Network Optimization via Delayed Low Priority Data Transfers
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Solution Overview
Problem
Current digital network protocols are inefficient in managing long-term variations in network traffic, leading to inefficiencies and increased costs for internet service providers as they struggle to optimize network usage without significant revenue increases, particularly due to the equal treatment of all data packets which can cause bottlenecks and interference between different types of data transmissions.
Innovation Solution
Implementing delayed data transfer requests and delay-or-drop data transfer requests at the application or transport layer, allowing data transfers to be scheduled during low network traffic periods or ignored if traffic is excessively high, using modified network protocols such as extended HTTP protocols with additional headers and quality of service indicators to prioritize data packets based on current network conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If all data packets are treated equally in network transmission, then network protocol simplicity is maintained, but network bandwidth efficiency deteriorates due to bottlenecks and interference between different types of data transmissions
Solution Approach 1:
The patent applies local quality by differentiating treatment of data packets based on their priority levels. High-priority packets (e.g., real-time communications) receive immediate transmission with guaranteed bandwidth, while low-priority packets (e.g., file downloads) are subjected to delayed or dropped transmission during congestion. This selective quality differentiation resolves the contradiction by optimizing bandwidth efficiency for specific packet types without fundamentally complicating the overall network protocol structure.
Solution Approach 2:
The patent changes the transmission parameter (delivery timing) based on packet priority and network conditions. Low-priority packets are transmitted with delayed timing or dropped when network congestion is detected, while high-priority packets maintain immediate transmission. This parameter change enables bandwidth efficiency improvement without requiring complete protocol redesign, thus resolving the contradiction between simplicity and efficiency.
2Productivity
If network capacity is increased to handle growing data demands, then service quality is improved, but operational costs deteriorate due to high upgrade expenses
Solution Approach 1:
The patent implements preliminary action by proactively managing low-priority data transfers during periods of network congestion. Instead of allowing congestion to develop and then upgrading infrastructure, the system preemptively delays or drops non-critical packets before bottlenecks form. This preliminary management action maintains service quality for high-priority traffic without requiring immediate capacity expansion, thereby avoiding high upgrade costs.
Solution Approach 2:
The patent enables the network system to self-regulate traffic flow based on detected congestion conditions. The system automatically adjusts transmission behavior by delaying or dropping low-priority packets without external intervention or infrastructure changes. This self-service capability allows the network to maintain productivity and service quality while avoiding the operational costs associated with capacity upgrades.
3Productivity
If data transfers are delayed to optimize network usage, then network bandwidth efficiency is improved, but loss of time increases for data delivery
Solution Approach 1:
The patent applies local quality by differentiating time sensitivity requirements across different data packets. High-priority packets maintain immediate delivery with minimal time loss, while low-priority packets accept delayed delivery in exchange for overall network efficiency improvement. This selective approach resolves the contradiction by localizing time delay impacts to only those packets where delay is acceptable.
Solution Approach 2:
The patent converts the potential harm of delayed data delivery into a benefit by strategically delaying only low-priority packets during congestion. This selective delay reduces overall network congestion and improves bandwidth efficiency, which ultimately benefits all traffic including high-priority packets. The time loss for low-priority packets is transformed into a system-wide efficiency gain.
Data Source
AI summary
As more internet service providers have more customers with high-speed internet access accounts and these customers access more multi-media rich data (such as videos), the network infrastructure of internet service providers becomes saturated. Thus, internet service providers are facing pressure to upgrade their networks. However, high-speed digital networking equipment is expensive. Thus, internet service providers need to optimize the usage of their existing networks. To optimize the usage of existing networks, a system of delaying certain data requests is proposed. By delaying certain data requests, the various components in a network can shift data transfers from peak traffic times to lower traffic times. One useful application of delayed requests is the case in which a web client requests data ahead of schedule either through predictive methods or through subscriptions for desired data.