INTELLIGENT NETWORK SLICE ORCHESTRATION FOR EDGE–CLOUD ARCHITECTURES USING HYBRID SWARM OPTIMIZATION
DOI: https://doi.org/10.65725/JCISE/2/2/006
JOURNAL OF COMPUTATIONAL INTELLIGENCE SCIENCE AND ENGINEERING (JCISE)
ISSN: 3107-8168
Volume 2 Issue 2, Apr-Jun 2026

Abstract: 
The rapid growth of distributed applications, Internet of Things (IoT) devices, and latency-sensitive services has significantly increased the demand for intelligent resource management in edge–cloud computing environments. Traditional static orchestration mechanisms are inadequate for handling dynamic network conditions, heterogeneous workloads, and quality-of-service (QoS) requirements. To address these challenges, this study proposes an intelligent network slice orchestration framework for edge–cloud architectures using hybrid swarm optimization techniques. The proposed model integrates swarm-based optimization approaches to dynamically allocate computational and networking resources across distributed edge and cloud infrastructures. The framework aims to improve slice utilization efficiency, reduce latency, optimize bandwidth consumption, and enhance overall service performance. Simulation-based evaluation demonstrates that the proposed approach achieves improved orchestration efficiency and better QoS metrics compared with conventional resource allocation methods. The study highlights the potential of hybrid swarm intelligence in enabling adaptive and scalable orchestration for next-generation distributed computing systems.

Authors: Yuvaraj Gandhi S, Revathi T

Keywords: Edge–Cloud Computing, Network Slicing, Swarm Intelligence, Resource Orchestration, QoS Optimization, Distributed Computing.