A density algorithm for controller placement problem in software defined wide area networks

He, Dun; Chen, Jue; Qiu, Xihe

doi:10.1007/s11227-022-04873-x

Cited by 4 publications

(4 citation statements)

References 39 publications

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“…Numerous research endeavors have delved into the intricacies of the SDN CPP and the associated node-controller assignment problem. These investigations initially explored the CPP in the context of wired networks design [4]- [10], [24]- [27], with emphasis on facility location analysis.…”

Section: Literature Reviewmentioning

confidence: 99%

“…The majority of CPP research has focused on minimizing the controller deployment cost while achieving low latency [4], [6], [7], [9], [13], [14], [16], [17], [24]- [27], [29]. Other works expanded their scope to include load balancing among distributed controllers and considerations of computational and storage power [6], [7], [13], [14], [16], [17], [25], [26].…”

Section: Literature Reviewmentioning

confidence: 99%

“…These CPPs were often formulated based on the analysis of facility location problems and their variants, including k-median (k-center) problems [4], [5], [8], [25], [29], capacitated facility location problems, and set covering problems [6], [7]. Additionally, Pareto optimal multiobjective optimization [9], [17], fault-tolerant facility location problems (k-terminal network reliability problem) [10], bin packing problems [13], k-means graph clustering [24], constraint covering graphs [26], integer linear optimization problems [16], [27], and two-stage joint optimization [14], [15], [31] have been employed for CPP formulations.…”

Section: Literature Reviewmentioning

confidence: 99%

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On Robust Optimal Joint Deployment and Assignment of RAN Intelligent Controllers in O-RANs

Abdel-Rahman,

Mazied,

Hassan

et al. 2024

IEEE Open J. Commun. Soc.

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The open radio access network (O-RAN) architecture is consolidating the concept of softwaredefined cellular networks beyond 5G networks, mainly through the introduction of the near-real-time radio access network (RAN) intelligent controller (Near-RT RIC) and the xApps. The deployment of the Near-RT RICs and the assignment of RAN nodes to the deployed RICs play a crucial role in optimizing the performance of O-RANs. In this paper, we develop a robust optimization framework for joint RIC deployment and assignment, considering the uncertainty in user locations. Specifically, our contributions are as follows. First, we develop C 3 P 2 , a robust static joint RIC placement and RAN node-RIC assignment scheme. The objective of C 3 P 2 is to minimize the number of RICs needed to control all RAN nodes while ensuring that the response time to each RAN node will not exceed δ milliseconds with a probability greater than β. Second, we develop CPPA, a robust joint RIC placement and adaptive RAN node-RIC assignment scheme. In contrast to C 3 P 2 , CPPA enjoys a recourse capability, where the RAN node-RIC assignment adapts to the variations in the user locations. We use chance-constrained stochastic optimization combined with several linearization techniques to develop a mixed-integer linear (MIL) formulation for C 3 P 2 . Two-stage stochastic optimization with recourse, combined with several linearization techniques, is used to develop an MIL formulation for CPPA. The optimal performance of C 3 P 2 and CPPA has been examined under various system parameter values. Furthermore, sample average approximation has been employed to design efficient approximate algorithms for solving C 3 P 2 and CPPA. Our results demonstrate the robustness of the proposed stochastic resource allocation schemes for O-RANs compared to existing deterministic allocation schemes. They also show the merits of adapting the allocation of resources to the network uncertainties compared to statically allocating them.INDEX TERMS Open radio access networks (O-RANs), RAN intelligent controller (RIC) placement, RIC assignment, chance-constrained stochastic optimization, two-stage stochastic optimization with recourse, sample average approximation.

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Section: Literature Reviewmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

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On Robust Optimal Joint Deployment and Assignment of RAN Intelligent Controllers in O-RANs

Abdel-Rahman,

Mazied,

Hassan

et al. 2024

IEEE Open J. Commun. Soc.

View full text Add to dashboard Cite

show abstract

“…Joshua et al [46] also applied a clustering technique for optimal controller placement, assessed using the Mininet emulator and silhouette scores to determine the ideal number of controllers for various topologies. In a similar effort, Chen et al [47] proposed a density-based controller placement algorithm (DCPA) for joint latency Rodney Sebopelo1, Bassey Isong | 469 optimization, which segments the network into subnetworks and strategically places controllers to minimize average and worst-case latencies. Tested on eight real network topologies, DCPA demonstrated optimal performance with low time consumption.…”

Section: Controller Placement Problemmentioning

confidence: 99%

An Integrated Framework for Controllers Placement and Security in Software-Defined Networks Ecosystem

Sebopelo,

Isong

2024

J. Inf. Syst. Informatics

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In the evolving landscape of Software-Defined Networking (SDN), the strategic placement of controllers poses a critical challenge that necessitate a precise balance between network performance and security. This paper presents an integrated framework for enhancing security and performance in SDN by combining controller placement and intrusion detection systems (IDS). Unlike existing solutions which were implemented disjointedly, we propose a holistic approach that leverages the proximity of controllers to network traffic for real-time threat detection, rapid response, and mitigation of security attacks. We employ an advanced clustering model for optimal controller placement, reducing costs and latency while ensuring reliability and balanced loads. In addition, we utilize k-nearest neighbour (KNN) for efficient anomaly detection in our IDS for improved network security. Experimental results confirm the framework’s effectiveness in strengthening SDN security and resilience. The enhanced-DBSCAN-based CPP model significantly minimized the cost, and latency, and ensured continuous operation in dynamic SDN environments while the KNN-based IDS shows effectiveness in improving threat detection capabilities, achieving high detection accuracy of 100% on the LAN dataset, outperforming other machine learning models such as Random Forest and Naïve Bayes. The indication is that strategic controller deployment, in conjunction with IDS, can significantly bolster threat detection, response times, and the overall security stance of the SDN environment.

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Research on placement of distributed SDN multiple controllers based on IAVOA

Chen

Dong

et al. 2023

Cluster Comput

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A density algorithm for controller placement problem in software defined wide area networks

Cited by 4 publications

References 39 publications

On Robust Optimal Joint Deployment and Assignment of RAN Intelligent Controllers in O-RANs

On Robust Optimal Joint Deployment and Assignment of RAN Intelligent Controllers in O-RANs

An Integrated Framework for Controllers Placement and Security in Software-Defined Networks Ecosystem

Research on placement of distributed SDN multiple controllers based on IAVOA

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