An IoT and Blockchain‐based approach for the smart water management system in agriculture

Expert Systems, Journal Year: 2021, Volume and Issue: 40(4)

Published: Nov. 24, 2021

Abstract Agriculture in rural areas facing critical issues such as irrigation with the increase water crises followed by some other line seed quality, poor fertilizers and many others. The recent advances suggest that IoT Blockchain Technology along artificial intelligence will be most dominant technologies near future. In this article, integration of Internet Things (IoT) technology is implemented for monitoring agricultural fields efficiently. An efficient quality smart management system design using managing coordinating use good seeds resources among communities. network securing information supporting trust members community. also sporting commercial resource constrained systems, which are communicating consisting a hardware platform. prototype its performance evaluation based on implementation presented.

Language: Английский

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A novel Q-learning-based hybrid algorithm for the optimal offloading and scheduling in mobile edge computing environments

Journal of Network and Computer Applications, Journal Year: 2023, Volume and Issue: 214, P. 103617 - 103617

Published: March 2, 2023

Language: Английский

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Using differential evolution and Moth–Flame optimization for scientific workflow scheduling in fog computing

Applied Soft Computing, Journal Year: 2021, Volume and Issue: 112, P. 107744 - 107744

Published: July 30, 2021

Language: Английский

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An improved discrete harris hawk optimization algorithm for efficient workflow scheduling in multi-fog computing

Sustainable Computing Informatics and Systems, Journal Year: 2022, Volume and Issue: 36, P. 100787 - 100787

Published: Aug. 18, 2022

Language: Английский

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Seagull optimization algorithm based multi-objective VM placement in edge-cloud data centers

Internet of Things and Cyber-Physical Systems, Journal Year: 2023, Volume and Issue: 3, P. 28 - 36

Published: Jan. 1, 2023

Edge-Cloud Datacenters (ECDCs) have been massively exploited by the owners of technology and industrial centers to satisfy user demand. At same time, amount energy used these data is considerable. To address this challenge, Virtual Machine (VM) placement ECDCs plays an important role; therefore, assigning VM properly physical machines (PM) can significantly decrease consumption. The applied technique simultaneously must consider additional objectives involving traffic power usage network elements, which makes it a challenging problem. This paper proposes multi-objective approach in edge-cloud centers, uses Seagull optimization optimize together. In strategy, among PMs reduced concentrating communications VMs on reduce transferred through PMs' consumption consolidating fewer PMs, consumes less energy. We evaluate with simulations CloudSim test two different topologies, VL2 (Virtual Layer 2) three-tier, validate that proposed effectively ECDCs. experimental results show our method 5.5% while reducing 70% components 80%.

Language: Английский

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A learning automata-based hybrid MPA and JS algorithm for numerical optimization problems and its application on data clustering

Knowledge-Based Systems, Journal Year: 2021, Volume and Issue: 236, P. 107682 - 107682

Published: Nov. 9, 2021

Language: Английский

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A Hybrid Mayfly-Aquila Optimization Algorithm Based Energy-Efficient Clustering Routing Protocol for Wireless Sensor Networks

Sensors, Journal Year: 2022, Volume and Issue: 22(17), P. 6405 - 6405

Published: Aug. 25, 2022

In recent times, Wireless Sensor Networks (WSNs) are becoming more and popular making significant advances in wireless communication thanks to low-cost low-power sensors. However, since WSN nodes battery-powered, they lose all of their autonomy after a certain time. This energy restriction impacts the network's lifetime. Clustering can increase lifetime network while also lowering use. will bring several similar sensors one location for data collection delivery Base Station (BS). The Cluster Head (CH) uses when collecting transferring data. life WSNs be extended, efficient identification CH minimize consumption. Creating routing algorithm that considers key challenges usage maximizing is still challenging. paper presents an energy-efficient clustering protocol based on hybrid Mayfly-Aquila optimization (MFA-AOA) solving these critical issues WSNs. Mayfly employed choose optimal from nodes. Aquila identifies selects optimum route between BS. simulation results showed proposed methodology achieved better consumption by 10.22%, 11.26%, 14.28%, normalized 9.56%, 11.78%, 13.76% than existing state-of-art approaches.

Language: Английский

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Machine Learning Assists IoT Localization: A Review of Current Challenges and Future Trends

Sensors, Journal Year: 2023, Volume and Issue: 23(7), P. 3551 - 3551

Published: March 28, 2023

The widespread use of the internet and exponential growth in small hardware diversity enable development Internet things (IoT)-based localization systems. We review machine-learning-based approaches for IoT systems this paper. Because their high prediction accuracy, machine learning methods are now being used to solve problems. paper’s main goal is provide a how algorithms problems, as well address current challenges. examine existing literature published papers released between 2020 2022. These studies classified according several criteria, including algorithm, chosen environment, specific covered protocol, measurement technique. also discuss potential applications localization, future trends.

Language: Английский

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Range-free localization algorithm based on modified distance and improved black-winged kite algorithm

Computer Networks, Journal Year: 2025, Volume and Issue: unknown, P. 111091 - 111091

Published: Feb. 1, 2025

Language: Английский

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A Comprehensive Review of the Tunicate Swarm Algorithm: Variations, Applications, and Results

Archives of Computational Methods in Engineering, Journal Year: 2025, Volume and Issue: unknown

Published: March 12, 2025

Language: Английский

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