2026· IEEE Transactions on Network and Service Management· Vol 23, pp. 6536-6549· 0 citations· 32 references
Abstract
Space-air-ground integrated networks (SAGINs) offer seamless three-dimensional coverage and strengthened flexibility, which are recognized as a core network architecture of 6G. Software-defined networking (SDN) and network function virtualization (NFV) are two enabling technologies for SAGINs that can be utilized to sequentially arrange virtual network functions (VNFs) into service function chains (SFCs) to provide users with resource-efficient and delay-optimized multi-source multicast request (MMR) services. However, SAGINs exhibit significant dynamism and heterogeneity, it brings great challenges when dynamically deploying the MMR’s source nodes and SFCs for fulfilling MMR routing. This paper investigates the multi-source multicast SFC embedding problem (MMSEP) considering the determination of the source nodes for MMR, VNFs placement, as well as network resources and delay constraints in the SDN/NFV-enabled SAGIN. Firstly, we define and formulate the MMSEP and demonstrate its NP-hardness. Subsequently, we employ a heuristic algorithm to assign the optimal source nodes for all multicast destination nodes and utilize the markov decision process (MDP) to simulate dynamic transitions in network states. Finally, we propose a deep deterministic policy gradient with attention mechanism (DDPG-AM) to address the MMSEP, aiming to minimize resource consumption costs and delays while maximizing the revenue of the internet service provider. The simulation results demonstrate that the proposed algorithm surpasses the state-of-the-art DDPG algorithm by approximately 27% in network utility, 17% in latency reduction, and 5% in acceptance ratio.
The rapid evolution of beyond-5G and emerging 6G networks is driving the need for flexible, reliable, and cost-efficient virtualized Radio Access Network (vRAN) architectures capable of supporting heterogeneous services such as enhanced Mobile Broadband (eMBB), Ultra-Reliable Low-Latency Communication (URLLC), and Massive Machine-Type Communication (mMTC). Future disaggregated RAN systems are expected to rely heavily on network slicing, functional split flexibility, and optical x-haul infrastructures to support stringent performance, scalability, and availability requirements. In this paper, we present an integrated framework for reliable, slice-aware, and functional split-aware Virtual Network Function (VNF) placement with lightpath provisioning in disaggregated vRAN environments. The proposed approach maximizes mobile network operators'profit by jointly optimizing function placement and optical resource allocation under latency, processing, bandwidth, and availability constraints. We formulate the problem as an Integer Linear Programming (ILP) model with two variants: one that employs unshared backups and another that uses a more cost-efficient shared backup scheme. To address ILP complexity, we develop a heuristic algorithm and a Genetic Algorithm (GA)-based metaheuristic that yields near-optimal solutions in real time. Extensive evaluations on topologies up to 128 nodes show that shared backup variants yield up to 18% higher profit, while maintaining up to 5-10% lower normalized CPU usage than unshared counterparts.
Mayank Ramnani, Shasank Dixit, Sushil K. Yadav et al.· 0 citations
Network function virtualization (NFV) decouples network functions from dedicated hardware by implementing them as software-based virtual network functions (VNFs), thereby enabling flexible network resource management. Network services are provisioned through service function chains (SFCs) composed of multiple VNFs. Given SFC requests and physical machines (PMs), this paper investigates the VNF deployment problem with three objectives: maximizing the service acceptance ratio (SAR), minimizing the total energy consumption (TEC), and balancing the load among PMs. We then propose a load-aware and energyefficient VNF deployment (LEEV) scheme that dynamically adapts its deployment strategy based on the system load. Under lightload conditions, LEEV deploys adjacent VNFs of a given SFC on one PM to reduce energy consumption, while under heavy-load conditions, it can shift toward load-balancing deployment without sacrificing energy efficiency. Simulation results reveal that LEEV achieves a higher SAR, lower TEC, and improved load balance.
You-Chiun Wang, Pei-Chin Tsai· International Conference on...· 0 citations
The development of immersive video service and large-scale cluster computing technology further expand the potential application scope of time-sensitive networks (TSN). In the delivery network for these emerging services, Ultra-Service Flows (USFs), characterized by ultra-high bandwidth and deterministic latency, have become the most representative traffic type. Therefore, the route scheduling for hybrid deployment of Regular-Service Flows (RSFs) and USF has become an unavoidable issue within a deterministic domain. However, existing research has not thoroughly investigated routing issues for the hybrid deployment of USF and RSF since the significant differences between them. To resolve this issue, a multi-objective optimization model is designed in this paper, in which three key factors are comprehensively considered: the path blocking degree of USF, the available bandwidth rate, and the end-to-end latency of RSF. Subsequently, we propose a cooperative framework where a Transformer-DRL agent, enforced by validity-constraint masking, generates high-quality initial populations to “warm start” NSGA-II. This hybrid design replaces random initialization, effectively resolving the evolutionary “cold start” issue in large-scale topologies while ensuring routing feasibility. The simulation results demonstrate that the algorithm proposed here in significantly improves performance and generalization capabilities, improving the RSF’s overall latency, the USF’s path-blocking degree, and the available bandwidth rate by 10.526%, 14.102%, and 14.286%, respectively.
