Noncooperative Gaming for Energy-Efficient Congestion Control in 6LoWPAN

Chowdhury, Srijit; Benslimane, Abderrahim; Giri, Chandan

doi:10.1109/jiot.2020.2969272

Cited by 24 publications

(6 citation statements)

References 36 publications

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“…The R-OPTICS uses two parameters core distance objects C D and reachability distance object R D . The ϵ is the distance threshold and is calculated using (5).…”

Section: Problem Solutionmentioning

confidence: 99%

“…Sharma et al [4] explored IoT objectives, enablers for massive machine type communications (mMTC), and device learning techniques. In IoT, congestion management was addressed by Chowdhury et al [5] with non-cooperative gaming for power-efficient congestion control (NGECC). Musaddiq et al [6] introduced a Q-learning-based intelligent collision probability inference algorithm for optimal IoT network performance.…”

Section: Introductionmentioning

confidence: 99%

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Enhancing routing efficiency in social internet of things: R-OPTICS and vEBT based congestion free model

Vinod,

Prakash

et al. 2024

IJECE

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The emergence of the social internet of things (SIoT) network has brought forth distinctive challenges, including node mobility and varying densities, leading to congestion and hampered network efficiency. To overcome these issues, a congestion-free routing model for SIoT is proposed. This model combines the relationship-ordering points to identify the clustering structure (R-OPTICS) algorithm for intelligent node clustering based on relationships and ordering,along with a van emde boas tree (vEBT) for efficient path selection. R-OPTICS enables effective network management by clustering nodes appropriately. The model’s performance is evaluated using metrics such as Rand-Index (1.5765),Davies-Bouldin (-0.4305), and Silhouette Coefficient (1.71685) to assess average goodness values. vEBT identifies optimal paths between clusters, facilitating smart routing decisions. The primary objective of the model is to enhance network efficiency and alleviate congestion by intelligently routing data between clusters. Through extensive simulations, the proposed model outperforms existing routing methods, resulting in improved efficiency and congestion reduction. This congestion-free routing model presents a promising solution to address the unique challenges of SIoT networks, ensuring optimal performance and effective resource management.

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“…The R-OPTICS uses two parameters core distance objects C D and reachability distance object R D . The ϵ is the distance threshold and is calculated using (5).…”

Section: Problem Solutionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Enhancing routing efficiency in social internet of things: R-OPTICS and vEBT based congestion free model

Vinod,

Prakash

et al. 2024

IJECE

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“…A recent decoupled learning optimization procedure was presented by Nan Jiang in [79]. This scheme involves the optimization of several features, including average access delay, successful device access, and average energy consumption.…”

Section: Ai-based Algorithms For Congestion Mitigation In Wsnmentioning

confidence: 99%

A Review on Congestion Mitigation Techniques in Ultra-Dense Wireless Sensor Networks: State-of-the-Art Future Emerging Artificial Intelligence-Based Solutions

Umar,

Khalid,

Ali

et al. 2023

Applied Sciences

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The Internet of Things (IoT) and wireless sensor networks (WSNs) have evolved rapidly due to technological breakthroughs. WSNs generate high traffic due to the growing number of sensor nodes. Congestion is one of several problems caused by the huge amount of data in WSNs. When wireless network resources are limited and IoT devices require more and more resources, congestion occurs in extremely dense WSN-based IoT networks. Reduced throughput, reduced network capacity, and reduced energy efficiency within WSNs are all effects of congestion. These consequences eventually lead to network outages due to underutilized network resources, increased network operating costs, and significantly degraded quality of service (QoS). Therefore, it is critical to deal with congestion in WSN-based IoT networks. Researchers have developed a number of approaches to address this problem, with new solutions based on artificial intelligence (AI) standing out. This research examines how new AI-based algorithms contribute to congestion mitigation in WSN-based IoT networks and the various congestion mitigation strategies that have helped reduce congestion. This study also highlights the limitations of AI-based solutions, including where and why they are used in WSNs, and a comparative study of the current literature that makes this study novel. The study concludes with a discussion of its significance and potential future study topics. The topic of congestion reduction in ultra-dense WSN-based IoT networks, as well as the current state of the art and emerging future solutions, demonstrates their significant expertise in reducing WSN congestion. These solutions contribute to network optimization, throughput enhancement, quality of service improvement, network capacity expansion, and overall WSN efficiency improvement.

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“…At present, there is a slowly increasing adoption towards using game theory; however, the target is again a scattered one. The work carried out by Chowdhury et al [29] targets towards two problems i.e., energy depletion and congestion in WSN emphasizing over low-end sensor node deployment. The author has designed non-cooperative game in order to optimize the process of improving data forwarding rate with an idea of resisting bottleneck condition in WSN.…”

Section: A Game-based Approachmentioning

confidence: 99%

Snapshot of Energy Optimization Techniques to Leverage Life of Wireless Sensor Network

Kavya¹,

Ravi²

2021

IJACSA

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Energy Optimization in Wireless Sensor Network (WSN) deals with the techniques which targets higher degree of energy efficiency using resource-constraint sensor nodes with minimal inclusion of any different variants of resources. At present, there are various approaches and techniques towards addressing the problems of energy but not all the research implications can be considered as optimized approach. Therefore, this paper reviews all the existing energy optimization schemes, categorizes them, briefly discuss about their strength and weakness to offer a compact snapshot of existing energy optimization techniques in WSN. The paper also contributes towards exploring the updates research trends and highlights about the open-end research problems in WSN. It is anticipated that the study findings of this manuscript will offer a true picture of study effectiveness in dealing with energy challenges so that favorable direction of investigation towards evolving up optimized solution comes up with promising outcome.

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Noncooperative Gaming for Energy-Efficient Congestion Control in 6LoWPAN

Cited by 24 publications

References 36 publications

Enhancing routing efficiency in social internet of things: R-OPTICS and vEBT based congestion free model

Enhancing routing efficiency in social internet of things: R-OPTICS and vEBT based congestion free model

A Review on Congestion Mitigation Techniques in Ultra-Dense Wireless Sensor Networks: State-of-the-Art Future Emerging Artificial Intelligence-Based Solutions

Snapshot of Energy Optimization Techniques to Leverage Life of Wireless Sensor Network

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