Enhanced salp swarm algorithm based on firefly algorithm for unrelated parallel machine scheduling with setup times

Applied Mathematical Modelling, Journal Year: 2021, Volume and Issue: 94, P. 285 - 305

Published: Jan. 23, 2021

Language: Английский

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A survey on firefly algorithms

Neurocomputing, Journal Year: 2022, Volume and Issue: 500, P. 662 - 678

Published: May 31, 2022

Language: Английский

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IoT-assisted physical education training network virtualization and resource management using a deep reinforcement learning system

Complex & Intelligent Systems, Journal Year: 2021, Volume and Issue: 8(2), P. 1229 - 1242

Published: Dec. 2, 2021

Abstract The Internet of Things (IoT) development made it possible for technology to communicate physical education by connecting cost-effective heterogeneous devices and digital applications uncontrolled accessible environments. traditional monitoring environment creates crucial manual efforts on athletes' activity observations tracking consistently. Similarly, remote assessment athletes in sports training seem be barriers training. It various chances improve through advancements like IoT deep learning. Students can efficiently monitor their behavior increase psychological benefits. IoT-assisted device is proposed track students' enhance outcomes. management ability allows students organize speed a wellness manner. In addition, this study examines the connections between which an essential component activities activity. This system collects information from IoT-based wearable that interact with data real time virtualizing device. network includes several monitors heartbeat body temperature person. analysis specific studies student feedback shows designed virtual educations effective its application implementation provides reliable guide developing educational systems. experimental evaluated; solution offered supporting approaches reality healthy systems solve health challenges posed devices. method has achieved extraordinary compared conventional systems, as shown findings. simulation help associated aspects abilities high accuracy ratio (98.3), prediction (96.5%), interaction (94.4%), performance (95.1%), efficiency (93.2), F -score (92.2%), reduce error rate (17.5%) patterns.

Language: Английский

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An Artificial Intelligence-Based Quorum System for the Improvement of the Lifespan of Sensor Networks

IEEE Sensors Journal, Journal Year: 2021, Volume and Issue: 21(15), P. 17373 - 17385

Published: May 13, 2021

Artificial Intelligence-based Quorum systems are used to solve the energy crisis in real-time wireless sensor networks. They tend improve coverage, connectivity, latency, and lifespan of networks where millions nodes need be deployed a smart grid system. The reality is that sensors may consume more power reduce lifetime network. This paper proposes quorum-based system number quorum increased without actually increasing quorums themselves, leading improvements throughput latency by 14.23%. proposed artificial intelligence scheme reduces network due an increase time slots over conventional algorithms previously proposed. Secondly, consumption reduced weighted load balancing, improving network's actual lifespan. Our experimental results show coverage rate on average 11% Coverage Contribution Area (CCA), Partial with Learning Automata (PCLA), Probabilistic Protocol (PCP) protocols respectively.

Language: Английский

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Dynamic Resource Allocation Using Improved Firefly Optimization Algorithm in Cloud Environment

Applied Artificial Intelligence, Journal Year: 2022, Volume and Issue: 36(1)

Published: March 24, 2022

Today, cloud computing has provided a suitable platform to meet the needs of users. One most important challenges facing is Dynamic Resource Allocation (DSA), which in NP-Hard class. goals DSA utilization resources efficiently and maximize productivity. In this paper, an improved Firefly algorithm based on load balancing optimization introduced solve problem called IFA-DSA. addition workloads between existing virtual machines, IFA-DSA also reduces completion time by selecting appropriate objectives fitness function. The best sequence tasks for resource allocation formulated as multi-objective problem. intended are balancing, time, average runtime, migration rate. order improve initial population creation firefly algorithm, heuristic method used instead random approach. method, created priority tasks, where each task determined pay you use model fuzzy results experiments show superiority proposed makespan criterion over ICFA 3%.

Language: Английский

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An enhanced QoS approach for multi-objective optimization using social spider optimization 5G enable IoMT network

International Journal of Information Technology, Journal Year: 2024, Volume and Issue: unknown

Published: July 1, 2024

Language: Английский

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Development of an IoT-enabled cost-effective asthma patient monitoring system: Integrating health and indoor environment data with statistical analysis and data visualization

Internet of Things, Journal Year: 2023, Volume and Issue: 24, P. 100942 - 100942

Published: Sept. 10, 2023

Language: Английский

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An Advanced Energy Efficient Resource Allocation for Software‐Defined WSN Using Hybrid Optimization Algorithm

International Journal of Communication Systems, Journal Year: 2025, Volume and Issue: 38(3)

Published: Jan. 12, 2025

ABSTRACT Software‐Defined Wireless Sensor Networking (SDWSN) is termed a rising network structure that has become more important to the Internet of Things (IoT). In this structure, control planes effectively manage sensor plane. Due these kinds separation, management networks became easier and also their efficacies are enhanced in self‐motivated atmosphere. The common issue presented atmosphere minimal life devices inspired by maximal level energy consumption rate. current study provides system architecture intends increase efficiency an SDWSN incorporating optimization techniques. A novel hybrid strategy created merging Election‐Based Optimization Algorithm (EBOA) with Ladybird Beetle (LBOA), result known as Hybrid Election‐based (HELBO). This work examines energy‐efficient resource allocation mechanism SDWSNs have substantial computing power memory. These algorithms optimize bandwidth along attain considerable Signal Interference plus Noise Ratio (SINR) under individual constraint quality service. Finally, empirical findings show recommended HELBO method outperforms other present algorithms.

Language: Английский

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Nature‐Inspired Meta‐Heuristic Algorithms for Resource Allocation in the Internet of Things

International Journal of Communication Systems, Journal Year: 2025, Volume and Issue: 38(5)

Published: Feb. 17, 2025

ABSTRACT The Internet of Things (IoT) is a paradigm‐shifting concept that helps realize an acquisition, processing, and analytical global network, digitizing tangible entities to enhance efficiency safety in various smart cities, healthcare, Industry 4.0 domains. However, whereas IoT scales, with several heterogeneous devices diverse, varied capabilities service demands, cloud resource management usually faces the challenge intricate complexity efficiently allocating resources despite demand for quality (QoS). Hence, this paper systematically reviews nature‐inspired metaheuristic algorithm applications allocation solving NP‐hard problems. We summarize recent advances methods, including comparisons against traditional methods. also discuss practical feasibility scaling issues real‐world scenarios. Further, we have highlighted few gaps current literature provided recommendations on specific topics future research, thereby indicating how develop scalable, efficient solutions meet IoT's ever‐evolving demands.

Language: Английский

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Data cryptography in the Internet of Things using the artificial bee colony algorithm in a smart irrigation system

Journal of Information Security and Applications, Journal Year: 2021, Volume and Issue: 61, P. 102945 - 102945

Published: July 27, 2021

Language: Английский

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