Planning Computation Offloading on Shared Edge Infrastructure for Multiple Drones

Giorgos Polychronis, S. Lalis
{"title":"Planning Computation Offloading on Shared Edge Infrastructure for Multiple Drones","authors":"Giorgos Polychronis, S. Lalis","doi":"10.1109/ICDCSW56584.2022.00063","DOIUrl":null,"url":null,"abstract":"Drones are used in a wide range of applications, which may involve computationally-demanding data processing tasks during the missions. While such heavy tasks can be offloaded to nearby edge-servers, this may not always be feasible due to capacity limitations and contention. In this case, it is important to have a fair allocation of server resources to drones. We propose a heuristic for this problem, and evaluate it though simulation experiments using realistic performance parameters. We show that the mission time can be greatly reduced, by up to 33% (16 min) compared to the default where drones perform all computations onboard, while evenly balancing the benefits of offloading among drones with different missions.","PeriodicalId":357138,"journal":{"name":"2022 IEEE 42nd International Conference on Distributed Computing Systems Workshops (ICDCSW)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 IEEE 42nd International Conference on Distributed Computing Systems Workshops (ICDCSW)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICDCSW56584.2022.00063","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

Abstract

Drones are used in a wide range of applications, which may involve computationally-demanding data processing tasks during the missions. While such heavy tasks can be offloaded to nearby edge-servers, this may not always be feasible due to capacity limitations and contention. In this case, it is important to have a fair allocation of server resources to drones. We propose a heuristic for this problem, and evaluate it though simulation experiments using realistic performance parameters. We show that the mission time can be greatly reduced, by up to 33% (16 min) compared to the default where drones perform all computations onboard, while evenly balancing the benefits of offloading among drones with different missions.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
多无人机共享边缘基础设施的规划计算卸载
无人机的应用范围很广,在执行任务期间可能涉及对计算要求很高的数据处理任务。虽然这些繁重的任务可以卸载到附近的边缘服务器,但由于容量限制和争用,这可能并不总是可行的。在这种情况下,为无人机公平分配服务器资源是很重要的。我们提出了一种启发式算法,并通过使用真实性能参数的仿真实验对其进行了评价。我们表明,与无人机在机载执行所有计算的默认情况相比,任务时间可以大大减少,最多可减少33%(16分钟),同时在不同任务的无人机之间均衡地平衡卸载的好处。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Holium: A Protocol for Data Transformation Pipelines ROFL: RObust privacy preserving Federated Learning Hyperverse: A High Throughput Pattern Matching Engine for Metaverse Cost-Effective Optimal Multi-Source Energy Management Technique in Heterogeneous Networks Local Model Quality Control Method Based on Credit Mortgage for Enterprise Credit Evaluation
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1