• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利：CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法，用中文像聊天一样搜索，搜遍4000万医学文献。AI智能推荐，让科研检索更轻松。

立即免费搜索

文件翻译

保留排版，准确专业，支持PDF/Word/PPT等文件格式，支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述，25分钟生成高质量综述，智能提取关键信息，辅助科研写作。

立即免费体验

基于启发式算法的物联网资源分配与优化。

IoT Resource Allocation and Optimization Based on Heuristic Algorithm.

机构信息

School of Computing Science and Engineering, Vellore Institute of Technology (VIT), Vellore 632014, India.

Deportment of Computer Engineering, Islamic Azad University Behshahr Branch, Behshahr 511-48515, Iran.

出版信息

Sensors (Basel). 2020 Jan 18;20(2):539. doi: 10.3390/s20020539.

DOI:10.3390/s20020539
PMID:31963762
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7014514/
Abstract

The Internet of Things (IoT) is a distributed system that connects everything via internet. IoT infrastructure contains multiple resources and gateways. In such a system, the problem of optimizing IoT resource allocation and scheduling (IRAS) is vital, because resource allocation (RA) and scheduling deals with the mapping between recourses and gateways and is also responsible for optimally allocating resources to available gateways. In the IoT environment, a gateway may face hundreds of resources to connect. Therefore, manual resource allocation and scheduling is not possible. In this paper, the whale optimization algorithm (WOA) is used to solve the RA problem in IoT with the aim of optimal RA and reducing the total communication cost between resources and gateways. The proposed algorithm has been compared to the other existing algorithms. Results indicate the proper performance of the proposed algorithm. Based on various benchmarks, the proposed method, in terms of "total communication cost", is better than other ones.

摘要

物联网（IoT）是一个通过互联网连接一切的分布式系统。物联网基础设施包含多个资源和网关。在这样的系统中，优化物联网资源分配和调度（IRAS）的问题至关重要，因为资源分配（RA）和调度涉及资源和网关之间的映射，并且还负责将资源最优地分配到可用的网关。在物联网环境中，网关可能要连接数百个资源。因此，手动资源分配和调度是不可能的。在本文中，我们使用鲸鱼优化算法（WOA）来解决物联网中的 RA 问题，目的是实现最优的 RA 和降低资源与网关之间的总通信成本。我们将所提出的算法与其他现有的算法进行了比较。结果表明，所提出的算法具有良好的性能。基于各种基准测试，所提出的方法在“总通信成本”方面优于其他方法。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5f09/7014514/e8d89802901f/sensors-20-00539-g018.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5f09/7014514/5982f0167626/sensors-20-00539-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5f09/7014514/e51f32746fe8/sensors-20-00539-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5f09/7014514/f6d22de37737/sensors-20-00539-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5f09/7014514/6f19dbbd2fe9/sensors-20-00539-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5f09/7014514/3b4219378e37/sensors-20-00539-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5f09/7014514/1893b4498fc6/sensors-20-00539-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5f09/7014514/c3c21870a91b/sensors-20-00539-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5f09/7014514/b9792a0580f8/sensors-20-00539-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5f09/7014514/f6371f684c2f/sensors-20-00539-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5f09/7014514/39feb2db181c/sensors-20-00539-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5f09/7014514/37e81e03ac7c/sensors-20-00539-g011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5f09/7014514/7047f74f6abf/sensors-20-00539-g012.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5f09/7014514/260e1a08c9b4/sensors-20-00539-g013.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5f09/7014514/0d8d12d3d2bb/sensors-20-00539-g014.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5f09/7014514/34e0b8fbb367/sensors-20-00539-g015.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5f09/7014514/b7cbde3c9836/sensors-20-00539-g016.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5f09/7014514/5d9554492c59/sensors-20-00539-g017.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5f09/7014514/e8d89802901f/sensors-20-00539-g018.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5f09/7014514/5982f0167626/sensors-20-00539-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5f09/7014514/e51f32746fe8/sensors-20-00539-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5f09/7014514/f6d22de37737/sensors-20-00539-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5f09/7014514/6f19dbbd2fe9/sensors-20-00539-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5f09/7014514/3b4219378e37/sensors-20-00539-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5f09/7014514/1893b4498fc6/sensors-20-00539-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5f09/7014514/c3c21870a91b/sensors-20-00539-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5f09/7014514/b9792a0580f8/sensors-20-00539-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5f09/7014514/f6371f684c2f/sensors-20-00539-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5f09/7014514/39feb2db181c/sensors-20-00539-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5f09/7014514/37e81e03ac7c/sensors-20-00539-g011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5f09/7014514/7047f74f6abf/sensors-20-00539-g012.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5f09/7014514/260e1a08c9b4/sensors-20-00539-g013.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5f09/7014514/0d8d12d3d2bb/sensors-20-00539-g014.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5f09/7014514/34e0b8fbb367/sensors-20-00539-g015.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5f09/7014514/b7cbde3c9836/sensors-20-00539-g016.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5f09/7014514/5d9554492c59/sensors-20-00539-g017.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5f09/7014514/e8d89802901f/sensors-20-00539-g018.jpg

