Please note: This seminar will be given online.
Aiman Erbad, College of Science and Engineering
Hamad Bin Khalifa University
Topics covered: Blockchain and machine learning
Smart Contracts (SCs), which are software programs that run on blockchain platforms, provide appealing security guarantees characterized by decentralized, autonomous, and verifiable execution. On the other hand, various blockchain-powered systems (e.g., IoT Monitoring and Service Provisioning) have been leveraging SCs to provide trust and transparency features. Such features are obtained by deploying the application logic and control decisions as SCs on the blockchain. However, on its own the SCs do not guarantee the best performance over time since the blockchain prices vary and system participants join and leave flexibly, and their load varies with time, potentially deeming the initial decisions sub-optimal. Furthermore, modifying the criteria manually by a third party at every variation in the blockchain jeopardizes the autonomous and independent execution promised by SCs. Thus, we propose the use of online learning “rational” SCs that leverage the chained data to continuously self-tune their operations and maintain maximum utility. We utilize a reinforcement learning agent to optimize the blockchain-powered system in two applications: IoT monitoring and peer-to-peer service provisioning. Results based on the Ethereum protocol show significant potential cost saving depending on system conditions and users’ preferences.
Aiman Erbad is an Associate Professor at the College of Science and Engineering at Hamad Bin Khalifa University (HBKU). He obtained a PhD in Computer Science from the University of British Columbia (Canada), an MSc of Computer Science in Embedded Systems and Robotics from the University of Essex (UK), and a BSc in Computer Engineering from the University of Washington, Seattle. He received the 2020 best research paper award from Computer Communications, IWCMC 2019 best paper award, and IEEE CCWC 2017 best paper award. His research interest spans cloud computing, edge computing, IoT, distributed AI algorithms, and private / secure networks.
To join this talk on Zoom, please go to https://zoom.us/j/91818163702.
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