-controller-based network architecture to improve quality of service in the mobile IP core network is still an open issue. This paper presents a performance evaluation of multi-controller-based network architecture, running OpenFlow and Open Shortest Path First protocol. The long-term evolution simulated network architecture is created using well-known network simulator Objective Modular Network Testbed running OpenFlow and simuLTE add-on. We test and analyze data traffic for Packet data ratio and Jitter and their associated effects on a multi-controller-based network running OpenFlow versus OSPF on a mobile core network. The experiment created two topologies; multi controller-based and Open Shortest path first network. Video and ping traffic is tested by the generation of traffic from User Equipment to the network-based server in the data center and back, and traffic metrics recorded on an inbuilt integrated development environment. The simulation setup consisted of an OpenFlow controller, HyperFlow algorithm, OpenFlow switches, and Open Shortest Path First routers. The multi-controller-based network improved Jitter by 10 ms. The Open Shortest Path first showed packet data ratio values of 89% gain while the controller-based network registered a value of 86%. A standard deviation test revealed 0.7%, which shows that the difference is not significant when testing for Packet data ratio. We provided insight into the performance of multi-controller-based architecture and Open Shortest Path First protocol in the communication service provider's core network.

Diagnostic and troubleshooting of OpenFlow‐enabled switches using kernel and userspace traces

SummaryAlthough software‐defined networking (SDN) provides a flexible way to provision and control networks, it also makes network debugging and troubleshooting more complex. In SDN, the network is fully managed by software programs that increase flexibility and sophistication but are prone to bugs. Pinpointing those bugs is challenging because they can occur at multiple locations, such as the forwarding plane, the controller OS, and the network services running on top of the controller. Compared to functional bugs, performance bugs are particularly irritating due to their non‐failure semantics. They can lead to performance loss (reduced throughput, increased latency, and wasted resources) while maintaining the network connectivity. The literature reports several tools and techniques to diagnose SDN bugs, but, unfortunately, they are mostly ineffective against performance bugs. In this paper, we propose a novel monitoring and diagnostic framework capable of diagnosing performance bugs in the SDN data plane. The proposed tool works within Open vSwitch (OVS), a popular software switch, albeit it can easily be adapted to any OpenFlow switch. Tracing techniques are used to collect low‐level performance data from monitored switches. Our tool derives adapted performance metrics from kernel and userspace traces, and then displays them in time‐synchronized graphical views. These views provide valuable insights into OVS operation. They also enable practitioners to discover performance‐related issues and analyze their root causes. A few use cases are presented to demonstrate the efficiency of our tool in optimizing OVS performance and diagnosing its performance bugs.

RESEARCH OF SDN NETWORK PERFORMANCE PARAMETERS USING MININET NETWORK EMULATOR

Background. The implementation of the new modern services on existing networks requires replacement or modernization of the old equipment. This negatively affects the efficiency of providing users with new types of services and their cost. Therefore, the issues/tasks of implementing SDN technology in the construction of networks are in the center of attention of representatives of science-research organizations and telecom operators. SDN networks have the advantages of flexible scaling of the system without replacing existing server and network equipment, eliminating operator dependence on specific vendor solutions, and rapid implementation of the new network technologies and services. To determine the numerical values of indicators of the functioning of SDN networks and check their compliance with the requirements, it is proposed to use in working process simulation modelling. For these goals, the Open Networking Foundation consortium developed the Mininet network emulator, the elements of that are published publicly. The formation of the simulation model and the procedure for determining the performance indicators of the SDN network that uses Mininet has a number of features that are considered in the work.
 Objective. The purpose of the article is to build a simulation model based on the Mininet network emulator and to determine the performance indicators of SDN networks of various structures/topologies.
 Methods. Creation of a SDN network segment for testing process of its functioning in the overload mode of various communication routes.
 Results. The Mininet network emulator allows simulating SDN networks of a rather complex structure, change the performance of network branches and the amount of load in communication routes, to create a network-wide overload mode. During the simulation, it is possible to determine a number of indicators of network performance, such as the RTT (Round Trip Time) parameter for each route of communication, the bandwidth of branches and routes of communication, the amount of delay on network elements, loading of OpenFlow Switch ports/interfaces, network elements with the highest delay, the number of served and lost packets.
 Conclusions. Use of the Mininet network emulator is a fairly convenient tool for determining the performance indicators of SDN networks. However, there are also some problems. First of all, setting up the system's operability requires writing programs to ensure the interaction among standard elements from the Mininet library. Secondone, is when congestion occurs in the communication routes, the Floodlight Controller does not automatically balance traffic along the work-around route. This task has to be solved manually by making changes to the OpenFlow Switch routing tables.
 Keywords: Software Defined Networking; SDN; Mininet; OpenFlow; Floodlight Controller; OpenFlowSwitch; NFV; virtualization.