相似文献

1
IoT Resource Allocation and Optimization Based on Heuristic Algorithm.基于启发式算法的物联网资源分配与优化。
Sensors (Basel). 2020 Jan 18;20(2):539. doi: 10.3390/s20020539.
2
Resource Allocation in the Cognitive Radio Network-Aided Internet of Things for the Cyber-Physical-Social System: An Efficient Jaya Algorithm.资源分配在认知无线电网络辅助的物联网中的 赛博物理社会系统：一种有效的 Jaya 算法。
Sensors (Basel). 2018 Oct 27;18(11):3649. doi: 10.3390/s18113649.
3
Planning and Optimization of Software-Defined and Virtualized IoT Gateway Deployment for Smart Campuses.面向智能校园的软件定义与虚拟化物联网网关部署的规划与优化
Sensors (Basel). 2022 Jun 22;22(13):4710. doi: 10.3390/s22134710.
4
A novel hybrid optimization enabled robust CNN algorithm for an IoT network intrusion detection approach.一种新型混合优化的健壮 CNN 算法在物联网网络入侵检测方法中的应用。
PLoS One. 2022 Dec 1;17(12):e0278493. doi: 10.1371/journal.pone.0278493. eCollection 2022.
5
Digital-Twin-Assisted Edge-Computing Resource Allocation Based on the Whale Optimization Algorithm.基于鲸鱼优化算法的数字孪生辅助边缘计算资源分配。
Sensors (Basel). 2022 Dec 6;22(23):9546. doi: 10.3390/s22239546.
6
A Multi-Hop Clustering Mechanism for Scalable IoT Networks.一种用于可扩展物联网网络的多跳聚类机制。
Sensors (Basel). 2018 Mar 23;18(4):961. doi: 10.3390/s18040961.
7
Energy-Efficient IoT Service Brokering with Quality of Service Support.具有服务质量支持的节能物联网服务代理。
Sensors (Basel). 2019 Feb 8;19(3):693. doi: 10.3390/s19030693.
8
Deep Reinforcement Learning-Based Task Scheduling in IoT Edge Computing.基于深度强化学习的物联网边缘计算任务调度
Sensors (Basel). 2021 Feb 28;21(5):1666. doi: 10.3390/s21051666.
9
Joint Resource Optimization in Simultaneous Wireless Information and Power Transfer (SWIPT) Enabled Multi-Relay Internet of Things (IoT) System.基于同时无线信息与能量传输（SWIPT）的多中继物联网（IoT）系统中的联合资源优化
Sensors (Basel). 2019 Jun 3;19(11):2536. doi: 10.3390/s19112536.
10
A Practical Evaluation of a High-Security Energy-Efficient Gateway for IoT Fog Computing Applications.用于物联网雾计算应用的高安全性节能网关的实际评估
Sensors (Basel). 2017 Aug 29;17(9):1978. doi: 10.3390/s17091978.

引用本文的文献

1
Intelligent resource allocation in internet of things using random forest and clustering techniques.基于随机森林和聚类技术的物联网智能资源分配
Sci Rep. 2025 Aug 20;15(1):30522. doi: 10.1038/s41598-025-15931-8.
2
Dynamic Coalition Formation among IoT Service Providers: A Systematic Exploration of IoT Dynamics Using an Agent-Based Model.物联网服务提供商之间的动态联盟形成：使用基于代理的模型对物联网动态进行系统探索。
Sensors (Basel). 2024 May 28;24(11):3471. doi: 10.3390/s24113471.
3
Optimization and Application of Communication Resource Allocation Algorithm for Urban Rail Transit Planning.
城市轨道交通规划中通信资源分配算法的优化与应用。
Comput Intell Neurosci. 2022 Aug 25;2022:5608665. doi: 10.1155/2022/5608665. eCollection 2022.
4
Joint Resource Allocation in Secure OFDM Two-Way Untrusted Relay System.安全正交频分复用双向不可信中继系统中的联合资源分配
Sensors (Basel). 2022 Mar 21;22(6):2398. doi: 10.3390/s22062398.
5
Machine Learning and Internet of Things Enabled Monitoring of Post-Surgery Patients: A Pilot Study.机器学习和物联网支持的术后患者监测：一项初步研究。
Sensors (Basel). 2022 Feb 12;22(4):1420. doi: 10.3390/s22041420.
6
A new hybrid metaheuristic method based on biogeography-based optimization and particle swarm optimization algorithm to estimate money demand in Iran.一种基于生物地理学优化和粒子群优化算法的新型混合元启发式方法，用于估计伊朗的货币需求。
MethodsX. 2021 Jan 13;8:101226. doi: 10.1016/j.mex.2021.101226. eCollection 2021.
7
Optical pattern generator for efficient bio-data encoding in a photonic sequence comparison architecture.用于在光子序列比较架构中高效生物数据编码的光学模式发生器。
PLoS One. 2021 Jan 15;16(1):e0245095. doi: 10.1371/journal.pone.0245095. eCollection 2021.