Cloud-Network Collaborative Architecture Design and Performance Optimization Based on SRv6 and Intent-Driven Approach

Optimizing Next-generation Cloud and Data Center Networks: A Review of Routing, Resource Management, and Emerging Technologies

A structured review of optimization models in cloud and data center environments using a Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guided methodology covering literature from 2016 to 2025 reveals that the adaptive methods can improve throughput, reduce latency, and enhance energy efficiency under specific datasets, simulation settings, traffic models, and network configurations.

Intelligent Placement of 5G Network Functions on Edge-Based Infrastructures

A constrained optimization model that supports different management goals through alternative objective functions (latency-aware or power-aware) while enforcing operational constraints, including node capacities, slice-specific latency bounds, and explicit limits on VNF migrations/relocations between scheduling periods is proposed.

Energy-Aware Digital Twin Allocation with LLMs for Adaptive Resource Management in Cloud-Native Infrastructures

This work proposes an adaptive resource allocation framework that leverages Digital Twins for real-time system monitoring and integrates Large Language Models to support context-aware decision-making under multi-objective constraints, enabling intelligent workload orchestration across heterogeneous data center environments.

A Deep Reinforcement Learning Framework for Scalable Cloud Service Orchestration

Performance-optimized Opportunistic Routing with Temporal-spatial Awareness and Collaborative Caching

— Opportunistic networks enable communication in infrastructure-deficient scenarios such as IoT deployment and disaster rescue through node mobility. However, existing routing protocols relying solely on contact frequency neglect link duration, leading to unstable transmission and inefficient caching. This paper proposes PORTAC, a historical contact–enhanced collaborative cache routing mechanism integrating contact stability–aware routing and multi-level cache scheduling. A spatio-temporal Contact Stability Index (CSI) evaluates link quality via duration-based logarithmic gain and historical context, while a core–radiation–edge cache hierarchy manages messages by value, forwarding count, and lifetime. Simulations on the ONE platform show that PORTAC increases delivery ratio by over 10.6% compared with PropheRouter, enhancing efficiency in dynamic networks.

Proximal Policy Optimization for Latency-Aware Service Function Chain Placement in Edge-Enabled Networks

This work proposes an enhanced Proximal Policy Optimization (PPO) framework for resource-aware and latency-sensitive SFC placement in edge-enabled networks, and demonstrates the applicability of the proposed framework in mission-critical and latency-sensitive service environments.