🤖 AI Summary
Existing simulation tools struggle to accurately model systems that integrate passive optical networks (PON) with edge computing, hindering early-stage design efficiency. This work proposes a hierarchical simulation platform tailored for PON-enabled edge infrastructure, offering the first fine-grained modeling of optical line terminals (OLTs) and optical network terminals (ONTs) as edge nodes. Built on an event-driven architecture, the platform incorporates hybrid virtualization using containers and virtual machines, supports multi-service execution models, and features configurable resource management policies, enabling comprehensive evaluation of strategies in complex heterogeneous scenarios. Validation through industry-relevant use cases demonstrates that the platform effectively supports critical decision-making tasks such as capacity planning, container placement, and task offloading in PON-based edge systems.
📝 Abstract
The convergence of Passive Optical Networks (PONs) and edge computing creates new opportunities: Optical Line Terminals (OLTs) and Optical Network Terminals (ONTs) can be repurposed as low-latency edge compute nodes for offloading workloads. However, exploring such design options early in the development cycle is costly and time-consuming, as prototyping requires specialized hardware and realistic traffic conditions. Simulation becomes essential, yet current tools are unable to accurately model this emerging class of systems. To address these gaps, we introduce GenioSim, a simulation platform for hierarchical PON-enabled edge infrastructures. It models OLTs and ONTs with realistic PON behavior, supports hybrid container- and VM-based virtualization, and provides multiple service and execution models. These capabilities enable the evaluation of resource management policies under complex, heterogeneous conditions. We present experiments in the context of use cases of industrial relevance, to show GenioSim can provide insights for capacity planning and for the choice of policies for container placement and task offloading in PON-enabled edge infrastructures.