On Network-Aware Semantic Communication and Edge-Cloud Collaborative Intelligence Systems
Murdadha Nasif, Ahmed Refaey Hussein

TL;DR
This survey reviews recent advances in semantic communication and edge-cloud collaborative intelligence, emphasizing system architectures, adaptive encoding, and operational challenges for next-generation AI-enabled networks.
Contribution
It provides a comprehensive synthesis of semantic communication techniques at the edge-cloud interface, integrating architectural models, learning methods, and operational considerations.
Findings
Semantic communication enables adaptive tradeoffs among resources and accuracy.
Network-aware and resource-adaptive encoding strategies improve efficiency.
Identifies open challenges and future research directions in the field.
Abstract
Semantic communication and edge-cloud collaborative intelligence are increasingly recognized as foundational enablers for next-generation intelligent services operating under stringent bandwidth, latency, and resource constraints. By shifting the communication objective from bit-perfect delivery toward the transmission of task-relevant semantic representations, semantic communication enables adaptive tradeoffs among communication overhead, inference accuracy, computational load, and end-to-end latency. This survey provides a comprehensive and system-level synthesis of recent advances in semantic communication at the edge-cloud interface, encompassing architectural models for collaborative intelligence, representation learning and semantic abstraction techniques, network-aware and resource-adaptive semantic encoding strategies, and learning-driven optimization and orchestration…
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Taxonomy
TopicsIoT and Edge/Fog Computing · Software-Defined Networks and 5G · Big Data and Digital Economy
