Skip to content

Profit-Driven Pricing and SLA-Aware Reserve Sizing for Multi-Tenant Satellite O-RAN Services

Jul 2026 · arXiv.org · Vol abs/2607.29594 · 0 citations · 15 references
Computer Science Engineering

TL;DR

The proposed approach consistently maintains non-positive empirical SLA gaps and achieves up to $30\% higher resource utilization than a price-optimization baseline without adaptive reserve control.

Abstract

This paper studies a multi-tenant resource allocation problem in a satellite open radio access network (O-RAN) wholesale setting, where heterogeneous traffic classes share a time-varying limited satellite capacity over a finite planning horizon. We formulate a joint pricing and reserve allocation problem from a service provider perspective, where tenant-specific demand exhibits price elasticity and stochastic service requirements subject to strict service-level agreement (SLA) constraints, leading to a coupled economic and reliability-driven bottleneck. A deterministic reformulation is adopted to approximate probabilistic SLA requirements through tractable margin constraints, enabling coordinated control of horizon-wide contract prices and time-varying reserves. The resulting problem is non-convex due to interdependent decisions across tenants, time windows, and service classes. To address this, an alternating optimization (AO) scheme is developed separating pricing and allocation decisions while preserving feasibility and SLA guarantees. Numerical results show that the proposed method achieves near-optimal profit within approximately $1\%$ of a global benchmark, while reducing runtime by up to $22\times$. In contrast, considered baseline schemes incur profit losses exceeding $15\%$ or fail to satisfy SLA constraints. The proposed approach consistently maintains non-positive empirical SLA gaps and achieves up to $30\%$ higher resource utilization than a price-optimization baseline without adaptive reserve control. These results demonstrate that joint economic and resource control enables the provider to efficiently exploit scarce satellite network capacity with reliable service delivery and scalable computation.

View source

Similar papers

Preprint Aug 2026

Joint pricing and matching for dynamic high-capacity ride-sharing considering passengers'choice uncertainty

This work investigates the uncertainty-aware joint pricing and matching problem for dynamic high-capacity ride-sharing services, where passengers are assumed to be price-elastic and decide whether to accept a ride-sharing offer based on the upfront prices provided by the platform. We formulate the studied problem as a...

Wang Chen, Xing-Lu Liu, Kai-Hang Zhang et al. · 0 citations
Open access Aug 2026

Dynamic Zonal Pricing and Vehicle Dispatching for Hub-Based Demand-Responsive Last-Mile Transit Services

Urban passenger hubs, such as airports and railway stations, generate concentrated last-mile demand from arriving passengers to spatially dispersed urban destinations. Fluctuating passenger arrivals and changing vehicle availability can create a mismatch between accepted demand and available service capacity. This pape...

Rong Fu, Hao-Ran Huang, Jingxu Chen et al. · 0 citations
Conference Aug 2026

Discrete Modeling and Combinatorial Optimization for Task Scheduling

This paper investigates centralized scheduling of mobile service agents under staggered multi-wave task arrivals, limited service capacity, service-time windows, and cross-wave capacity reservation requirements. A spatiotemporal candidate-arc representation is developed to discretize the continuous scheduling process,...

Miao Shen, Chuan-Fu Guo, Peng Wang et al. · 0 citations
Open access Sep 2026

A Stochastic Dual Dynamic Programming Approach for Fixed-Route Electric Vehicle Charging under Congestion Uncertainty

Deploying heavy-duty electric trucks under real-world uncertainty is operationally challenging, particularly when multiple vehicles compete for limited public charging resources and face uncertain wait times. This research studies the Fixed-Route Vehicle Charging Problem and formulates it as a multistage stochastic pro...

Zi-Yan Li, Nikolay Aristov, E. Dugundji · 0 citations
Open access Aug 2026

A Study on the Optimization of Site Selection and Capacity Allocation for New Energy Vehicle Swapping Stations in Urban Areas

Urban battery swapping station (BSS) planning is difficult because site opening, service-module allocation, user assignment, battery degradation pressure, travel burden, and congestion are tightly coupled. A plan that minimizes investment alone may create long queues, whereas a plan that only reduces waiting can overbu...

Lin-Wei Hong, Jian Chu, Wen-Kang Zhang · 0 citations

We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.