A proposal of port scan detection method based on Packet‐In Messages in OpenFlow networks and its evaluation

SummaryBy quickly detecting a port scan and blocking the culprit host from the network, it is possible to minimize the spread of the damage by infected hosts and malicious users. In the past, various Software‐Defined Networking (SDN)‐based methods have been proposed, whose main advantage is the lower overhead compared to traditional methods that collect and analyze all captured traffic. On the other hand, due to the polling process used in these methods, it is necessary to set a short interval (e.g., few seconds) to keep the attacks' detection as short as possible. However, when the attack frequency is very low compared to normal traffic, there is an unnecessary overhead. In this paper, we propose a port scan detection method that considers the characteristics of Packet‐In messages sent from the OpenFlow (OF) switch to the controller. This allows a prompt detection and with less overhead than conventional polling methods. The evaluation was conducted using both simulated and real traffic data. Results confirm that the proposed method can detect port scans with lower overhead than existing methods.

Implementation of Network Traffic Monitoring using Software Defined Networking Ryu Controller

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 Analysis of Load Balancing Algorithm Using Software- Defined Network

A data center is one of the secured space which serves as a house for many disks, switches, servers, routers, and several other hardware for a computer. It is a hardware solution for users who are present near the data center. Cloud Computing (CC) is the newer version of the data center which is capable of giving computer services to the users. Cloud service is the one which provides the users with data center set up when needed or preferred by the user themselves. In general cloud network service will be limited to a particular location or zone. In case if the target area of the user is near then the server will complete the action needed for the user. Only certain servers can provide service for the user in such cases some servers will remain idle. If the provided service by the servers is not used properly this may also lead to the issue of processing and managing a larger set of traffic which is one of the difficult tasks to perform. More network traffic may lead to giving more amount of pressure and complexity to the data center. In such a case Load Balancing (LB) is the preferred process for reducing the network failure and degradation process of the entire network. Software-defined networking is one the upcoming process which is capable of managing the entire network and also gives a general view about the network and its further configuration which needed to be upgraded. In this research paper, a software-defined network is developed for LB algorithms. In this paper, a Dynamic Server LB algorithm (Dserv- LB) is used for open-flow switches in the software-defined network system. This algorithm is one of the packet type LB algorithm. The request in the server is directly forwarded to the web-server with a higher level of server resources. From the result of the proposed algorithm, it was found that Dserv-LB is capable of improving the performance of the entire network and properly uses the server resource.

Concise Retrieval of Flow Statistics for Software-Defined Networks

Software-defined networking (SDN) provides a new network architecture by decoupling control and data planes. By performing the tasks of the control plane in a centralized manner, SDN enables the capability of programmability and flexibility to fulfill various types of network applications. The decoupling of control and data planes also brings additional messaging overhead and latency to degrade the efficiency of flow statistics collection, but timely and accurate flow statistics are critical for numerous SDN applications. In this article, we propose an effective scheme, <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">flow statistics retrieval using cookie</i> , to reduce the messaging overhead of acquiring traffic statistics from OpenFlow switches. Our scheme uses the cookie field of flow entries to designate a set of flows in a switch and avoid collecting flow statistics. Moreover, it provides the flexibility of assigning flow statistics retrieved from each switch to fulfill different requirements of messaging overhead. With the flexibility, we develop several algorithms of flow-statistics-to-switch assignment. The results of the performance evaluation show that our scheme can reduce both the messaging overhead and latency for retrieving flow statistics with only a few bits of the cookie field. The proposed algorithms can also balance the volume of flow statistics transmitted from a switch or minimize the transmission overhead.

