Search Results for author:
Found 6 papers, 1 papers with code
Towards a Dynamic Future with Adaptable Computing and Network Convergence (ACNC)
Hence, this paper presents the concept of Adaptable CNC (ACNC) as an autonomous Machine Learning (ML)-aided mechanism crafted for the joint orchestration of computing and network resources, catering to dynamic and voluminous user requests with stringent requirements.
ORIENT: A Priority-Aware Energy-Efficient Approach for Latency-Sensitive Applications in 6G
Anticipation for 6G's arrival comes with growing concerns about increased energy consumption in computing and networking.
A Semantic-Aware Multiple Access Scheme for Distributed, Dynamic 6G-Based Applications
The emergence of the semantic-aware paradigm presents opportunities for innovative services, especially in the context of 6G-based applications.
QoS-Aware Service Prediction and Orchestration in Cloud-Network Integrated Beyond 5G
The proposed framework adeptly accommodates the dynamic nature of users, the placement of services that mandate ultra-low latency in B5G, and service continuity when users migrate from one location to another.
Double Deep Q-Learning-based Path Selection and Service Placement for Latency-Sensitive Beyond 5G Applications
This paper fills the gap by studying the joint problem of communication and computing resource allocation, dubbed CCRA, including function placement and assignment, traffic prioritization, and path selection considering capacity constraints and quality requirements, to minimize total cost.
Self-Sustaining Multiple Access with Continual Deep Reinforcement Learning for Dynamic Metaverse Applications
The Metaverse is a new paradigm that aims to create a virtual environment consisting of numerous worlds, each of which will offer a different set of services.
