Multi-Objective Privacy-Preserving Function Placement in an Edge-Cloud FaaS Marketplace

Abstract

The shift toward modular microservices has driven the success of serverless Function-as-a-Service (FaaS) as a way to offload infrastructure management. However, meeting the diverse needs of emerging applications—from ultra-low latency control to budget-constrained processing—requires FaaS to transcend centralized clouds and span the edge-cloud continuum. Yet, this introduces two challenges: orchestrating diverse user demands across heterogeneous capabilities and protecting sensitive requests from the underlying infrastructure. We propose a Privacy-Preserving FaaS Marketplace using decentralized orchestration agents. Providers autonomously trade function offers, enabling multi-objective placement that dynamically satisfies strict user QoS constraints. Crucially, Paillier homomorphic encryption blinds function identifiers during resolution to preserve client privacy. Simulations demonstrate our system improves on traditional latency-minimizing FaaS gateways by optimizing placement and proactively shielding clients from SLA violations. Results validate seamless orchestration in the Edge-Cloud continuum while enabling key trade-offs between agent state aggregation, function placement accuracy, and network overhead.