Generation and collection of data for normal and conflicting flows in software defined network flow table

&lt;a name="_Hlk31039004"&gt;&lt;/a&gt;&lt;span lang="EN-US"&gt;In terms of network simplification and regulation, Software Defined Networking (SDN) is a new form of infrastructure that offers greater adaptability and flexibility. SDN, however, is an invention that is logically centralized. &lt;/span&gt;&lt;span&gt;In addition, the optimization of the control plane and data plane in SDN has become an area deserving of more attention. The flow in OpenFlow has been one of the essential parameters in the SDN standards, in which every individual flow includes packet matching fields, flow priority, separate counters, instructions for packet forwarding, flow timeouts and a cookie. This research work is conducted in order to produce and collect flows from the OpenFlow switch in two scenarios; in normal flows and when conflict policy rules are enforced in the network. In this article, the throughput is required to review and evaluate the conflict impact on two protocols as a performance metric; the Transmission Control Protocol (TCP) and the User Datagram Protocol (UDP) that flows via a forwarded plane. During the simulation of the SDN OpenFlow network, the metrics are tested using MININET. The results demonstrate that the existence of SDN conflict rules allows TCP and UDP to have a significant average change in bandwidth that eventually affects the network and operations performance.&lt;/span&gt;

DoS and DDoS attacks in Software Defined Networks: A survey of existing solutions and research challenges

Software Defined Networking (SDN) is a new networking paradigm where forwarding hardware is decoupled from control decisions. It promises to dramatically simplify network management and enable innovation and evolution. In SDN, network intelligence is logically centralized in software-based controllers (the control plane), while network devices (OpenFlow Switches) become simple packet-forwarding devices (the data plane) that can be programmed via an open interface (OpenFlow protocol). Such decoupling of the control plane from the data plane introduces various challenges that include security, reliability, load balancing, and traffic engineering. Dreadful security challenges in SDNs are denial of service (DoS) and distributed denial of service (DDoS) attacks. For instance, in SDNs, DoS/DDoS attacks could flood the control plane, the data plane, or the communication channel. Attacking the control plane could result in failure of the entire network, while attacking the data plane or the communication channel results in packet drop and network unavailability. In this paper we deliver several contributions that shed light on the field of DoS/DDoS attacks in SDNs, providing a complete background about the area, including attacks and analysis of the existing solutions. In particular, our contributions can be summarized as follow: we review and systematize the state-of-the-art solutions that address both DoS and DDoS attacks in SDNs through the lenses of intrinsic and extrinsic approaches. Moreover, the discussed countermeasures are organized accordingly to their focus, be it on detection, mitigation, prevention, or graceful degradation. Further, we survey the different approaches and tools adopted to implement the revised solutions. Finally, we also highlight possible future research directions to address DoS/DDoS attacks in SDNs.

A Proposed Adaptive Least Load Ratio Algorithm to Improve Resources Management in Software Defined Network OpenFlow Environment

So far, the existing load-balancing schemes (static and dynamic) have not taken over a concise and reasonable mechanism for systematic isolation of the resource counters monitored in the OpenFlow switch periodically. To address the aforementioned issue, the adaptive least load ratio algorithm was proposed and followed a straightforward procedure to generate the best possible decisions based on significant motivation characteristics identified in dynamic load balancing schemes like Least Connection-Based and Least Bandwidth-Based. the study was carried out using the HTTPerf tool as it provided a flexible facility for the generation of various HTTP workloads to evaluate server performance. Results revealed that, while Software defined network was under the influence of client requests load ranging from 0 up to 180 (req/sec), the proposed algorithm confirmed a faster server reply time up to 13.37%, server connection time up to 16.3% and average network throughput was improved up to 8%. Moreover, server CPU utilization time and average queue length were reduced to 2.5% and 14%. respectively. accordingly, and based on what the proposed algorithm has achieved in terms of quantitative performance parameters, it could be adopted in SDN-based data centers.

