OpenFlow driven ethernet traffic analysis

Bianco, A.; Krishnamoorthi, V. Ram; Li, Nanfang; Giraudo, Luca

doi:10.1109/icc.2014.6883781

Cited by 8 publications

(5 citation statements)

References 6 publications

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“…In order to evenly balance the flows according to traffic patterns and link utiliza-tion, it is essential for a load balancing approach to obtain global network information. Combining with the centralized network architecture such as SDN [26], some mechanisms can use controller to collect global network information and assign flows to proper paths through the Openflow protocols [27]. However, these solutions lack scalability because the overhead of collecting information, computing paths and deploying paths makes them impractical to respond timely in large-scale networks.…”

Section: Related Workmentioning

confidence: 99%

A port-based forwarding load-balancing scheduling approach for cloud datacenter networks

2021

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Today’s datacenter networks (DCNs) scale is rapidly increasing because of the wide deployment of cloud services and the rapid rise of edge computing. The bandwidth consumption and cost of a DCN are growing sharply with the extensions of network size. Thus, how to keep the traffic balanced is a key and challenging issue. However, the traditional load balancing algorithms such as Equal-Cost Multi-Path routing (ECMP) are not suitable for high dynamic traffic in cloud DCNs. In this paper, we propose a port-based forwarding load balancing scheduling (PFLBS) approach for Fat-tree based DCNs with some new features which can overcome the disadvantages of the existing load balancing methods in the following aspects. Firstly, we define a port-based source-routing addressing scheme, which decreases the switch complexity and makes the table-lookup operation unnecessary. Secondly, based on this addressing scheme, we proposed an effective routing mechanism which can obtain multiple available paths for flow scheduling based in Fat-tree. All the path information is saved in servers and each server only needs to maintain its own path information. Thirdly, we propose an efficient algorithm to implement large flows scheduling dynamically in terms of current link utilization ratio. This method is suitable for cloud DCNs and edge computing, which can reduce the complexity of the switches and the power consumption of the whole network. The experiment results indicate that the PFLBS approach has better performance compared with the ECMP, Hedera and MPTCP approaches, which decreases the flow completion time and improves the average throughput significantly. PFLBS is simple and can be implemented with a few signaling overheads.

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Section: Related Workmentioning

confidence: 99%

A port-based forwarding load-balancing scheduling approach for cloud datacenter networks

2021

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“…All the management and control functions (routing, flow identification, QoS, etc.) are taken over by the OpenFlow controller, which has a global view of the network and configures the switches to forward packets on the basis of a specified flow definition [20,21]. With OpenFlow, load-balancing scheduling techniques are programmable and have received considerable attention.…”

Section: Software-defined Networking Schemesmentioning

confidence: 99%

ProMo: A Probabilistic Model for Dynamic Load-Balanced Scheduling of Data Flows in Cloud Systems

Souravlas

2019

Electronics

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An important issue in cloud computing is the balanced flow of big data centers, which usually transfer huge amounts of data. Thus, it is crucial to achieve dynamic, load-balanced data flow distributions that can take into account the possible change of states in the network. A number of scheduling techniques for achieving load balancing have therefore been proposed. To the best of my knowledge, there is no tool that can be used independently for different algorithms, in order to model the proposed system (network topology, linking and scheduling algorithm) and use its own probability-based parameters to test it for good balancing and scheduling performance. In this paper, a new, Probabilistic Model (ProMo) for data flows is proposed, which can be used independently with a number of techniques to test the most important parameters that determine good load balancing and scheduling performance in the network. In this work, ProMo is only used for testing with two well-known dynamic data flow scheduling schemes, and the experimental results verify the fact that it is indeed suitable for testing the performance of load-balanced scheduling algorithms.

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“…These values permit to properly plan the control network (for a given flow arrival rate) and to quantitatively evaluate the conditions under which the traffic overhead due to SDN can be considered negligible with respect to the data carried by the flow. If we consider an average flow size of 10-20 kB for the data as reported in [23,24], the overall control bandwidth is surprisingly large relatively to the amount of exchanged data and is mainly due to the reactive nature of the two applications. These results suggest that reactive applications in large POP networks should be avoided and provide an upper bound on the maximum amount of control traffic that any real application (which is supposed to act in a hybrid way between reactive and proactive behaviors) would generate.…”

Section: Evaluation Of Openflow Control Trafficmentioning

confidence: 99%

Scalability of ONOS reactive forwarding applications in ISP networks

Bianco

Giaccone

Mashayekhi

et al. 2017

Computer Communications

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Software Defined Networking (SDN) is a powerful approach that enhances network control and management, and provides a flexible way to develop network applications. However, scalability of SDN networks is an important concern for many network operators. The main peculiarities of SDN when applied to an Internet Service Provider (ISP) network are the large geographical extension and the need of in-band transmission of control traffic. Therefore, the control traffic exchanged between the SDN controller and the network nodes must be carefully evaluated for the network design and dimensioning. We consider an ISP network controlled by the recently ONOS (Open Network Operating System) controller developed by ON.Lab. We devise a quantitative model to compute the exact number of exchanged OpenFlow messages and the corresponding bandwidth needed to install a traffic flow when running the default ONOS layer-2 forwarding applications. We compute also the exact number of flow rules installed in each switch. We show the general applicability of our models for a Point Of Presence (POP) network and for a large set of real nationwide and worldwide ISP networks. Our quantitative models can be used for a safe network planning also when the network applications are not fully reactive.

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OpenFlow driven ethernet traffic analysis

Cited by 8 publications

References 6 publications

A port-based forwarding load-balancing scheduling approach for cloud datacenter networks

A port-based forwarding load-balancing scheduling approach for cloud datacenter networks

ProMo: A Probabilistic Model for Dynamic Load-Balanced Scheduling of Data Flows in Cloud Systems

Scalability of ONOS reactive forwarding applications in ISP networks

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