System-Level Design and Orchestration of Large-Scale Cellular Access Networks for Regulatory-Compliant Financial Services
DOI:
https://doi.org/10.63282/3050-922X.IJERET-V4I3P115Keywords:
Disaggregated cellular architecture, Multi-domain control plane, Cloud-native RAN deployment, Primal–dual control methods, Policy-constrained reinforcement learning, Tail-latency engineering, Telemetry-driven control loops, Time-series demand forecasting, Digital-twin–assisted validation, Privacy-preserving analytics, Network orchestration, Secure financial infrastructure, SLA-aware service assurance, Regulatory-compliant financial services, Edge-to-cloud integrationAbstract
The high pace of computerization of the financial services has radically changed the performance, reliability and compliance standards required of the communication infrastructures. The requirements of financial transactions, algorithm trading systems, digital banking applications, real-time payment systems, distributed ledger frameworks, low latency are of utmost need as well as high availability, high data confidentiality, and regulatory compliance across borders. Cellular access networks on a large scale and, especially, those developed with the 5G or even newer 6G paradigm provide unprecedented flexibility as facilitated by virtualization, disaggregation, and cloud-native orchestration. Nevertheless, the adoption of these networks into regulatory-compliant financial networks brings with it the challenge of complexities at the system level with multi-domain control, service-level agreement (SLA) assurance, privacy-preserving analytics, and deterministic tail-latency management. This paper introduces a mature system-level design and orchestration architecture of the large-scale cellular access network to financial services that are regulatory-compliant. The architecture being proposed combines disaggregated cellular modules, multi-domain control plane, cloud-native Radio Access Network (RAN) deployment and edge-to-cloud integration to make possible secure and SLA-aware service provisioning. The structure uses primal-dual control schemes to optimize under constraints, committee-based reinforcement learning to policy-constrained optimization of the control process, telemetry-based control to respond promptly to market fluctuations in financial markets, and prediction by the time series to anticipate a traffic explosion in response to the fluctuations in the financial market. The architecture is designed with privacy-sensitive analytics, cryptographic isolation, secure enclave-based computation, and digital-twin-assisted validation, whether by enforcing regulatory correctness (such as data residency requirements, auditability requirements, transaction traceability, and privacy regulations).
Under the digital twin environment, simulations in the case of scenario validation, resilience testing, as well as stress analysis with extreme financial workloads, can be performed. Mechanisms for tail-latency engineering are provided to put an upper bound on the 99.999th percentile latency, which high-frequency trading and payment clearing systems can use. The orchestration problem is formulated mathematically as a constrained optimization problem that minimizes the latency and operational cost and subject to compliance, availability, and security constraints. The primal-dual approach will guarantee convergence at the dynamic workloads, whereas reinforcement learning will improve the adaptive choice of the policies within the non-stationary traffic conditions. Closed-loop service assurance Telemetry-based feedback allows corrective orchestration actions to ensure that the service source operates correctly and with continuous monitoring. The proposed framework was shown to achieve 38, 42 and 31 percent improvements in tail-latency, SLA violations, and regulatory audit traceability metric, respectively over the usual centralized RAN architectures, by virtue of the simulation-based validation. The edge deployment solutions also minimize the exposure to cross-border data transfer, which is in line with the financial regulatory requirements. The findings affirm that the cellular access networks can be strategically designed to facilitate mission-evidential financial applications in the event when the orchestration mechanisms are compliance cognizant, latency driven as well as security-focused. The paper offers an integrated architecture model, mathematical program optimization and orchestration strategy between telecommunications engineering and financial regulatory infrastructure design. The suggested solution creates a blueprint of next-generation secure financial connectivity which can use cloud native and edge integrated cellular networks
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