Emulating Software Defined Network using Mininet-ns3-WIFI Integration for Wireless Networks

SDN enables a new networking paradigm probable to improve system efficiency where complex networks are easily managed and controlled. SDN allows network virtualization and advance programmability for customizing the behaviour of networking devices with user defined features even at run time. SDN separates network control and data planes. Intelligently controlled network management and operation, such that routing is eliminated from forwarding elements (switches) while shifting the routing logic in a centralized module named SDN Controller. Mininet is Linux based network emulator which is cost effective for implementing SDN having in built support of OpenFlow switches. This paper presents practical implementation of Mininet with ns-3 using Wi-Fi. Previous results reported in literature were limited upto 512 nodes in Mininet. Tests are conducted in Mininet by varying number of nodes in two distinct scenarios based on scalability and resource capabilities of the host system. We presented a low cost and reliable method allowing scalability with authenticity of results in real time environment. Simulation results show a marked improvement in time required for creating a topology designed for 3 nodes with powerful resources i.e. only 0.077 sec and 4.512 sec with limited resources, however with 2047 nodes required time is 1623.547 sec for powerful resources and 4615.115 sec with less capable resources respectively.

Performance Evaluation of QoS metrics in Software Defined Networking using Ryu Controller

With assistance from Software Defined Networking (SDN), networks have become more creative to build and maintain over the last few years. The inflexibility of modern network architecture is presenting researchers with a tough achievement. SDN replaces existing inescapable and complicated networks with a creative way of separating the control plane from the data plane and fixing those constraints, namely configurations done manually, monitoring, protection, usability, and functionality. SDN controllers (e.g., POX, RYU, ONOS, OpenDaylight, Floodlight, etc.) have therefore developed as a core for the management of these networks. The performance evaluation of the SDN controller has an outstanding effect on improving the flexibilities and abilities of a network topology of SDN infrastructures. This research summarizes the SDN controller performance tests using criteria (e.g., Bandwidth, Round-Trip Time). This study employs a Mininet emulator to enforce an SDN architecture that comprises an RYU controller with a switching part, one OpenFlow switch, and multiple nodes. The goal is to determine performance QoS (Quality of Service) including Bandwidth, Throughput using the iperf test.

Securing industrial communication with software-defined networking.

Industrial Cyber-Physical Systems (CPSs) require flexible and tolerant communication networks to overcome commonly occurring security problems and denial-of-service such as links failure and networks congestion that might be due to direct or indirect network attacks. In this work, we take advantage of Software-defined networking (SDN) as an important networking paradigm that provide real-time fault resilience since it is capable of global network visibility and programmability. We consider OpenFlow as an SDN protocol that enables interaction between the SDN controller and forwarding plane of network devices. We employ multiple machine learning algorithms to enhance the decision making in the SDN controller. Integrating machine learning with network resilience solutions can effectively address the challenge of predicting and classifying network traffic and thus, providing real-time network resilience and higher security level. The aim is to address network resilience by proposing an intelligent recommender system that recommends paths in real-time based on predicting link failures and network congestions. We use statistical data of the network such as link propagation delay, the number of packets/bytes received and transmitted by each OpenFlow switch on a specific port. Different state-of-art machine learning models has been implemented such as logistic regression, K-nearest neighbors, support vector machine, and decision tree to train these models in normal state, links failure and congestion conditions. The models are evaluated on the Mininet emulation testbed and provide accuracies ranging from around 91-99% on the test data. The machine learning model with the highest accuracy is utilized in the intelligent recommender system of the SDN controller which helps in selecting resilient paths to achieve a better security and quality-of-service in the network. This real-time recommender system helps the controller to take reactive measures to improve network resilience and security by avoiding faulty paths during path discovery and establishment.