Mengjie Guo, Qiang Wu, Ran Wang et al.· IEEE Transactions on Network...· 0 citations
The proliferation of applications and multimedia services has led users to demand more bandwidth while limiting access time to the target content. The current 5G specifications provide mechanisms to support these challenging requirements by leveraging both the slicing paradigm, which enables the allocation of network resources with dedicated Quality of Service (QoS), and the Multi-Access Edge Computing (MEC), bringing content as close as possible to end users. Two additional key enablers can further improve user experience: the 5G non-3GPP access and the use of Non-Terrestrial Networks (NTN). The former could extend the overall coverage by exploiting legacy technologies, largely deployed, such as Wi-Fi, which can also avoid frequency license issues in many cases. The latter represents the most efficient solution to support multicast/broadcast content distribution towards the edges of the network. These key enablers are addressed in the ESA 5G-EMERGE project, where 5G, satellite broadcasting, and a Content Delivery Network (CDN) are integrated to efficiently deliver IP-based multimedia services. In this framework, the contribution of this paper is to describe the innovative reference architecture and technologies proposed in 5G-EMERGE, focusing on the implementation and validation of a non-3GPP edge component compliant with the 5G MEC architecture, leveraging NTN as backbone, interworking with a commercial 5G core network, and providing support for QoS enforcement and multicast delivery. The experimental results demonstrate the effectiveness of the proposed solution in terms of both delay reduction and bandwidth optimization.
D. Verde, C. Roseti, F. Zampognaro et al.· International Conference on...· 0 citations
Fifth-generation (5G) and time-sensitive networking (TSN) are widely recognized as the most promising technologies for future industrial networks. Quality of service (QoS) mapping and traffic scheduling mechanisms are critical to ensuring deterministic transmission in 5G-TSN integrated networks. However, the uncertainty of 5G air-interface delay significantly reduces the deterministic guarantee for traffic in 5G-TSN networks. A QoS mapping algorithm based on incremental mini-batch K-means++ stratified sampling (IMK-S3) is proposed to quickly and accurately determine the 5G QoS identifier (5QI) values of traffic flows, even under dynamic traffic variations. Based on this, combined with cross-layer scheduling optimization, a QoS-mapping-based no-wait latency-balanced joint scheduling (QMLB-JS) algorithm is proposed. QMLB-JS supports hold and forward buffer mechanism in DS-TT and NW-TT, and realizes accurate time-based gating management by orchestrating the time of time-triggered (TT) traffic injection into the network. Simulation results demonstrate that the proposed algorithm improves the end-to-end deterministic transmission capability of the integrated 5G-TSN network.
He Li, Shihui Duan, Fangmin Xu et al.· IEEE Open Journal of the Com...· 0 citations
Civil aviation space-air-ground integrated networks (SAGINs) are expected to support heterogeneous cockpit and cabin services over dynamic air-to-air (A2A), air-to-ground (A2G), and air-to-satellite (A2S) data links. This paper studies service function chain (SFC)-aware online access-side aggregated data-link orchestration for civil aviation SAGINs enabled by software-defined networking and network function virtualization (SDN/NFV). We jointly orchestrate spatial bearer resources and temporal elasticity enabled by temporal elastic mapping and parking (TEMP). A rolling-slot model is developed with four request-level actions: NOW, TEMP, REJECT, and DROP, under a lexicographic objective that prioritizes service success, then normalized access-orchestration delay, and finally residual TEMP-related risk. To avoid exhaustive search over the full binary action space, we propose Model-Induced Risk and Scarcity-Aware Refinement (MRSAR), which derives deferred-realization risk from the success-prioritized objective and resource-scarcity signals from data-link and TEMP buffer constraints. These signals guide valuation-based feasible construction and bounded neighborhood refinement. Simulation results show that MRSAR remains close to the Gurobi-MILP reference in service success, outperforms arrival-order and delay-myopic greedy baselines, controls REJECT and DROP failures, and achieves a favorable quality-complexity tradeoff for rolling online orchestration.