NFV Provisioning in Large-Scale Distributed Networks With Minimum Delay

Alenazi, Mohammed J. F.; Almutairi, Abdulrahman; Almowuena, Saleh; Abdul, Wadood; Çetinkaya, Egemen K.

doi:10.1109/access.2020.3017667

Cited by 8 publications

(5 citation statements)

References 36 publications

(30 reference statements)

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“…Achievable sum rate(bps) Total consumed power(watts) (29) • Average Packet Delay One of the QoS requirements for 5G networks is to reduce the amount of delays [76], [77]. A packet's downlink delay is a result of delays in transmission, propagation, processing, and queuing [78], [79].…”

Section: Ee(bits/joule) =mentioning

confidence: 99%

A2T-Boost: An Adaptive Cell Selection Approach for 5G/SDN-Based Vehicular Networks

Alablani

Arafah²

2023

IEEE Access

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Heterogeneous ultra-dense networks (HUDNs) are one of the key enabling technologies for the fifth-generation (5G) networks. They aim to provide high capacity, low installation cost, and distributed traffic loads. The cell selection is a challenging issue in HUDNs, due to the different characteristics of base stations (BSs) and the existence of a large number of them. Thus, the traditional cell selection scheme is not applicable in such a network. In this paper, a novel adaptive cell selection strategy is proposed, called adaptive two-tier based on adaptive boosting (A2T-Boost). It can adapt to the various characteristics of base stations, as well as the different movement features of mobile stations such as vehicles and pedestrian. It is a software-defined networking (SDN)/machine learning (ML)-based scheme. A real-world case is considered in the downtown of Los Angeles city. Simulation results demonstrate that A2T-Boost achieves high prediction performance and it outperforms other related schemes in terms of average number of handovers (HOs) by up to 50%. Moreover, it enhances the average achievable downlink sum-rates and network energy efficiency achieved by vehicles by up to 33.76%. Furthermore, the average packet delay is decreased using the proposed scheme by up to 12.87%.

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Section: Ee(bits/joule) =mentioning

confidence: 99%

A2T-Boost: An Adaptive Cell Selection Approach for 5G/SDN-Based Vehicular Networks

Alablani

Arafah²

2023

IEEE Access

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“…This step greatly reduces the workload of subsequent capacity allocation. Especially in the case of a large amount of data, the K-means algorithm is more efficient than other algorithms [17][18].…”

Section: K-means Algorithmmentioning

confidence: 99%

Distributed System Optimization Based on K-means Clustering

2021

DPS

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The regional energy internet is a distributed complex system with deep integration of energy and information. If different energy systems are planned and operated independently and lack of coordination with each other, problems such as low energy utilization rate, weak self-healing ability, and low system security and reliability will be caused. Therefore, scientific and reasonable planning methods and operation strategies are crucial to the overall efficiency and economy of distributed multi-energy systems. The main purpose of this paper is to study the optimization of distributed systems based on K-Means clustering. In this paper, a multi-energy unified clustering model based on the K-means algorithm is established to analyze the data characteristics in the cluster, and at the same time, the energy-side data is clustered to evaluate the available value of various types of energy. Experiments show that according to the 2/5/10 principle, when the system response time is within 2s, the user experience is very good. When the response time is between 2s and 5s, the user experience is better. Because the number of concurrent users of the system exceeds 500, the response time of the system is within the normal response time range acceptable to users and meets the needs of enterprises.

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“…8,9 In recent years, its use for quantifying resilience has evolved to become an essential component in multiple applications within the field of computer network security. [10][11][12][13][14] One of the main resilience metrics, referred to as robustness, is the ability of a network to keep providing the same level of service in the presence of disruptions. 6,7 In general, resilience is determined by centrality measures that quantify the significance of nodes; robustness is evaluated after the node with the highest centrality measure has been attacked.…”

Section: Introductionmentioning

confidence: 99%

“…Graph theory has long been used for network analysis, including designing, modeling, and optimizing networks 8,9 . In recent years, its use for quantifying resilience has evolved to become an essential component in multiple applications within the field of computer network security 10‐14 . One of the main resilience metrics, referred to as robustness, is the ability of a network to keep providing the same level of service in the presence of disruptions 6,7 .…”

Section: Introductionmentioning

confidence: 99%

Evaluation of industrial network robustness against targeted attacks

Alrumaih,

Alenazi

2023

Concurrency and Computation

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SummaryDeveloping a long‐lasting, secure Industry 4.0 system presents a significant challenge for businesses and other interested parties. Industrial control systems (ICSs) are particularly vulnerable to cybercrime because of the operating systems' excessive availability and high robustness requirements. This research investigates five graph‐theory‐based measures to evaluate the robustness of industrial network topologies against three centrality‐based attacks and one random attack. Experiments are conducted to examine the three levels of the ICS network topology, from the field devices to the controllers and the enterprise devices. The results are twofold. On the one hand, the closeness‐based attack is the most harmful since it has the highest destructive potential and needs to attack only half of the total nodes in the network to reach the lowest robustness level. The betweenness‐based attack follows closely in terms of destruction, whereas the degree‐based attack is less destructive but rapidly degrades the robustness of the network. On the other hand, the flow robustness measure provides the best performance in the presence of any of the studied attacks, showing strong perception of robustness reduction when only one percent of the total nodes in the network are attacked. For this reason, the flow robustness measure is suitable to identify and locate the targeted attacks at their early stages, preventing them from becoming more catastrophic. Finally, the results suggest that the industrial network security system should combine at least two measures to ensure robustness against the most destructive attacks and their early‐stage detection. The research also confirmed the results by implementing attacks and measures on a real gas transmission network.

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NFV Provisioning in Large-Scale Distributed Networks With Minimum Delay

Cited by 8 publications

References 36 publications

A2T-Boost: An Adaptive Cell Selection Approach for 5G/SDN-Based Vehicular Networks

A2T-Boost: An Adaptive Cell Selection Approach for 5G/SDN-Based Vehicular Networks

Distributed System Optimization Based on K-means Clustering

Evaluation of industrial network robustness against targeted attacks

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