Jul 2026· International Conference on Smart Communications and Networking· pp. 1-6· 0 citations· 17 references
Abstract
The rapid growth of data- and delay-sensitive applications is driving unprecedented mobile traffic demand, straining terrestrial networks (TNs). Integrated Terrestrial-NonTerrestrial Networks (IT-NTNs), envisioned for 6G, aim to expand coverage and enhance capacity via satellite connectivity. Efficient load balancing across TN and NTN domains remains challenging due to inherent heterogeneity between the networks. This paper proposes a QoS-aware load balancing (QALB) algorithm for IT-NTNs. We introduce a congestion-dependent latency model that captures the coupling between latency and resource utilization, embedded in a unified cost function for user-cell association. The resulting load balancing problem is addressed using a distributed heuristic, with simulation results showing that QALB improves network performance in load distribution, throughput, and QoS satisfaction compared to benchmark schemes.
As the telecommunications industry advances towards the realisation of 6G, ubiquitous global coverage has emerged as a key objective. This has driven significant interest in the integration of terrestrial and non-terrestrial networks (ITNTNs), where satellite systems complement terrestrial infrastructure to enable seamless connectivity. However, the global operational scale of satellite systems necessitates cooperation between Low Earth Orbit satellite operators (LEOPs) and local mobile network operators (MNOs), introducing new economic and operational challenges. At the same time, emerging applications are expected to impose strict quality-of-service (QoS) requirements that must be guaranteed across both domains. This paper proposes a QoS-aware tiered pricing framework for supporting users with diverse QoS requirements in an ITNTN. Users are classified into service classes based on empirical traffic characterisation, with each class assigned a dedicated network slice and a target load level linked to QoS guarantees through a queueing-based latency model. The MNO determines class-specific prices that regulate aggregate demand to match these target loads. Numerical results demonstrate that the proposed framework enforces QoS requirements, preserves the desired load hierarchy, and aligns pricing with QoS differentiation, while remaining analytically tractable under heterogeneous user populations.
Simbarashe Tanyanyiwa, O. Falowo· International Conference on...· 0 citations
Mobility Robustness Optimization (MRO) is essential to maintain service continuity, yet its execution often conflicts with Mobility Load Balancing (MLB) functions. While existing literature relies heavily on simulated environments, this paper presents a novel, data-driven, and congestion-aware MRO framework design for live networks. The proposed approach employs multi-vendor capabilities and a five-phase rule-based system to ensure that Handover Control Parameter (HCP) adjustments are grounded in domain-specific knowledge. The framework was deployed in a live network, processing data from over 10,000 cells. Live results show a 19.9% increase in user throughput, a 7.6% decrease in Handover Failures (HOF), and a 36.6% reduction in packet drop rate. Ultimately, this study demonstrates that the proposed framework is highly scalable and adaptive for diverse multi-vendor network environments.
Tiago Faria, João Martins, Sameer Ibraimo et al.· International Conference on...· 0 citations
The increasing demand for higher throughput and lower latency in modern applications has driven the evolution of IEEE 802.11 with the introduction of Wi-Fi 7. The new Extremely High Throughput (EHT) amendment enhances performance with Multi-Link Operation (MLO), allowing concurrent transmissions over multiple frequency links. While MLO improves channel access, reduces latency, and boosts reliability, uneven traffic loads may still cause link congestion, starvation, or collisions, which can severely impact TCP flows. This work investigates the impact of MLO on TCP best effort and video traffic flows, and proposes a Reinforcement Learning (RL) Transmission Opportunity (TXOP) Random Discard strategy for adaptive load balancing. Simulation results demonstrate that the proposed AI-driven approach enhances TCP throughput and latency in Wi-Fi 7 multi-link networks.
Nicola D'Ambra, Ferdinando Marrone, Pasquale Imputato et al.· International Mediterranean...· 0 citations
The rapid evolution of 5G and emerging 6G networks requires optical access systems to support immersive extended reality (XR) services with stringent quality-of-service (QoS) requirements, like ultra-low latency and high bandwidth. However, conventional dynamic bandwidth allocation (DBA) schemes in passive optical networks (PONs) allocate upstream bandwidth solely based on reported queue occupancy, without considering the unique characteristics of XR traffic. To address these limitations, we propose an XR-aware Predictive (XP)-DBA scheme that integrates XR traffic prediction, deadline-aware scheduling, adaptive grant control, and a cycle-controller to proactively allocate bandwidth, prioritize latency-critical packets, and limit polling-cycle growth. We also derive closed-form analytical expressions to characterize XR-specific stability and delay feasibility in PON systems. We evaluate XP-DBA under standardized and burst-enhanced XR traffic models across varying XR user densities and transmission distances of up to 100 km. The results show that XP-DBA will reduce latency, jitter, and polling-cycle time while increasing throughput and supporting higher XR user densities under heavy network loads without violating XR delay bounds. These findings establish XP-DBA as an efficient and scalable scheduling solution for next-generation immersive XR services over long-reach optical access networks.
Akhilesh Patel, Y. Singh· IEEE Transactions on Network...· 0 citations
The integration of Non Terrestrial Networks into 5G and beyond cellular systems has introduced a significant paradigm shift, enabling ubiquitous connectivity and extending services to previously unconnected and underserved remote regions. In particular, Low Earth Orbit satellites, operating close to the Earth surface, can provide communication latency comparable to that of terrestrial networks. However, due to their high mobility, LEO satellites trigger frequent handovers, which degrade users quality of experience and increase signaling overhead. In this work, our objective is to minimize the number of handovers in a LEO satellite system while preventing satellite overloading. We formulate the problem within a game theoretic framework and apply the Spatial Adaptive Play algorithm to obtain a handover efficient and load balanced solution. Additionally, we propose a low complexity heuristic algorithm to achieve similar objectives with reduced computational overhead.
P. Taksande, Jainesh Mehta, P. Chaporkar· 0 citations
As Data Center Networks (DCNs) continue to scale, the limitations of traditional centralized Software-Defined Networking (SDN) architectures become increasingly apparent, as they fail to meet the stringent demands for low latency and quality of service (QoS). In this paper, we propose an adaptive traffic-aware load balancing mechanism (ATL), a telemetrydriven in-switch scheme implemented on the programmable data plane (PDP) using P4 and driven by In-band Network Telemetry (INT). The current traffic regime is inferred by analyzing the remaining capacity (RC) of each link and its short-term variation (VAR), and adopts a dual-optimization strategy: (i) separating elephant flows (large flows) and mice flows (small flows) onto disjoint path sets to mitigate head-of-line blocking and packet reordering; (ii) dynamically adjusting the flowlet threshold $\left(F^{*}\right)$ to strike a balance between maximizing parallelism and ensuring in-order delivery. We prototyped and evaluated ATL in a Mininet/BMv2 environment, targeting bandwidth-constrained scenarios representative of IoT and edge deployments. The results show that, compared to existing methods such as ECMP, HULA, AWCMP, and APS, ATL consistently reduces both the average and 99th-percentile AFCT while achieving superior elephant-flow throughput, with notable improvements in traffic stability and packet-ordering preservation. Furthermore, ATL demonstrates a favorable cost-performance trade-off ratio of 1:0.99, confirming its efficiency and feasibility within the resource-constrained P4 switch environment.