A survey of low-latency transmission strategies in software defined networking

Czachórski

2021

Sensors

The increasing use of Software-Defined Networks brings the need for their performance analysis and detailed analytical and numerical models of them. The primary element of such research is a model of a SDN switch. This model should take into account non-Poisson traffic and general distributions of service times. Because of frequent changes in SDN flows, it should also analyze transient states of the queues. The method of diffusion approximation can meet these requirements. We present here a diffusion approximation of priority queues and apply it to build a more detailed model of SDN switch where packets returned by the central controller have higher priority than other packets.

Section: Introduction and An Overview Of Existing Resultsmentioning

confidence: 99%

Diffusion Model of Preemptive-Resume Priority Systems and Its Application to Performance Evaluation of SDN Switches

Czachórski

2021

Sensors

Journal of Electrical and Computer Engineering

“…Furthermore, a network can grow so that numerous fow setup requests from many switches become a source of performance bottlenecks. Tis is because the number of fow setup requests is directly proportional to the number of switches, implying that the overall cost to confgure a fow route for n-switches concerning network load is about 94 + 144 N. Te authors in [28] report that a large network can have switches that can generate up to 10 million fow requests per second. Tis is beyond the capacity of a single controller, as some controllers can only accommodate 6000 fow requests per second [13].…”

Section: Scalability and Overheadmentioning

confidence: 99%

Distributed Controller Placement in Software-Defined Networks with Consistency and Interoperability Problems

Yusuf

Bakar

Isyaku

et al. 2023

Software-defined networking (SDN) brings an innovative approach to networking by adopting a flow-centric model and removing networking decisions from the data plane to provide them centrally from the control plane. A single centralized controller is used in a traditional SDN design. However, the complexity of modern networks, due to their size and requirements’ coarseness, has made using a single controller a source of performance bottlenecks. Similarly, the solution found by using multiple controllers in distributed control planes brings forth the profound issue of interoperability, consistency, and the “controller placement problem” (CPP). It is an NP-hard problem that deals with positioning controllers at optimum locations within the network and mapping with resources at the data plane to meet quality of service (QoS) requirements. Over the years, the problem has received significant attention from the research community, and many solutions have been considered. This paper offers an in-depth review of the proposals by providing an updated evolution of the problem concerning the application environment, design objectives, and cost and controller type. Based on our findings, new research ideas were identified and discussed.

“…Through the above analysis, it is easy to notice that whether the statistics uploaded by the switch to the controller are correct or not can seriously affect the judgment of the controller. Without the correct input, other schemes such as low latency transmission 22 and switch migration 23 deployed in control plane will not work properly. Therefore, it is very important that data plane sends the correct statistics to control plane.…”

Section: Motivationmentioning

confidence: 99%

Audit‐based correction mechanism for malicious statistics information of data plane

et al. 2023

Self Cite

Summary In software‐defined networking (SDN), the controller relies on the information collected from the data plane for route planning, load balancing, and other functions. Statistics information is the most important kind of information among them, so the correctness of statistics information is the key to the proper operation of the network. Most of the current research on data plane focuses on policy consistency, rule redundancy, forwarding anomalies, and so on, and little attention is paid to whether the statistics information uploaded by the switches to the controller is correct. However, incorrect statistics information inevitably leads the controller to make wrong decisions. Therefore, this paper proposes an audit‐based malicious information correction mechanism to address the problem of wrong statistics information uploaded by the switches. This mechanism audits the statistics information and locates malicious switches before uploading the statistics information to the controller. It identifies and corrects the statistics information errors by combining flow path and statistics information. We have performed simulations on Nsfnet, Abilene, and Fat‐Tree, and the results show that our method can correct about 70% of the statistical information errors with less computational cost. To the best of our knowledge, this paper is the first malicious statistics information correction scheme for wildcard rules.