ISP-Friendly P2P Rate Allocation via Utility Optimization
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Solution Overview
Problem
The increasing demand for high-quality Internet video-on-demand services puts significant pressure on traditional server-based infrastructures, leading to high costs and potential failures, while peer-to-peer (P2P) networks can reduce this burden but often incur ISP-unfriendly traffic, increasing costs for Internet Service Providers (ISPs) and ultimately affecting users with higher prices.
Innovation Solution
An ISP-friendly rate allocation system that operates at the packet level, using techniques such as utility function optimization and minimum cost flow formulation to allocate bandwidth, minimizing server load, ISP-unfriendly traffic, and maximizing peer prefetching, thereby reducing the adverse impact on ISPs and ensuring quality of service for users.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If P2P networks are used for content distribution, then server-based infrastructure burden is reduced, but ISP-unfriendly traffic increases causing higher costs for ISPs
Solution Approach 1:
The patent applies local quality by differentiating traffic treatment based on its origin and destination. Intra-ISP traffic receives preferential treatment with higher allocation rates, while inter-ISP traffic is constrained. This is achieved through rate allocation mechanisms that identify traffic types and apply different bandwidth allocation policies, thereby reducing ISP-unfriendly traffic while maintaining P2P distribution efficiency.
Solution Approach 2:
The patent implements dynamic rate allocation that adjusts bandwidth allocation in real-time based on network conditions and traffic types. The system continuously monitors traffic patterns and modifies allocation rates between intra-ISP and inter-ISP traffic dynamically, allowing the network to adapt to changing demands while minimizing harmful inter-ISP traffic transmission.
2Object-generated harmful factors
If rate allocation techniques are applied to reduce ISP-unfriendly traffic, then ISP costs are reduced, but QoS to end users may be compromised
Solution Approach 1:
The patent incorporates feedback mechanisms where the rate allocation system continuously monitors QoS metrics and network performance. Based on this feedback, the system adjusts allocation rates dynamically - reducing inter-ISP traffic when QoS thresholds are met, and increasing allocation when user quality requirements demand it. This closed-loop control ensures QoS is maintained while minimizing harmful traffic.
Solution Approach 2:
The patent changes key parameters such as allocation rates, threshold values, and weighting factors based on network conditions and QoS requirements. By dynamically adjusting these parameters, the system can shift the balance between reducing ISP-unfriendly traffic and maintaining user QoS, optimizing both objectives under different operating conditions.
3Object-generated harmful factors
If topology-based techniques are used to improve ISP-friendliness, then network structure complexity increases, but rate allocation effectiveness may be limited
Solution Approach 1:
The patent extracts the rate allocation function from complex topology-based approaches and implements it as a separate, independent mechanism. Instead of redesigning the entire network topology, the system applies rate allocation as an overlay control layer that operates on existing topology structures, thereby reducing complexity while maintaining effectiveness in reducing ISP-unfriendly traffic.
Data Source
AI summary
An ISP-friendly rate allocation system and method that reduces network traffic across ISP boundaries in a peer-to-peer (P2P) network, Embodiments of the system and method continuously solve a global optimization problem and dictate accordingly how much bandwidth is allocated on each connection. Embodiments of the system and method minimize load on a server in communication with the P2P network, minimize ISP-unfriendly traffic while keeping the minimum server load unaffected, and maximize peer prefetching. Two different techniques are used to compute rate allocation, including a utility function optimization technique and a minimum cost flow formulation technique. The utility function optimization technique constructs a utility function and optimizes that utility function. The minimum cost flow formulation technique generates a minimum cost flow formulation using a bipartite graph have a vertices set and an edges set. A distributed minimum cost flow formulation is solved using Lagrangian multipliers.