QoS-based distributed flow management in software defined ultra-dense networks

Bilen, Tuğçe; Ayvaz, Kübra; Canberk, Berk

doi:10.1016/j.adhoc.2018.05.002

Cited by 7 publications

(5 citation statements)

References 11 publications

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“…The average sojourn time and average queue length were used as the performance measures for evaluating the performance of the model. Also, Bilen, Ayvaz, and Canberk in [21]…”

Section: Modelling Based On M X /M/1 Distributionmentioning

confidence: 97%

Resilience Analysis of Software-Defined Networks Using Queueing Networks

Nweke

Wolthusen

2020

2020 International Conference on Computing, Networking and Communications (ICNC)

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Software-Defined Networks (SDN) are being adopted widely and are also likely to be deployed as the infrastructure of systems with critical real-time properties such as Industrial Control Systems (ICS). This raises the question of what security and performance guarantees can be given for the data plane of such critical systems and whether any control plane actions will adversely affect these guarantees, particularly for quality of service in real-time systems. In this paper we study the existing literature on the analysis of SDN using queueing networks and show ways in which models need to be extended to study attacks that are based on arrival rates and service time distributions of flows in SDN.

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“…The average sojourn time and average queue length were used as the performance measures for evaluating the performance of the model. Also, Bilen, Ayvaz, and Canberk in [21]…”

Section: Modelling Based On M X /M/1 Distributionmentioning

confidence: 97%

Resilience Analysis of Software-Defined Networks Using Queueing Networks

Nweke

Wolthusen

2020

2020 International Conference on Computing, Networking and Communications (ICNC)

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“…Research on SDVNs focuses on integrating and analyzing heterogeneous data for intelligent decision making. [148] Centralized SDUDN Queueing model Sood et al [40] Centralized CPU Utilization Queueing Model ravi et al [96] Centralized Packet Scheduling Queueing Model Mahmood et al [149] Centralized SDN-based VANETs QoS Resources ravi et al [3] Centralized Data Scheduling Queueing Model Liyanage et al [46] Hierarchical SDVN CPP kumar et al [150] Heterogeneous SD5GNet Queueing Model Ye et al [151] Heterogeneous VNF-5G core networks Queueing Model…”

Section: Work Conducted Reliability Utilization Delay Multi-hop Sdvn ...mentioning

confidence: 99%

Stochastic Modeling for Intelligent Software-Defined Vehicular Networks: A Survey

et al. 2023

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Digital twins and the Internet of Things (IoT) have gained significant research attention in recent years due to their potential advantages in various domains, and vehicular ad hoc networks (VANETs) are one such application. VANETs can provide a wide range of services for passengers and drivers, including safety, convenience, and information. The dynamic nature of these environments poses several challenges, including intermittent connectivity, quality of service (QoS), and heterogeneous applications. Combining intelligent technologies and software-defined networking (SDN) with VANETs (termed intelligent software-defined vehicular networks (iSDVNs)) meets these challenges. In this context, several types of research have been published, and we summarize their benefits and limitations. We also aim to survey stochastic modeling and performance analysis for iSDVNs and the uses of machine-learning algorithms through digital twin networks (DTNs), which are also part of iSDVNs. We first present a taxonomy of SDVN architectures based on their modes of operation. Next, we survey and classify the state-of-the-art iSDVN routing protocols, stochastic computations, and resource allocations. The evolution of SDN causes its complexity to increase, posing a significant challenge to efficient network management. Digital twins offer a promising solution to address these challenges. This paper explores the relationship between digital twins and SDN and also proposes a novel approach to improve network management in SDN environments by increasing digital twin capabilities. We analyze the pitfalls of these state-of-the-art iSDVN protocols and compare them using tables. Finally, we summarize several challenges faced by current iSDVNs and possible future directions to make iSDVNs autonomous.

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Section: Related Workmentioning

confidence: 99%

“…Queueing network models have also been used to study the behaviour of SDN in ultra dense network and satellite communication networks [5], [6]. The authors in [5] examine the use of SDN to ease the management of ultra dense data plane with distributed controllers. They propose a distributed flow management model based on queueing network model and characterize the distributed controllers by considering the flow characteristics and outage.…”

Section: Related Workmentioning

confidence: 99%

Modelling Adversarial Flow in Software-Defined Industrial Control Networks Using a Queueing Network Model

Nweke

Wolthusen

2020

2020 IEEE Conference on Communications and Network Security (CNS)

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In recent years, software defined networking (SDN) has been proposed for enhancing the security of industrial control networks. However, its ability to guarantee the quality of service (QoS) requirements of such networks in the presence of adversarial flow still needs to be investigated. Queueing theory and particularly queueing network models have long been employed to study the performance and QoS characteristics of networks. The latter appears to be particularly suitable to capture the behaviour of SDN owing to the dependencies between layers, planes and components in an SDN architecture. Also, several authors have used queueing network models to study the behaviour of different application of SDN architectures, but none of the existing works have considered the strong periodic network traffic in software-defined industrial control networks. In this paper, we propose a queueing network model for softwaredefined industrial control networks, taking into account the strong periodic patterns of the network traffic in the data plane. We derive the performance measures for the analytical model and apply the queueing network model to study the effect of adversarial flow in software-defined industrial control networks.

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QoS-based distributed flow management in software defined ultra-dense networks

Cited by 7 publications

References 11 publications

Resilience Analysis of Software-Defined Networks Using Queueing Networks

Resilience Analysis of Software-Defined Networks Using Queueing Networks

Stochastic Modeling for Intelligent Software-Defined Vehicular Networks: A Survey

Modelling Adversarial Flow in Software-Defined Industrial Control Networks Using a Queueing Network Model

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