• 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

一种增强型动态传输机会方案,用于支持无线校园网络中变化的业务负载。

An enhanced dynamic transmission opportunity scheme to support varying traffic load over wireless campus networks.

机构信息

Department of Electrical and Electronic Engineering, Universiti Teknologi PETRONAS, Seri Iskandar, Perak, Malaysia.

Center for Cyber Security, Faculty of Information Science and Technology, Universiti Kebangsaan Malaysia, Bangi, Malaysia.

出版信息

PLoS One. 2020 Aug 26;15(8):e0238073. doi: 10.1371/journal.pone.0238073. eCollection 2020.

DOI:10.1371/journal.pone.0238073
PMID:32845901
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7449386/
Abstract

Transmission opportunity (TXOP) is a key factor to enable efficient channel bandwidth utilization over wireless campus networks (WCN) for interactive multimedia (IMM) applications. It facilitates in resource allocation for the similar categories of multiple packets transmission until the allocated time is expired. The static TXOP limits are defined for various categories of IMM traffics in the IEEE802.11e standard. Due to the variation of traffic load in WCN, the static TXOP limits are not sufficient enough to guarantee the quality of service (QoS) for IMM traffic flows. In order to address this issue, several existing works allocate the TXOP limits dynamically to ensure QoS for IMM traffics based on the current associated queue size and pre-setting threshold values. However, existing works do not take into account all the medium access control (MAC) overheads while estimating the current queue size which in turn is required for dynamic TXOP limits allocation. Hence, not considering MAC overhead appropriately results in inaccurate queue size estimation, thereby leading to inappropriate allocation of dynamic TXOP limits. In this article, an enhanced dynamic TXOP (EDTXOP) scheme is proposed that takes into account all the MAC overheads while estimating current queue size, thereby allocating appropriate dynamic TXOP limits within the pre-setting threshold values. In addition, the article presents an analytical estimation of the EDTXOP scheme to compute the dynamic TXOP limits for the current high priority traffic queues. Simulation results were carried out by varying traffic load in terms of packet size and packet arrival rate. The results show that the proposed EDTXOP scheme achieves the overall performance gains in the range of 4.41%-8.16%, 8.72%-11.15%, 14.43%-32% and 26.21%-50.85% for throughput, PDR, average ETE delay and average jitter, respectively when compared to the existing work. Hence, offering a better TXOP limit allocation solution than the rest.

摘要

传输机会 (TXOP) 是实现无线校园网络 (WCN) 中交互式多媒体 (IMM) 应用高效信道带宽利用的关键因素。它为相似类别的多个数据包传输进行资源分配,直到分配的时间到期。IEEE802.11e 标准为各种类别的 IMM 流量定义了静态 TXOP 限制。由于 WCN 中的流量负载变化,静态 TXOP 限制不足以保证 IMM 流量流的服务质量 (QoS)。为了解决这个问题,一些现有工作根据当前关联队列大小和预设阈值动态分配 TXOP 限制,以确保 IMM 流量的 QoS。然而,现有工作在估计当前队列大小时没有考虑所有介质访问控制 (MAC) 开销,而这是动态 TXOP 限制分配所必需的。因此,不适当考虑 MAC 开销会导致不准确的队列大小估计,从而导致动态 TXOP 限制的不适当分配。本文提出了一种增强的动态 TXOP (EDTXOP) 方案,该方案在估计当前队列大小时考虑了所有 MAC 开销,从而在预设阈值内分配适当的动态 TXOP 限制。此外,本文还提出了一种 EDTXOP 方案的分析估计,以计算当前高优先级流量队列的动态 TXOP 限制。通过改变数据包大小和数据包到达率来改变流量负载,进行了仿真。结果表明,与现有工作相比,所提出的 EDTXOP 方案在吞吐量、PDR、平均 ETE 延迟和平均抖动方面分别实现了 4.41%-8.16%、8.72%-11.15%、14.43%-32%和 26.21%-50.85%的整体性能提升。因此,它提供了比其他方案更好的 TXOP 限制分配解决方案。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cd22/7449386/5d52f160832a/pone.0238073.g011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cd22/7449386/d91a6c6df561/pone.0238073.g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cd22/7449386/ecb7506b3225/pone.0238073.g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cd22/7449386/e8393e65cb76/pone.0238073.g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cd22/7449386/19ee7fccf2b3/pone.0238073.g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cd22/7449386/98319344881b/pone.0238073.g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cd22/7449386/c752a043f69e/pone.0238073.g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cd22/7449386/6d37ac8f0576/pone.0238073.g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cd22/7449386/d9ce43bbcb74/pone.0238073.g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cd22/7449386/c876c1c09332/pone.0238073.g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cd22/7449386/e477fe10b464/pone.0238073.g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cd22/7449386/5d52f160832a/pone.0238073.g011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cd22/7449386/d91a6c6df561/pone.0238073.g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cd22/7449386/ecb7506b3225/pone.0238073.g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cd22/7449386/e8393e65cb76/pone.0238073.g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cd22/7449386/19ee7fccf2b3/pone.0238073.g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cd22/7449386/98319344881b/pone.0238073.g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cd22/7449386/c752a043f69e/pone.0238073.g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cd22/7449386/6d37ac8f0576/pone.0238073.g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cd22/7449386/d9ce43bbcb74/pone.0238073.g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cd22/7449386/c876c1c09332/pone.0238073.g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cd22/7449386/e477fe10b464/pone.0238073.g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cd22/7449386/5d52f160832a/pone.0238073.g011.jpg

