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jia xu
Приєднався 22 гру 2013
LLM4Workflow An LLM based Automated Workflow Model Generation Tool
LLM4Workflow An LLM based Automated Workflow Model Generation Tool
Переглядів: 23
Відео
EXPRESS 2.0: An Intelligent Service Management Framework for AIoT Systems in the Edge
Переглядів 94Рік тому
1. School of Computer Science and Technology, Anhui University, Hefei, China; 2. School of Information Technology, Deakin University, Geelong, Australia; 3. Department of Computing Technologies, Swinburne University of Technology, Melbourne, Australia; Special thanks to Ms. Ruo Zhao for dubbing.
EdgeWorkflowReal
Переглядів 1463 роки тому
EdgeWorkflowReal: An Edge Computing based Workflow Execution Engine for Smart Systems.
EXPRESS
Переглядів 2714 роки тому
EXPRESS: An Energy-Efficient and Secure Framework for Mobile Edge Computing and Blockchain based Smart Systems
FogWorkflowSim
Переглядів 1 тис.5 років тому
FogWorkflowSim: An Automated Simulation Toolkit for Workflow Performance Evaluation in Fog Computing Xiao Liu, Lingmin Fan, Jia Xu, Xuejun Li, Lina Gong, John Grundy, Yun Yang 1School of Information Technology, Deakin University, Geelong, Australia 2School of Computer Science and Technology, Anhui University, Hefei, China 3Faculty of Information Technology, Monash University, Melbourne, Austral...
Hi Sir, Can you please post any updates or your recent work using FogWorkflowSim .Thank You for sharing your Knowledge with us.
this video how to install the fog workflowsim ua-cam.com/video/UhSvIOQ1NbY/v-deo.html
Hi, can you please make a detailed video of setting up the code and machines. It would be really helpful for us. Looking forward to your reply. Thank you
Dear, only the Min-Min algorithm is working on all platforms like only Fog, Only Cloud, and Simple. kindly provide a solution, so that all algorithms work on all platforms and could provide different results.
Great work! but after "Drawing iteration figure....." the grarph or figure is not showing up. like you got in 3:18... plz help!!!
How can we simulate PSO in a Multi-Objective way, GUI shows exclusively either Time or Energy or Cost as objective using a radio button.
is this toolkit not running on desktop
can adding of Machine Learning algorithm is feasible in toolkit.
Do you already tried to add machine learning algorithms in offloading, to analyse the time difference on the execution of tasks?
yes, a few baseline algorithms are included, and you can add your own algorithm in the desktop version. We are planning to include a few more advanced offloading algorithms designed by us and others. please stay tuned.
@@xiaoliu7307 would be interesting to configure mobility and location in the configurations of the devices or another metrics, like QoS
very helpful video....i have run simulation..But figure drawing not came..any solution kindly suggest
please visit our online version: www.iseclab.org.cn:8000/FogWorkflowSim
@@jiaxu1258 Graph plotting is visible in online link...as provided by you... but on my laptop graph plotting not occurring...i have also installed matlab...but no solution occurs....only drawing and finished drawing message appeared...but no drawing shown,..kindly suggest suitable suggestion for the same....kindly provide any email id or any contact number...i am research scholar from india...wants to work on the same....
@@gauravgoel4754 please contact @Jia Xu via xujia@stu.ahu.edu.cn
@@xiaoliu7307 Thanks
@@jiaxu1258 Registration link is not working in online link.
This is really helpful for my Master dissertation!
Where can i download the source code of the demo?
@@stevendennis9783 github.com/ISEC-AHU/FogWorkflowSim
new address for Web UI: www.iseclab.org.cn/FogWorkflowSim
The Web UI for FogWorkflowSim can be accessed from here: 47.74.84.61:8080/
The Project Website on Github: github.com/WorkflowSim/WorkflowSim-1.0
延时依然很高，但是很好奇怎样通过拍摄人脸计算得到心率数据的？还有这个案例并没有体现边缘计算的作用
根据人脸视频分析心率有专门的算法，主要是依据脸部血管的收缩变化。这个demo里面边缘节点主要用来做数据预处理，然后将处理后的数据再传到云上进行分析返回结果，从而大幅度减少了直接将视频数据传到云上所耗费的传输时间。感兴趣你可以看下我们的文章COMEC: Computation Offloading for Video-based Heart Rate Detection APP in Mobile Edge Computing - ISPA2018。