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Enhancing mobile crowdsensing in Fog-based Internet of Things utilizing Harris hawks optimization

https://doi.org/10.1007/s12652-021-03344-0

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What this work says

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Harris hawks optimization: Algorithm and applications

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5G Internet of Things: A survey

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On Selecting Vehicles as Recommenders for Vehicular Social Networks

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Edge Computing Architecture for Mobile Crowdsensing

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A Systematic Survey of Industrial Internet of Things Security: Requirements and Fog Computing Opportunities

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Fog Computing and Smart Gateway Based Communication for Cloud of Things

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A Comprehensive Survey on Internet of Things (IoT) Toward 5G Wireless Systems

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Toward the Standardization of Non-Orthogonal Multiple Access for Next Generation Wireless Networks

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A City-Wide Real-Time Traffic Management System: Enabling Crowdsensing in Social Internet of Vehicles

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5G and IoT: Towards a new era of communications and measurements

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CrowdTasker: Maximizing coverage quality in Piggyback Crowdsensing under budget constraint

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Smartphone Malware and Its Propagation Modeling: A Survey

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Service Popularity-Based Smart Resources Partitioning for Fog Computing-Enabled Industrial Internet of Things

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Mobility and Intruder Prior Information Improving the Barrier Coverage of Sparse Sensor Networks

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Distributed and Energy-Efficient Mobile Crowdsensing with Charging Stations by Deep Reinforcement Learning

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The Internet of Things

What points at this work

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Galactic swarm‐improved whale optimization algorithm‐based resource management in Internet of things

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Secured Authentication and Optimal Key‐Based Encryption for Data Privacy Preservation in Mobile Crowd Sensing

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Swarm intelligence techniques and their applications in fog/edge computing: an in-depth review

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Securing internet of things using machine and deep learning methods: a survey

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ADOPT—the aquila-differential optimizer for efficient task allocation and QoS enhancement in mobile crowdsensing

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Energy-efficient task allocation in mobile crowdsensing using mobility and participation prediction

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Task offloading in Internet of Things based on the improved multi-objective aquila optimizer

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Energy-aware ACO-DNN optimization model for intrusion detection of unmanned aerial vehicle (UAVs)

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The Application of Hybrid Krill Herd Artificial Hummingbird Algorithm for Scientific Workflow Scheduling in Fog Computing

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An Intrusion Detection System on The Internet of Things Using Deep Learning and Multi-objective Enhanced Gorilla Troops Optimizer

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A Multi-Level Thresholding Image Segmentation Method Using Hybrid Arithmetic Optimization and Harris Hawks Optimizer Algorithms

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ETFC: Energy-efficient and deadline-aware task scheduling in fog computing

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A Traffic-Aware Task Mapping Problem in Fog-Cloud of Things

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An Efficient Lightweight Crypto Security Module for Protecting Data Transmission Through IOT Based Electronic Sensors

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An efficient load balancing in cloud computing using hybrid Harris hawks optimization and cuckoo search algorithm

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HHMFO-DVFS for An Optimal Makespan-Energy-aware Workflow Scheduling in Cloud

inferred← citeshttps://doi.org/10.21203/rs.3.rs-3811017/v2openalex-snapshot

HHMFO-DVFS for An Optimal Makespan-Energy-aware Workflow Scheduling in Cloud

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Development of Task Allocation in Mobile Crowdsensing Using User Mobility Prediction, Participation Rate Prediction, and Population-Based Metaheuristic Algorithms

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