相似文献

1
An enhanced dynamic transmission opportunity scheme to support varying traffic load over wireless campus networks.一种增强型动态传输机会方案,用于支持无线校园网络中变化的业务负载。
PLoS One. 2020 Aug 26;15(8):e0238073. doi: 10.1371/journal.pone.0238073. eCollection 2020.
2
GTXOP: a game theoretic approach for QoS provisioning using transmission opportunity tuning.GTXOP:一种使用传输机会调整的基于博弈论的 QoS 配置方法。
PLoS One. 2013 May 1;8(5):e62925. doi: 10.1371/journal.pone.0062925. Print 2013.
3
Traffic Priority Based Channel Assignment Technique for Critical Data Transmission in Wireless Body Area Network.基于流量优先级的无线体域网关键数据传输信道分配技术。
J Med Syst. 2018 Sep 20;42(11):206. doi: 10.1007/s10916-018-1054-y.
4
IDMA-based MAC protocol for satellite networks with consideration on channel quality.基于IDMA的考虑信道质量的卫星网络MAC协议。
ScientificWorldJournal. 2014;2014:181734. doi: 10.1155/2014/181734. Epub 2014 Jul 13.
5
Resource optimization scheme for multimedia-enabled wireless mesh networks.支持多媒体的无线网状网络的资源优化方案
Sensors (Basel). 2014 Aug 8;14(8):14500-25. doi: 10.3390/s140814500.
6
A Fair Contention Access Scheme for Low-Priority Traffic in Wireless Body Area Networks.无线体域网中低优先级业务的公平竞争接入方案。
Sensors (Basel). 2017 Aug 23;17(9):1931. doi: 10.3390/s17091931.
7
Resource allocation for downlink multiuser video transmission over wireless lossy networks.无线有损网络上的下行多用户视频传输资源分配
IEEE Trans Image Process. 2008 Sep;17(9):1663-71. doi: 10.1109/TIP.2008.2001402.
8
An energy-efficient MAC protocol using dynamic queue management for delay-tolerant mobile sensor networks.一种使用动态队列管理的节能 MAC 协议,用于延迟容忍型移动传感器网络。
Sensors (Basel). 2011;11(2):1847-64. doi: 10.3390/s110201847. Epub 2011 Feb 1.
9
Joint congestion and contention avoidance in a scalable QoS-aware opportunistic routing in wireless ad-hoc networks.无线自组织网络中可扩展的 QoS 感知机会路由中的联合拥塞和避免竞争。
PLoS One. 2023 Aug 1;18(8):e0288955. doi: 10.1371/journal.pone.0288955. eCollection 2023.
10
A Preemptive Priority-Based Data Fragmentation Scheme for Heterogeneous Traffic in Wireless Sensor Networks.一种用于无线传感器网络中异构流量的抢占式优先级数据分片方案。
Sensors (Basel). 2018 Dec 17;18(12):4473. doi: 10.3390/s18124473.

引用本文的文献

1
Efficient models for enhancing the link adaptation performance of LTE/LTE-A networks.用于增强LTE/LTE-A网络链路自适应性能的高效模型。
EURASIP J Wirel Commun Netw. 2022;2022(1):10. doi: 10.1186/s13638-022-02091-w. Epub 2022 Feb 2.

本文引用的文献

1
WhatsApp messaging improves communication in an oral and maxillofacial surgery team.WhatsApp 消息传递改善了口腔颌面外科团队的沟通。
Int J Med Inform. 2019 Dec;132:103987. doi: 10.1016/j.ijmedinf.2019.103987. Epub 2019 Oct 1.