An Efficient and Innovative Edge Intelligence-Driven Latency-Aware Wireless Network Slicing Framework for Next-Generation Smart Cities

Dr. V Subrahmanyam, Dr. M. V. Siva Prasad

Abstract: The rapid proliferation of smart city applications, ranging from autonomous transportation and remote healthcare to immersive augmented reality and large-scale IoT deployments, demands wireless networks capable of providing ultra-low latency, high reliability, and dynamic adaptability. Traditional cloud-centric architectures often fail to meet these stringent requirements due to inherent latency bottlenecks, resource contention, and limited scalability. To address these challenges, this paper proposes an efficient and innovative edge intelligence?driven latency-aware wireless network slicing framework specifically designed for next-generation smart city ecosystems. The proposed framework integrates edge intelligence with network slicing to create application-specific virtualized network environments, each tailored to meet unique quality-of-service (QoS) demands. By embedding machine learning?based predictive analytics at the network edge, the system proactively identifies latency-critical tasks, optimizes resource allocation, and ensures seamless adaptation to dynamic workloads. Furthermore, the latency-aware design incorporates real-time monitoring and adaptive slice orchestration, allowing the network to balance throughput, latency, and reliability without compromising scalability. Experimental evaluations demonstrate that the framework significantly reduces end-to-end latency, enhances slice utilization efficiency, and improves service-level agreement (SLA) adherence compared to conventional cloud-centric and static slicing approaches. Results highlight up to a 40?60% improvement in latency reduction and a notable increase in resource utilization efficiency, making the proposed system highly suitable for mission-critical smart city applications. This work establishes a foundation for next-generation wireless network infrastructures by merging edge intelligence, adaptive orchestration, and latency-aware slicing, thereby enabling sustainable, resilient, and intelligent smart cities. Future research will focus on extending the framework with block chain-enabled security, cross-domain slice federation, and green energy-aware orchestration for holistic smart city deployments.

Keywords: Edge Intelligence, Wireless Network Slicing, Latency-Aware Networks, Smart Cities, Quality of Service (QoS), Edge Computing, 5G/6G Networks, Resource Optimization, Service-Level Agreements (SLA), Intelligent Orchestration

How to Cite?: Dr. V Subrahmanyam, Dr. M. V. Siva Prasad, "An Efficient and Innovative Edge Intelligence-Driven Latency-Aware Wireless Network Slicing Framework for Next-Generation Smart Cities", Volume 14 Issue 9, September 2025, International Journal of Science and Research (IJSR), Pages: 1013-1017, https://www.ijsr.net/getabstract.php?paperid=SR25921171753, DOI: https://dx.doi.org/10.21275/SR25921171753