A self-organized priority-based MAC protocol in wireless sensor networks based on SDR-RHSO optimal relay node selection and HL-ANN wake-up scheduling

Thalagondapati, Veeraiah; Singh, M. P.

doi:10.1007/s12652-022-04390-y

Cited by 4 publications

(6 citation statements)

References 18 publications

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“…In high-traffic settings, however, dynamic time-slot management is International Journal of Intelligent Engineering and Systems, Vol. 16 Figure . 1 The proposed method is depicted in a block diagram challenging and will impair network throughput. To boost network functionality, an effective congestion avoidance strategy [13] is presented based on Huffman coding algorithm and ant colony optimization.…”

Section: Related Workmentioning

confidence: 99%

“…Artificial intelligence algorithms are employed for awakening scheduling of active nodes [16], while the Spatial Spider Optimization algorithm and Kmeans clustering enhancement are used to pick cluster heads. Provides improved delay and throughput at first, but both degrade with time.…”

Section: Related Workmentioning

confidence: 99%

“…The network coding path combines data for transmission to the next hop, increasing channel usage and reducing International Journal of Intelligent Engineering and Systems, Vol. 16 packet redundancy in the network [18]. When congestion occurs, an adaptive methodology is given in which the packet dropping rate is increased and the node sends packets by aggregating them using network coding.…”

Section: Energy-aware Proficient Rate Control With Data Aggregation A...mentioning

confidence: 99%

“…The amount of time it takes for information to travel from its source to its destination (sink) 𝐸2𝐸 𝐷𝑒𝑙𝑎𝑦 = 𝑇𝑖𝑚𝑒 𝑠𝑖𝑛𝑘 − 𝑇𝑖𝑚𝑒 𝑜𝑟𝑖𝑔𝑖𝑛 (13) International Journal of Intelligent Engineering and Systems, Vol. 16 In this Eq. ( 13) 𝑇𝑖𝑚𝑒 𝑠𝑖𝑛𝑘 is the time at the sink while accepting the data and 𝑇𝑖𝑚𝑒 𝑜𝑟𝑖𝑔𝑖𝑛 is the time at the origin while forwarding that data.…”

Section: End-to-end Delaymentioning

confidence: 99%

“…An effective methods are required in WSN to handle massive amounts of frequently sensed data with limited bandwidth and International Journal of Intelligent Engineering and Systems, Vol. 16, No. 3,2023 DOI: 10.22266/ijies2023.0630.08 energy utilization.…”

Section: Introductionmentioning

confidence: 99%

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Smart Bandwidth Prediction, Power Management and Adaptive Network Coding for WSN

2023

IJIES

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WSN has been widely used in many sensitive applications and it also has novel possibilities for laying the groundwork for using ubiquitous and pervasive computing, but it has also presented a number of issues and challenges, such as a dynamic network topology and a congestion problem that hinders not only network bandwidth utilisation but also performance. Proficient rate control and fair bandwidth allocation (PRC-FBA) was one of the schemes in the literature to solve issues of WSN by combining the ideas of traffic class priority and bandwidth fairness. However, because of the nature of WSN, the energy of nodes near the sink node is diminished when packets move from lowly congested nodes to highly congested nodes. This paper proposes a proficient rate control with data aggregation and fair bandwidth allocation (PRCDA-FBA) to address this problem by using an effective data aggregation approach for reducing the number of transmissions. In the proposed method, fair bandwidth allocation is simplified by an artificial intelligence-based bandwidth prediction method. Thus, PRCDA-FBA increases the network's durability. Despite having lower bandwidth utilizations, energy-critical sensor nodes require careful power management to avoid being eavesdropped upon. Along with data aggregation and fair bandwidth allocation, the effects of overhearing packets by energy-critical nodes are mitigated through network-wide route adjustments based on the energy level of nodes. Thus, in the proposed method, data aggregation is scheduled based on the availability of bandwidth, energy, queue size and packet priority. The proposed method is named as energy-aware proficient rate control with data aggregation and fair bandwidth allocation (EPRCDA-FBA). The proposed algorithms have been deployed on the Network Simulator 2.35 platform, and a comparative analysis has been performed using several metrics, including throughput, packet loss, End-to-End (E2E) delay and energy utilization. The EPRCDA-FBA method archives highest throughput which is 9.17%, 5.48%, 4.68% and 2.45% higher than congestion control strategies like discrete-time sliding mode congestion controller (DSMC), weighted priority based fair queue gradient rate control (WPFQGRC), PRC-FBA and rate adjustment-based congestion control (RACC).

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Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Section: Energy-aware Proficient Rate Control With Data Aggregation A...mentioning

confidence: 99%

Section: End-to-end Delaymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Smart Bandwidth Prediction, Power Management and Adaptive Network Coding for WSN

2023

IJIES

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A novel hybrid pelican-particle swarm optimization algorithm (HPPSO) for global optimization problem

Raj,

Punia,

Kumar

2024

Int J Syst Assur Eng Manag

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Distributed TDMA Scheduling for Autonomous Aerial Swarms: A Self-Organizing Approach

Aydin,

Akcasoy,

Cakir

et al. 2024

IEEE Access

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Self-organization is a key strategy for improving the performance of an aerial swarm ad hoc network. The proliferation of low-cost VTOL drones has broadened the application domain of aerial swarms, and the need for synchronized communication among network entities has become crucial. However, existing ad hoc approaches struggle to maintain multi-hop connections in contested environments characterized by frequent topology changes and intermittent links. To overcome these limitations, we introduced STDMA protocol, which enables the self-configuration of drones without reliance on a ground controller. In continuation of the earlier work, we conduct extensive experiments to evaluate the performance of the proposed protocol.Comparative simulation experiments cover various scenarios with different network sizes, frame lengths, and traffic loads. The STDMA protocol achieves optimal access delay in highly contested environments and reduces delay by approximately 19.181%. Moreover, it exhibits improved channel utilization compared to the E-ASAP/SM protocol, with a 4.5 times increase.INDEX TERMS ad hoc networks, autonomous control, decentralized control, distributed systems, reliable communication, self-organizing network management, swarm intelligence, UAV swarm I. INTRODUCTION

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A self-organized priority-based MAC protocol in wireless sensor networks based on SDR-RHSO optimal relay node selection and HL-ANN wake-up scheduling

Cited by 4 publications

References 18 publications

Smart Bandwidth Prediction, Power Management and Adaptive Network Coding for WSN

Smart Bandwidth Prediction, Power Management and Adaptive Network Coding for WSN

A novel hybrid pelican-particle swarm optimization algorithm (HPPSO) for global optimization problem

Distributed TDMA Scheduling for Autonomous Aerial Swarms: A Self-Organizing Approach

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