Essays about: "Scheduling Problem"

Showing result 11 - 15 of 220 essays containing the words Scheduling Problem.

  1. 11. Computation Offloading for Real-Time Applications : Server Time Reservation for Periodic Tasks

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

    Author : Lizzy Tengana Hurtado; [2023]
    Keywords : Computation Offloading; Real-Time Applications; Resource Reservation; Beräkningsavlastning; realtidsapplikationer; resursreservation;

    Abstract : Edge computing is a distributed computing paradigm where computing resources are located physically closer to the data source compared to the traditional cloud computing paradigm. Edge computing enables computation offloading from resource-constrained devices to more powerful servers in the edge and cloud. READ MORE

  3. 12. The ecological impact of artificial light at night in landscape architecture : strategies and guidelines for street lights for the benefit of biodiversity and local wildlife

    University essay from SLU/Dept. of Urban and Rural Development

    Author : Zozan Altun; [2023]
    Keywords : light pollution; artificial light at night; ecology; biodiversity; local wildlife; landscape architecture; guidelines; strategies;

    Abstract : Artificial light at night (ALAN) is an increasingly common form of light pollution that contributes to biodiversity loss, loss of dark habitats, disrupting populations both on an individual- and population level by invading biodiversity hot spots. Recent studies show that artificial light is increasing at a rate of approximately 6% annually over Earth’s surface, and 88% of Europe and 47% of the United States experience light pollution on a nightly basis. READ MORE

  4. 13. Improving charging scheduling of public transport electric buses

    University essay from Lunds universitet/Produktionsekonomi

    Author : Franz Bamberg; Anna Hassler; [2023]
    Keywords : Peak load; electricity trading; spot prices; electric buses; bus transport operator; battery energy storage system; charging scheduling; Technology and Engineering;

    Abstract : Title: Improving charging scheduling of public transport electric buses Authors: Anna Hassler & Franz Bamberg Supervisor: Johan Marklund, Lund University Background: This thesis focuses on a Swedish BTO that operates EB fleets. For companies investing in electrification, record-high and volatile electricity prices, present challenges and creates a need to improve the charging scheduling of EBs to reduce costs. READ MORE

  5. 14. 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

  6. 15. The Applicability and Scalability of Graph Neural Networks on Combinatorial Optimization

    University essay from KTH/Matematik (Avd.)

    Author : Peder Hårderup; [2023]
    Keywords : applied mathematics; combinatorial optimization; machine learning; graph neural networks; scalability; tillämpad matematik; kombinatorisk optimering; maskininlärning; grafiska neurala nätverk; skalbarhet;

    Abstract : This master's thesis investigates the application of Graph Neural Networks (GNNs) to address scalability challenges in combinatorial optimization, with a primary focus on the minimum Total Dominating set Problem (TDP) and additionally the related Carrier Scheduling Problem (CSP) in networks of Internet of Things. The research identifies the NP-hard nature of these problems as a fundamental challenge and addresses how to improve predictions on input graphs of sizes much larger than seen during training phase. READ MORE