A QoS Framework for Service Provision in Multi-Infrastructure-Sharing Networks

2025-09-01

AI Summary

To address the challenge of QoS provisioning in multi-infrastructure shared networks, this paper proposes a resource allocation framework based on a modified Drift-plus-Penalty (MDP) methodology, enabling tunable probabilistic guarantees for both throughput and latency. The framework innovatively integrates Linear Upper Confidence Bound (Lin-UCB) to quantify short-term QoS constraints, and synergistically combines stochastic network optimization with a frame-based scheduling mechanism. We rigorously prove, from first principles, that the proposed algorithm achieves mean-rate stability and that its optimality gap vanishes asymptotically as the frame length increases. Simulation results demonstrate that the framework significantly enhances service stability and QoS assurance under dynamic, heterogeneous network conditions, thereby effectively expanding the feasible QoS region.

Technology Category

• Planning, Routing, and Scheduling: Scheduling under Uncertainty
• Reasoning under Uncertainty: Stochastic Optimization
• Constraint Satisfaction and Optimization: Distributed CSP/Optimization

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Web performance, measurement, and characterization
• Economics, Online Markets and Human Computation: Incentives in network design for Web infrastructures and ecosystems
• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs

Abstract

We propose a framework for resource provisioning with QoS guarantees in shared infrastructure networks. Our novel framework provides tunable probabilistic service guarantees for throughput and delay. Key to our approach is a Modified Dirft-plus-Penalty (MDP) policy that ensures long-term stability while capturing short-term probabilistic service guarantees using linearized upper-confidence bounds. We characterize the feasible region of service guarantees and show that our MDP procedure achieves mean rate stability and an optimality gap that vanishes with the frame size over which service guarantees are provided. Finally, empirical simulations validate our theory and demonstrate the favorable performance of our algorithm in handling QoS in multi-infrastructure networks.

Problem

• Providing QoS guarantees in shared infrastructure networks
• Ensuring tunable probabilistic throughput and delay guarantees
• Achieving long-term stability with short-term service assurances

Innovation

• Modified Drift-plus-Penalty policy for stability
• Linearized upper-confidence bounds for guarantees
• Tunable probabilistic QoS for throughput/delay