Sökning: "network slicing"

Visar resultat 1 - 5 av 10 avhandlingar innehållade orden network slicing.

1. 1. Improving the Adaptability of the End-host : Service-aware Network Stack Tuning

   Författare :Alexander Rabitsch; Anna Brunström; Per Hurtig; Stefan Alfredsson; Michael Welzl; Karlstads universitet; []
   Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; transport layer; 5G; transport services; mobile broadband; network slicing; latency; availability; service optimization; multi-connectivity; Computer Science; Datavetenskap;

   Sammanfattning : The Internet of today is very different from how it used to be. Modern networked applications are becoming increasingly diverse. Consequently, a variety of requirements must be met by the network. Efforts to make the underlying mechanisms of the Internet more flexible have therefore been made to adapt to this diversification. LÄS MER

3. 2. Orchestration Strategies for Slicing in 5G Networks : Design and Performance Evaluation

   Författare :Muhammad Rehan Raza; Paolo Monti; Lena Wosinska; George Rouskas; KTH; []
   Nyckelord :TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; software defined networking; network function virtualization; orchestration; dynamic slicing; 5G; big data analytics; reinforcement learning; Informations- och kommunikationsteknik; Information and Communication Technology;

   Sammanfattning : The advent of 5th generation of mobile networks (5G) will introduce new challenges for the infrastructure providers (InPs). One of the major challenges is to provide a common platform for supporting a large variety of services. LÄS MER

4. 3. Data Driven AI Assisted Green Network Design and Management

   Författare :Meysam Masoudi; Cicek Cavdar; Jens Zander; Muhammad Ali Imran; KTH; []
   Nyckelord :TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; 6G; 5G; Energy efficiency; Machine learning; Reinforcement learning; Network architecture; Sleep modes; Mobile networks; 5G; C-RAN; nätverksarkitektur; nätverksdelning; maskininlärning;

   Sammanfattning : The energy consumption of mobile networks is increasing due to an increase in traffic demands and the number of connected users to the network. To assure the sustainability of mobile networks, energy efficiency must be a key design pillar of the next generations of mobile networks. LÄS MER

5. 4. Ultra-Reliable and Resilient Communication Service for Cyber-Physical Systems

   Författare :Milad Ganjalizadeh; Marina Petrova; Jens Zander; Petar Popovski; KTH; []
   Nyckelord :TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; 5G; availability; cyber-physical systems CPSs ; deep Q-networks DQN ; deep reinforcement learning; distributed learning; machine learning; network slicing; reliability; soft actor-critic SAC ; ultra-reliable low-latency communications URLLC ; wireless communications.; Informations- och kommunikationsteknik; Information and Communication Technology; Datalogi; Computer Science;

   Sammanfattning : Cyber-Physical Systems (CPSs) are becoming ubiquitous in modern society, enabling new applications that rely on the seamless interaction between computing, communication, and physical processes. In this context, ultra-reliable low-latency communications (URLLC) emerges as a crucial element, reliably allowing the real-time exchange of critical data. LÄS MER

7. 5. Distributed Intelligence for IoT Systems Using Edge Computing

   Författare :Ramin Firouzi; Rahim Rahmani; Thashmee Karunaratne; Sadok Ben Yahia; Stockholms universitet; []
   Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; Internet of Things IoT ; Edge Computing; Distributed Intelligence; Software Defined Networking SDN ; Federated Learning; 5G; O-RAN; Network Slicing; Reinforcement Learning; data- och systemvetenskap; Computer and Systems Sciences;

   Sammanfattning : Over the past decade, the Internet of Things (IoT) has undergone a paradigm shift away from centralized cloud computing to edge computing. Hundreds of billions of things are estimated to be deployed in the rapidly advancing IoT paradigm, resulting in an enormous amount of data. LÄS MER