Essays about: "routing features"

Showing result 1 - 5 of 33 essays containing the words routing features.

  1. 1. Estimating Poolability of Transport Demand Using Shipment Encoding : Designing and building a tool that estimates different poolability types of shipment groups using dimensionality reduction.

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

    Author : Marvin Kërçini; [2023]
    Keywords : Poolability; Transport networks; Autoencoder; Dimensionality reduction; Vehicle Routing Problem; Raggruppabilità; Reti di trasporto; Autoencoder; Riduzione della dimensionalità; Vehicle Routing Problem; Poolbarhet; Transportnätverk; Autokodare; Dimensionsreduktion; Fordonsdirigeringsproblem;

    Abstract : Dedicating less transport resources by grouping goods to be shipped together, or pooling as we name it, has a very crucial role in saving costs in transport networks. Nonetheless, it is not so easy to estimate pooling among different groups of shipments or understand why these groups are poolable. READ MORE

  3. 2. BGPcredit : A Blockchain-based System for Securing BGP

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

    Author : Yu Yang Liu; [2022]
    Keywords : blockchain; RPKI; consensus algorithm; border gateway protocol; security; blockchain; RPKI; konsensusalgoritm; border gateway-protokoll; säkerhet;

    Abstract : Due to the absence of appropriate security mechanisms, even the latest version of Board Gateway Protocol (BGP) is still highly vulnerable to malicious routing hijacking. The original problem is that BGP allows router to accept any BGP update message without any extra validation process. READ MORE

  4. 3. Material Handling by Automated Guided Vehicle System Using Discrete-Event Simulation : A case study at Autoliv, Thailand

    University essay from Högskolan Väst/Institutionen för ingenjörsvetenskap

    Author : Samuel Abishek Joseph Peter; [2022]
    Keywords : Discrete Event Simulation; AGV routing; scheduling; AGV models; positioning and dispatching;

    Abstract : A case study for this project is performed at Autoliv in Thailand the company uses a lean production flow approach. This manufacturing plant operates on the level of Industry 3.0, which automates processes using information technology. The case study scenario in manufacturing plants that runs in industrial automation 3. READ MORE

  5. 4. Individualized Pedestrian and Micromobility Routing Incorporating Static and Dynamic Parameters

    University essay from Linköpings universitet/Kommunikations- och transportsystem; Linköpings universitet/Tekniska fakulteten

    Author : Adam Grachek; [2021]
    Keywords : shortest path; pedestrian; micromobility; routing demonstrator; routing features;

    Abstract : This project seeks to demonstrate routing optimization that would allow pedestrian and micromobility user groups to select and prioritize different route features according to their preferences. Through the creation of a routing demonstrator that considers both static and dynamic parameters in the form of pavement quality, elevation climb, travel time, and air quality, along with user-specified weights for their prioritization of each of these parameters, a number of routes were created and mapped to qualitatively compare against routes representing only a shortest path. READ MORE

  6. 5. Machine Learning Modeling using Heterogeneous Transfer Learning in the Edge Cloud

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

    Author : Fernando Garcia Sanz; [2021]
    Keywords : Deep learning; Edge cloud; Heterogeneous transfer learning; Machine Learning; Service performance; ; Deep learning; Edge cloud; heterogen överföringsinlärning; maskininlärning; serviceprestanda; ;

    Abstract : The dynamic nature of the edge cloud and future network infrastructures is another challenge to be added when modeling end-to-end service performance using machine learning. That is, a model that has been trained for one specific environment may see reductions in prediction accuracy over time due to e.g., routing, migration, or scaling decisions. READ MORE