Essays about: "RL-based scheduling"

Found 3 essays containing the words RL-based scheduling.

  1. 1. Machine Learning-Based Instruction Scheduling for a DSP Architecture Compiler : Instruction Scheduling using Deep Reinforcement Learning and Graph Convolutional Networks

    University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Author : Lucas Alava Peña; [2023]
    Keywords : Instruction Scheduling; Deep reinforcement Learning; Compilers; Graph Convolutional Networks; Schemaläggning av instruktioner; Deep Reinforcement Learning; kompilatorer; grafkonvolutionella nätverk;

    Abstract : Instruction Scheduling is a back-end compiler optimisation technique that can provide significant performance gains. It refers to ordering instructions in a particular order to reduce latency for processors with instruction-level parallelism. READ MORE

  3. 2. Energy Sustainable Reinforcement Learning-based Adaptive Duty-Cycling in Wireless Sensor Networks-based Internet of Things Networks

    University essay from Luleå tekniska universitet/Institutionen för system- och rymdteknik

    Author : Nadia Charef; [2023]
    Keywords : Reinforcement Learning; Q-learning; Dynamic Energy Management; Energy Sustainabiltiy; IEEE802.15.4 MAC Protocol; Adaptive Duty Cycling; Wireless Sensors Networks; Internet of Things;

    Abstract : The Internet of Things (IoT) is widely adopted across various fields due to its flexibility and low cost. Energy-harvesting Wireless Sensor Networks (WSNs) are becoming a building block of many IoT applications and provide a perpetual source of energy to power energy-constrained IoT devices. READ MORE

  4. 3. Energy Efficient Communication Scheduling for IoT-based Waterbirds Monitoring: Decentralized Strategies

    University essay from Luleå tekniska universitet/Institutionen för system- och rymdteknik

    Author : Otabek Sobirov; [2022]
    Keywords : TSCH; 6TiSCH; RPL; scheduling; energy consumption; COOJA; autonomous scheduling; distributed scheduling; reinforcement learning; RL-based scheduling; Q-Learning;

    Abstract : Monitoring waterbirds have several benefits, including analyzing the number of endangered species, giving a reliable indication of public health, etc. Monitoring waterbirds in their habitat is a challenging task since the location is distant, and the collection of monitoring data requires large bandwidth. READ MORE