|   | 1 | Project Title: Resilient Edge-Cloud Autonomous Learning with Timely inferences | 
          
          
            |   | 2 | Project Advisor and Mentors: Professor Anand Sarwate, Professor Waheed Bajwa, Nitya Sathyavageeswaran, Vishakha Ramani, Yu Wu, Aliasghar Mohammadsalehi, Muhammad Zulqarnain | 
          
          
            |   | 3 | Names: Shreya Venugopaal, Haider Abdelrahman, Tanushree Mehta, Lakshya Gour, Yunhyuk Chang | 
          
          
            |   | 4 |  | 
          
          
            |   | 5 |  | 
          
          
            |   | 6 | Objective: The purpose of this project is to use ORBIT in order to  | 
          
          
            |   | 7 |  | 
          
          
            |   | 8 | Main objectives | 
          
          
            |   | 9 | learn how to design and run experiments on ORBIT | 
          
          
            |   | 10 | prototype a handoff scheme for ML prediction | 
          
          
            |   | 11 | develop a latency profiling framework for MEC-assisted machine learning | 
          
          
            |   | 12 |  | 
          
          
            |   | 13 | – Split the network, early exit, simulate multiple CPU speeds, network delays | 
          
          
            |   | 14 |  | 
          
          
            |   | 15 | Progress | 
          
          
            |   | 16 | Goals | 
          
          
            |   | 17 | Team introductions | 
          
          
            |   | 18 | Kickoff meetings | 
          
          
            |   | 19 | Refining and understanding research questions | 
          
          
            |   | 20 | go over goals for the summer | 
          
          
            |   | 21 | For next week: | 
          
          
            |   | 22 | Go through WINLAB orientation (TBD) | 
          
          
            |   | 23 | Reading for next time: | 
          
          
            |   | 24 | PPA Chapters 1 and 2 | 
          
          
            |   | 25 | Coding: | 
          
          
            |   | 26 | install python (via Anaconda or something else) | 
          
          
            |   | 27 | go through the interactive intro to python online or by downloading the notebook | 
          
          
            |   | 28 | Review the basics of Python linked from the UT Austin site to learn basic syntax, flow control, etc. | 
          
          
            |   | 29 | Week 2: | 
          
          
            |   | 30 | Goals: | 
          
          
            |   | 31 | Summary:  | 
          
          
            |   | 32 | Basics of pattern recognition and Machine Learning (PPA - Patterns, Predictions, Actions) | 
          
          
            |   | 33 | set up an instance using pytorch on an Orbit node | 
          
          
            |   | 34 | Created a node image with Pytorch | 
          
          
            |   | 35 | Basics of Pytorch | 
          
          
            |   | 36 | Created small Machine Learning models | 
          
          
            |   | 37 | Loaded the Modified National Institute of Standards and Technology (MNIST) database onto the node | 
          
          
            |   | 38 | computed the second moment matrix | 
          
          
            |   | 39 | Did PCA and SVM on MNIST | 
          
          
            |   | 40 | Next Steps: | 
          
          
            |   | 41 | Create and train a “small” and “large” Neural Network  | 
          
          
            |   | 42 | Attempt to simulate the difference between their performances at inference | 
          
          
            |   | 43 | Links: | 
          
          
            |   | 44 | Week 3: | 
          
          
            |   | 45 | Goals: | 
          
          
            |   | 46 | Summary:  | 
          
          
            |   | 47 | Created and Trained a ‘Small’ and ’Large’ Neural Networks | 
          
          
            |   | 48 | Compared their performances on the CIFAR10 dataset | 
          
          
            |   | 49 | Established connection between two nodes  | 
          
          
            |   | 50 | Communicated test data between nodes to compare accuracy and delay between our NN models | 
          
          
            |   | 51 | Need to serialize by bytes instead of transferring as strings | 
          
          
            |   | 52 | Had a discussion on various research papers related to our project | 
          
          
            |   | 53 | Next Steps: | 
          
          
            |   | 54 | Send the data as bytes instead of strings | 
          
          
            |   | 55 | Calculate the times for transfer & processing | 
          
          
            |   | 56 | Read more papers related to stuff about early exit and edge cloud computing | 
          
          
            |   | 57 | Divide data into “chunks” for faster and more efficient transmission | 
          
          
            |   | 58 | Design experiments to test different architectures and implementations of Early Exiting and Split Computing | 
          
          
            |   | 59 | Track and add Age of Information Metrics | 
          
          
            |   | 60 | Presentation links:  | 
          
          
            |   | 61 | Link - Lakshya | 
          
          
            |   | 62 | Link - Shreya | 
          
          
            |   | 63 | Link - Haider | 
          
          
            |   | 64 | Link - James | 
          
          
            |   | 65 | Link - Tanushree | 
          
          
            |   | 66 | Week 4: | 
          
          
            |   | 67 | Goals | 
          
          
            |   | 68 | Summary | 
          
          
            |   | 69 | Next Steps | 
          
          
            |   | 70 |  |