An adaptive enhanced differential evolution strategies for topology robustness in internet of things

Qureshi, Talha Naeem; Javaid, Nadeem; Almogren, Ahmad; Khan, Asad Ullah; Almajed, Hisham N.; Mohiuddin, Irfan

doi:10.1504/ijwgs.2022.119267

Cited by 17 publications

(8 citation statements)

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“…Figure 1: Overview: (a) Variety of complex networks are analyzed from different angles. These are finding resilience in financial systems [41], identifying correlations in social systems [42,43,44], analyzing differences for diagnostics in Biological Networks [45,46,47] and exploring robustness in IoTs [1,10,16,17,27,48,40,49,38]. Available models for simulating complex/ real-world systems and generating graph models are WS, ER and BA [50].…”

Section: Topology Robustness and Its Importancementioning

confidence: 99%

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Topology Robustness Modelling against Targeted Attacks for Smart Healthcare System using Go-GA

Changazi

Bakhshi

Yousaf

et al. 2023

Preprint

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The Internet of Things (IoT) has become a pivotal component of modern technology, enabling the interconnection of numerous intelligent devices. It is envisioned to revolutionize various fields through the realization of numerous applications across industries, including healthcare, precision farming, transportation, and smart cities. However, the practical problem of node and link failures due to various constraints, such as low power backup, adverse environmental conditions, fragile metallurgy, and targeted attacks, can negatively impact the overall functionality of IoT networks. To address these challenges, soft and intelligent computing techniques, such as classical heuristic and genetic algorithms, can be utilized to improve the topology robustness of future IoT networks. In this study, we present a system model for a smart healthcare network and evaluate the effectiveness of optimization techniques, including the newly proposed Optimization of Topology for Efficient Convergence (OTEC), which combines a geometric approach in a genetic algorithm with two mechanisms, Efficient Edge Swap (EES) and Node Removal based on Threshold (NRT), to address key limitations in existing techniques. The metric of Schneider R is used to assess the robustness of the topology, with geographic information about IoT nodes and their neighbors stored on a central big data server. The OTEC approach utilizes a nested approach, demonstrating significant improvement over classical genetic algorithms by achieving a 21% increase in Schneider R. Additionally, OTEC effectively addresses limitations present in traditional heuristic algorithms such as ROSE, Simulated Annealing and Hill Climbing. The concept of trustworthiness is also considered from an overall perspective of system functionality. The optimized topology not only improves the robustness of the network but also enhances its trustworthiness, ensuring that the system can operate reliably and ethically. By leveraging soft and intelligent computing techniques, this study provides a valuable contribution to the development of future IoT networks that can handle the challenges of node and link failures while remaining trustworthy and dependable.

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Section: Topology Robustness and Its Importancementioning

confidence: 99%

“…Therefore, it causes an increase in cost along with jeopardizing scale-free property of the network. Thus, ensuring the robustness of scale-free networks while preserving the initial degree distribution of nodes is of vital importance [1,40,56,57].…”

Section: Literature Reviewmentioning

confidence: 99%

Topology Robustness Modelling against Targeted Attacks for Smart Healthcare System using Go-GA

Changazi

Bakhshi

Yousaf

et al. 2023

Preprint

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“…Therefore, an efficient measure is required to find the central node and fragment the network with minimum resources. Moreover, the network is optimized against the removal of nodes using the local information of the node [ 29 , 30 ].…”

Section: Related Workmentioning

confidence: 99%

Towards Enhancing the Robustness of Scale-Free IoT Networks by an Intelligent Rewiring Mechanism

Abbas

Javaid

Azar

et al. 2022

Sensors

Self Cite

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The enhancement of Robustness (R) has gained significant importance in Scale-Free Networks (SFNs) over the past few years. SFNs are resilient to Random Attacks (RAs). However, these networks are prone to Malicious Attacks (MAs). This study aims to construct a robust network against MAs. An Intelligent Rewiring (INTR) mechanism is proposed to optimize the network R against MAs. In this mechanism, edge rewiring is performed between the high and low degree nodes to make a robust network. The Closeness Centrality (CC) measure is utilized to determine the central nodes in the network. Based on the measure, MAs are performed on nodes to damage the network. Therefore, the connections of the neighboring nodes in the network are greatly affected by removing the central nodes. To analyze the network connectivity against the removal of nodes, the performance of CC is found to be more efficient in terms of computational time as compared to Betweenness Centrality (BC) and Eigenvector Centrality (EC). In addition, the Recalculated High Degree based Link Attacks (RHDLA) and the High Degree based Link Attacks (HDLA) are performed to affect the network connectivity. Using the local information of SFN, these attacks damage the vital portion of the network. The INTR outperforms Simulated Annealing (SA) and ROSE in terms of R by 17.8% and 10.7%, respectively. During the rewiring mechanism, the distribution of nodes’ degrees remains constant.

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“…Online education is a massive recovery and expansion that differs from superficial unions and symbols. So there is a big difference between the two [5].…”

Section: Innovation and Development Of Sportsmentioning

confidence: 99%

Innovation and Development of Sports Football Teaching Mode under the Background of Big Data and Internet of Things

Liu

2022

Wireless Communications and Mobile Computing

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Football is a sport that integrates competition, fitness, and entertainment, and its proportion in national development is rising. Under the background of big data, how to better carry out the innovation of physical education teaching mode is an important problem facing the current football reform. This paper mainly studies the effect of sports football teaching innovation on improving the ability of football education and students’ interest in football learning. This paper mainly uses the experimental method, the survey method, and the expert interview method to study the theory of football teaching and the model innovation under the big data. According to the basic principles and requirements, the questionnaires were distributed, filled out, and collected on the spot, and finally, the questionnaires were sorted and analyzed to draw conclusions. Finally, according to the experimental results, the average scores of the experimental students in group A were 8.2 and 73.5, respectively. The average scores of group B students were 81.6 and 74.3, respectively. The experimental group was significantly better than the control group in terms of test scores and performance levels, indicating that the use of new teaching methods combining big data and the Internet is of great significance.

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An adaptive enhanced differential evolution strategies for topology robustness in internet of things

Cited by 17 publications

References 0 publications

Topology Robustness Modelling against Targeted Attacks for Smart Healthcare System using Go-GA

Topology Robustness Modelling against Targeted Attacks for Smart Healthcare System using Go-GA

Towards Enhancing the Robustness of Scale-Free IoT Networks by an Intelligent Rewiring Mechanism

Innovation and Development of Sports Football Teaching Mode under the Background of Big Data and Internet of Things

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