QoS-RRC: an overprovisioning-centric and load balance-aided solution for future internet QoS-oriented routing

摘要

The concepts and designs of 4WARD project for the Future Internet involve a clean-slate architecture with various networking innovations, including a new connectivity paradigm called Generic Path (GP). In GP architecture, several facilities are designed to efficiently support complex value-added applications and services with assured Quality of Service (QoS). The GP mainly makes transparent the underlying network structure and heterogeneity, and any entities, regardless of their purpose (technology, location or architectural layer) communicate with each other in a single way via a common interface. In addition, cooperation with network-layer provisioning mechanisms is required to map data paths that are compliant with session-demanded resources (QoS requirements - minimum bandwidth and maximum delay/loss experience) in appropriate GPs. In contrast, robust and scalable QoS-provisioning facilities are urgently required as a support for efficient GP allocations. To address this need, this paper introduces the QoS-Routing and Resource Control (QoS-RRC), a set of GP-compliant facilities to meet the requirements mentioned above. QoS-RRC complements GP architecture with QoS-oriented routing, with the aid of load balancing to select paths that comply with session-demands while keeping residual bandwidth to increase user experience. To address scalability issues, QoS-RRC operates on the basis of an overprovisioning-centric approach to achieve cost-effectiveness in terms of state storage, signaling load and network operations. An initial QoS-RRC performance evaluation was carried out in Network Simulator v.2 (NS-2), which showed that there had been drastic improvements in the flow delay experience and bandwidth use among a range of relevant state-of-the-art solutions. Moreover, the impact of QoS-RRC on the user experience (compared to current IP QoS and routing standards) has been evaluated, by analyzing the main objective and subjective Quality of Experience (QoE) metrics, namely Peak Signal to Noise Ratio (PSNR), The Structural Similarity Index (SSIM), Video Quality Metric (VQM) and Mean Opinion Score (MOS).