The controller placement problem for wireless SDN

Dvir, Amit; Haddad, Yoram; Zilberman, Aviram

doi:10.1007/s11276-019-02077-5

Cited by 27 publications

(24 citation statements)

References 30 publications

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“…This, in return, increases the controller's control over the switches and the speed of data transmission [34]. Especially in software-based wireless network structures, the use of multiple controllers in a hierarchical structure and the position of the controller in the network decrease latency by optimising resource usage by increasing the supervision role of the controller over network elements located in the data layer [35].…”

Section: Datasetmentioning

confidence: 99%

Deep network approach with stacked sparse autoencoders in detection of DDoS attacks on SDN‐based VANET

2020

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Software-defined network (SDN)-based vehicular ad hoc network (VANET) is an outstanding technology for smart transportation as it increases traffic safety, efficiency, comfort, and manageability. However, despite all its benefits and good performance, SDN-based VANET is vulnerable to attack threats such as distributed denial of service (DDoS). When SDN-based VANET systems are exposed to DDoS attacks, this may affect traffic safety, causing traffic accidents and deaths. Therefore, the relevant security threats need to be addressed before integrating the SDN-based VANETs into smart transportation systems. In this study, the stacked sparse autoencoder (SSAE) + Softmax classifier deep network model is proposed to detect DDoS attacks targeting SDN-based VANETs. The features in the dataset obtained from the SDN-based VANET were reduced dimensionally utilising SSAE, and the most significant features were obtained. Then, these features were used as input into the Softmax classifier. According to the experimental results, the best accuracy scores were calculated as 96.9% using the four-layer SSAE + Softmax classifier deep network model proposed. When compared, the results demonstrate the SSAE + Softmax classifier deep network model proposed can obtain better results in the classification of DDoS attacks and is more successful than the other machine learning classifiers.

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Section: Datasetmentioning

confidence: 99%

Deep network approach with stacked sparse autoencoders in detection of DDoS attacks on SDN‐based VANET

2020

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“…The previous works in [9][10][11][12][13][14][15][16][17][18] focused on minimizing energy consumption or designing cost-effective controller placement strategies for SDN; however, it can be observed that the transmission delay or propagation delay between switches and controls may affect network performance significantly; thus, it is highly desired to design delay minimization-based controller placement strategy. The control plane delay between switches and controllers was considered in designing the optimal SDN controller placement strategy [19][20][21][22][23][24]. The authors in [19] studied the problem of placing controllers in SDN with wireless southbound interface.…”

Section: Delay Minimization-based Controller Placement Algorithmsmentioning

confidence: 99%

“…The control plane delay between switches and controllers was considered in designing the optimal SDN controller placement strategy [19][20][21][22][23][24]. The authors in [19] studied the problem of placing controllers in SDN with wireless southbound interface. To achieve low signaling transmission latency and link failure probability, a heuristic solution was proposed based on simulated annealing genetic algorithm.…”

Section: Delay Minimization-based Controller Placement Algorithmsmentioning

confidence: 99%

“…However, as a major performance metric characterizing service transmission performance, the signaling transmission delay should be considered when designing optimal controller placement strategies. While the signaling propagation delay between controllers and switches was mainly considered in [19][20][21][22][23][24], the inter-controller signaling transmission, which is mandatorily required for achieving controller synchronization over network states, failed to be considered extensively.…”

Section: Introductionmentioning

confidence: 99%

“…To achieve the efficient placement of the controllers, we design an SDN hierarchical management architecture based on which the proposed capacitated controller deployment scheme can be conducted. • While previous research work [19][20][21][22][23][24] aimed to achieve the minimum propagation delay between controllers and switches when designing controller placement strategy for SDN, they failed to examine extensively the inter-controller delay, the signaling transmission delay between controllers and switches, and the signaling processing delay at the controllers which may jointly affect the transmission performance of the user services severely. In this paper, we examine the control plane delay of SDN comprehensively; formulate it as a sum of the transmission delay and propagation delay between controllers and switches, the processing delay at the controllers, and the inter-controller delay; and design an effective capacitated controller placement strategy which minimizes control plane delay.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Control plane delay minimization-based capacitated controller placement algorithm for SDN

Chai

Yuan

Zhu

et al. 2019

J Wireless Com Network

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Software-defined networking (SDN) is proposed as a new network paradigm which decouples control plane from data plane and provides flexible network management. In this paper, we consider the capacitated controller placement problem in SDN, which jointly determines the number, location, and the capacity matching strategy of SDN controllers. redTo stress the importance of control plane delay which is composed of both the transmission and processing delay between controllers and switches, and the inter-controller delay; we formulate control plane delay minimization problem subject to controller-switch association constraints, controller capacity constraints, etc. Since the formulated optimization problem is a complicated nonlinear integer programming problem which cannot be solved easily, we transform it into controller-switch association subproblem and controller capacity matching subproblem. To solve the controller-switch association subproblem, we propose a heuristic algorithm based on Dijkstra algorithm and K-means algorithm. Given the controller-switch association strategy, we then apply the Kuhn-Munkres (K-M) algorithm to solve the controller capacity matching subproblem and obtain the capacitated controller placement strategy. Simulation results are shown to demonstrate the effectiveness of the proposed algorithm.

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Controller placement problem in software‐defined networking: A survey

Kumari

Sairam

2021

Networks

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A distinctive feature of software‐defined networking (SDN) is a logically centralized control plane realized using multiple physical controllers. The placement of the controllers, the so‐called controller placement problem (CPP), is a crucial design issue. It influences network performance parameters such as latency, flow setup time, network availability, load balance of the controllers, and energy consumption. In this article, we illustrate the formulation of these CPP objectives. We categorize the CPP design solutions as either static or adaptive. In adaptive CPP, the solutions proposed dynamically adapt to the number of controllers required and the switch to controller mapping to varying network traffic. We further differentiate adaptive CPP as wired or wireless. The optimization strategies adopted by the papers are analyzed and grouped into five categories: exact, heuristic, meta‐heuristic, clustering, and game theory. The merits and demerits of each approach are discussed. In conclusion, we outline the research challenges worth investigating.

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The controller placement problem for wireless SDN

Cited by 27 publications

References 30 publications

Deep network approach with stacked sparse autoencoders in detection of DDoS attacks on SDN‐based VANET

Deep network approach with stacked sparse autoencoders in detection of DDoS attacks on SDN‐based VANET

Control plane delay minimization-based capacitated controller placement algorithm for SDN

Controller placement problem in software‐defined networking: A survey

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