Efficient Topology Discovery for Software-Defined Networks

OpenFlow discovery protocol (OFDP) is the standard protocol for discovering network topologies for OpenFlow. Each controller generates and receives OFDP messages for each switch to yield a network topology. However, for a network with a large number of switches, the controller may suffer from high overhead to perform OFDP even though the network topology remains unchanged. In this article, we improve the efficiency of network topology discovery by implementing a delegated function in OpenFlow switches. Our mechanism can reduce controller’s overhead for topology discovery to shorten the time of discovering a network topology. It also provides with the interoperability with switches which only perform OFDP. The experimental results demonstrate that the proposed scheme can improve the time for discovering a new network topology by decreasing the number of messages. Our scheme also eliminates unnecessary Packet-Out and Packet-In messages when the network topology remains unchanged. As a result, the controller overhead, including CPU usage and traffic load, is greatly reduced to shorten the response latency of controllers. Hence, the proposed scheme improves the feasibility of achieving scalable OpenFlow networking.

OFaaS: OpenFlow Switch as a Service for Multi Tenant Slicing in SD-CDN

In Software Defined-Content Delivery Networks (SD-CDN), the policies of tenants such as Youtube, Netflix, Office 365, etc. are not the same due to having different 5G traffic requirements for such contents as enhanced Mobile Broadband (eMBB), ultra-reliable low-latency (URLLC) and massive machine-type communication (mMTC). This leads SD-CDN multi-tenant slicing to provide different services with limited network resources, where each tenant can functionally manage their own virtual slice of a physical component according to service level agreements (SLAs). However, they are not permitted to dynamically configure their own components. Therefore, the physical end-to-end configuration of all edge devices causes extra hardware and bandwidth costs. Although software as a service (SaaS) is more preferred to handle cost-efficiency on a switch configuration that increases forwarding throughput (Mbps) with a less number of physical components in SD-CDN, the edge devices can be only served as infrastructure as a service (IaaS) currently. This motivation leads us to serve the switch as a service that includes both IaaS and SaaS characteristics. Therefore, we propose an OpenFlow as a service (OFaaS) design where each tenant has flow management and switch configuration permissions on their own virtual slice. In flow management, we define a novel Service Oriented Architecture (SOA) to orchestrate OFaaS driven topology by isolating each tenant from physical complexity. Here, each tenant can dynamically alter QoS on a flow and load balance between a sub-set of contents via OpenFlow protocol. In switch configuration; a novel OFaaS Management Algorithm for a multi-tenant slicing increases the number of tenants served per OpenFlow switch thanks to OFaaS design. It enables an end-to-end configuration via the NETCONF protocol with a novel YANG model of OFaaS. According to performance evaluation; OFaaS has the same forwarding throughput as conventional IaaS based OpenFlow switch for a homogenous content, whereas it has 71% more forwarding throughput (Mbps) and it has 40% more cost-efficient than conventional one for a heterogeneous content with $17 savings per tenant.

Route manipulation aware Software-Defined Networks for effective routing in SDN controlled MANET by Disney Routing Protocol

• The Proposed scheme helps to find the optimal routing with a secure and intelligent manner • Proposed method achieves a better ratio for packet transmission delay • Route manipulation matrix helps to find the intruder free communication toward the different nodes In MANET network management, the Software-Defined Networking (SDN) plays a vital role in terms of controller plane and data plane. It is always easy to manage the data communication over the MANET because of logically centralized control on the SDN. Since the dynamic route on MANET, are controls the packets and changes the route between the source to destination alternatively. Hence the maintenance of real-time SDN analysis-based application planes is a crucial process. To maintain the effective MANET communication over the Software-Defined Network, it essential to improve the control and data plane process on the SDN controlled MANET based OpenFlow switching procedure. Nevertheless, SDN allows for route interaction against security threads. In this research article, the four stages were suggested to preserve the security measures in packet-based data transmission that are conceived in MANET. In this article, an SDN controlled MANET based OpenFlow switching scenario for effective security threading is proposed. The major part played by an SDN controlled MANET in bringing about a result of being effective without wasting time and energy on routing. The proposed Distinct Network Yarning (DISNEY) routing protocol for SDN controlled MANET overcomes the congestion communication on MANET routing. To decrease performance degradation, efficient routing is maintained by the route matrix manipulation table. This routing scheme helps to find the optimal routing with a secure and intelligent manner. The proposed result was compared to existing approaches. As a result, the proposed illustration to be improved by routing and data transmission. In comparison to the proposed method achieves a better ratio for packet transmission delay, throughput, and data transmission rate.

