FUPE: A security driven task scheduling approach for SDN-based IoT–Fog networks

Javanmardi, Saeed; Shojafar, Mohammad; Mohammadi, Reza; Nazari, Amin; Persico, Valerio; Pescapè, Antonio

doi:10.1016/j.jisa.2021.102853

Cited by 36 publications

(25 citation statements)

References 69 publications

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“…The fuzzy cross entropy model [20] achieved the second highest performance in terms of data trustworthiness, and the Pareto optimal [16] solution demonstrated a strong performance. FUPE [19] based on the multi-objective PSO method showed a weaker performance due to poor convergence. The fuzzy cross entropy [20] and Pareto optimal [16] methods have the limitation of lower adaptability in the dynamic network.…”

Section: Resultsmentioning

confidence: 99%

“…The fuzzy cross entropy [20] and Pareto optimal [16] methods have lower performance due to their low adaptability in the model. The FUPE [19] method has poor convergence, which affects the performance of the model. The network utilization of the proposed DBG and existing methods in a dynamic network is compared in Figure 6.…”

Section: Resultsmentioning

confidence: 99%

“…The Pareto optimal [16] and fuzzy cross entropy [20] methods have lower adaptability, which increases the network utilization. The FUPE [19] method has poor convergence in the optimization process, which increases the network utilization. The computational time of the DBG and existing methods for various CMs is shown in Table 7 and Figure 7.…”

Section: Resultsmentioning

confidence: 99%

“…The security of the model was less defensive in the heterogeneous IoT system due to the distributed manner used. Javanmardi et al [19] proposed a security-aware task scheduler in IoT-fog networks called FUPE, based on fuzzy-based multi-objective Particle Swarm Optimization, to increase the security of protection. The FUPE method has higher security against DDoS attacks, and effectively detects the attack.…”

Section: Literature Reviewmentioning

confidence: 99%

“…Other researchers [16][17][18][19][20] achieved higher security in IoT networks using game theory, optimization, and attribute-based security models. However, the review of recent methods applied in the IoT shows that the existing approaches have the limitations of low data trustworthiness, low adaptability, and high latency.…”

Section: Literature Reviewmentioning

confidence: 99%

See 4 more Smart Citations

Dynamic Bargain Game Theory in the Internet of Things for Data Trustworthiness

Sumathi

Muthuramalingam

Prado

et al. 2021

Sensors

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Smart home and smart building systems based on the Internet of Things (IoT) in smart cities currently suffer from security issues. In particular, data trustworthiness and efficiency are two major concerns in Internet of Things (IoT)-based Wireless Sensor Networks (WSN). Various approaches, such as routing methods, intrusion detection, and path selection, have been applied to improve the security and efficiency of real-time networks. Path selection and malicious node discovery provide better solutions in terms of security and efficiency. This study proposed the Dynamic Bargaining Game (DBG) method for node selection and data transfer, to increase the data trustworthiness and efficiency. The data trustworthiness and efficiency are considered in the Pareto optimal solution to select the node, and the bargaining method assigns the disagreement measure to the nodes to eliminate the malicious nodes from the node selection. The DBG method performs the search process in a distributed manner that helps to find an effective solution for the dynamic networks. In this study, the data trustworthiness was measured based on the node used for data transmission and throughput was measured to analyze the efficiency. An SF attack was simulated in the network and the packet delivery ratio was measured to test the resilience of the DBG and existing methods. The results of the packet delivery ratio showed that the DBG method has higher resilience than the existing methods in a dynamic network. Moreover, for 100 nodes, the DBG method has higher data trustworthiness of 98% and throughput of 398 Mbps, whereas the existing fuzzy cross entropy method has data trustworthiness of 94% and a throughput of 334 Mbps.

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

See 3 more Smart Citations

Dynamic Bargain Game Theory in the Internet of Things for Data Trustworthiness

Sumathi

Muthuramalingam

Prado

et al. 2021

Sensors

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Software‐defined networks‐enabled fog computing for IoT‐based healthcare: Security, challenges and opportunities

Kumhar

Bhatia

2022

Security and Privacy

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The Internet of Things (IoT) is a crucial technology in the healthcare industry thanks to recent developments in automated data collection. Current statistics of the healthcare sector show that it is expanding at a remarkable rate. However, the performance of the healthcare system is impacted by many challenges, such as security, privacy, latency, scalability, and heterogeneity that come with advancement. Fog computing and software‐defined networks (SDN) are critical enabling technologies that help to improve IoT‐based healthcare systems by ensuring timely and reliable data provisioning for use in healthcare applications. SDN solves interoperability, device management, and network management issues and automates patient health monitoring without human interaction. SDN and fog computing in IoT‐based healthcare can optimize device communication and computing power at a low cost. SDN‐enabled fog computing has lower latency and better security than cloud‐based IoT healthcare architecture. The researchers have not entirely discovered SDN‐enabled fog computing to the best of our knowledge. This paper covers healthcare IoT technicalities and related technologies. We examined ways to merge SDN, fog computing, and IoT to improve healthcare solutions. Finally, we concluded the paper with research issues and future healthcare system improvements.

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A comprehensive survey on scheduling algorithms using fuzzy systems in distributed environments

Jalali Khalil Abadi,

Mansouri

2024

Artif Intell Rev

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FUPE: A security driven task scheduling approach for SDN-based IoT–Fog networks

Cited by 36 publications

References 69 publications

Dynamic Bargain Game Theory in the Internet of Things for Data Trustworthiness

Dynamic Bargain Game Theory in the Internet of Things for Data Trustworthiness

Software‐defined networks‐enabled fog computing for IoT‐based healthcare: Security, challenges and opportunities

A comprehensive survey on scheduling algorithms using fuzzy systems in distributed environments

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