Enhancing Blockchain security in cloud computing with IoT environment using ECIES and cryptography hash algorithm

Blockchain is one of the fast growing technologies that has significant role in the area of criminal investigation. The security is becoming a great threat to all the industries, Electronic Health Record(EHR), Banking, Smart Applications (SA), Supply Chain Management (SCM) and IoT environment in recent years. In this research, we have developed a novel framework that will monitor the activities that takes place on particular data evidence, We create a Cloud based Software Defined Network (SDN), its consists of 100 - mobile Nodes (IOT devices), open flow switch and Blockchain based controllers, cloud server, Authentication Server (AS) and investigator. Initially all users are registered with AS and obtain their secret key from AS based on the Harmony Search Optimization (HSO). In the mobile nodes the packets are encrypted by usingElliptic CurveIntegrated Encryption Scheme (ECIES) algorithm and transfer to the cloud server. SDN controller maintains blockchain to preserve evidences collected from data and signature of the users based on the SHA-256 Cryptographic Hash Algorithm. Authorized investigator performs following processes: identification, evidence collection, evidence analysis, and report generation based on the Logical Graph of Evidences (LGoE). we plot the resultant graph for Response time versus Number of users, Evidence insertion time versus number of users, Evidence verification time versus Number of users, Computational overhead versus number of users, Total change rate versus Number of users, Hash computation time versus number of users, Key generation time versus number of users, Encryption time versus number of users and Decryption time versus number of users. Finally, the investigator or other legal people can obtain the evidences from the controller and construct as a Logical Graph of Evidence (LGoE). The experimental analysis revealed the fact that the proposed system obtained better performance in terms of response time, accuracy, increasing throughput and total change security parameters.

Impact of TCAM size on power efficiency in a network of OpenFlow switches

Recent developments in networking include the interest in software-defined networking, in which OpenFlow switches are in charge of forwarding traffic by matching incoming packets with forwarding rules in their flow tables. Flow tables are commonly implemented in ternary content addressable memories (TCAMs). Typically, this type of memory tends to be extremely expensive and to be power-hungry devices. The price and power dissipation of TCAM depend on the capacity of the memory. A blind design of memory size can result in dramatic degradation in performance and power efficiency of the entire network. In this study, the authors clarify this impact and show how the optimum value of TCAM capacity is attainable. They also propose a power consumption model for TCAM-based OpenFlow switches. Simulation results show that the proposed solution reduces the average power consumption by 24% compared to the minimum link on method and by 11.5% compared to the minimum node on (MNO) method and thus power efficiency is better achieved when each memory is supplied by appropriate TCAM size.

QoSComm: A Data Flow Allocation Strategy among SDN-Based Data Centers for IoT Big Data Analytics

When Internet of Things (IoT) big data analytics (BDA) require to transfer data streams among software defined network (SDN)-based distributed data centers, the data flow forwarding in the communication network is typically done by an SDN controller using a traditional shortest path algorithm or just considering bandwidth requirements by the applications. In BDA, this scheme could affect their performance resulting in a longer job completion time because additional metrics were not considered, such as end-to-end delay, jitter, and packet loss rate in the data transfer path. These metrics are quality of service (QoS) parameters in the communication network. This research proposes a solution called QoSComm, an SDN strategy to allocate QoS-based data flows for BDA running across distributed data centers to minimize their job completion time. QoSComm operates in two phases: (i) based on the current communication network conditions, it calculates the feasible paths for each data center using a multi-objective optimization method; (ii) it distributes the resultant paths among data centers configuring their openflow Switches (OFS) dynamically. Simulation results show that QoSComm can improve BDA job completion time by an average of 18%.

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

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.