Peer-Assisted Web Transfer Using Agents for Faster Data Delivery
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Solution Overview
Problem
Current Internet communication systems face challenges in providing fast and efficient data transfer without incurring significant infrastructure costs or being unable to handle dynamic content, as existing solutions like proxies and peer-to-peer file sharing systems are either too costly or inefficient for widespread implementation.
Innovation Solution
A network architecture that includes client, agent, and peer communication devices, with an acceleration server managing assignments, allows for efficient data transfer by utilizing existing devices to store and distribute data, reducing the need for extensive infrastructure investments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If traditional proxy servers are deployed to accelerate data communication, then data transfer speed is improved, but infrastructure costs and device complexity increase significantly
Solution Approach 1:
The system enables end-user devices to serve each other by storing and sharing data locally. When a user requests data, their device first checks local storage (cache) before querying remote servers. This self-service approach reduces dependency on centralized proxy infrastructure while maintaining fast data access speeds.
Solution Approach 2:
The system creates copies of data on user devices rather than relying on a single centralized source. Multiple users can store copies of the same data locally, enabling parallel access and reducing the need for complex proxy infrastructure to manage data distribution.
2Productivity
If proxy servers are used to cache and distribute data, then data communication efficiency is improved, but the cost for content owners and infrastructure investment increase
Solution Approach 1:
User devices perform the caching and data distribution functions that traditionally required expensive proxy servers. Each device uses its own storage and processing capabilities to serve data requests, eliminating the need for costly centralized infrastructure while maintaining high communication efficiency.
Solution Approach 2:
Instead of having centralized servers serve all data requests, the system inverts the model by enabling distributed client devices to serve each other. This inversion transforms the cost burden from infrastructure providers to end-users, significantly reducing implementation costs.
3Ease of manufacture
If existing devices are utilized for data storage and distribution, then infrastructure costs are reduced, but the ability to handle dynamic content effectively deteriorates
Solution Approach 1:
The system dynamically adjusts behavior based on content type and user needs. It can switch between serving data from local cache, other users' devices, or remote servers depending on availability and requirements. This dynamic approach enables effective handling of both static and dynamic content while maintaining low infrastructure costs.
Solution Approach 2:
User devices perform multiple functions: they serve as data clients, local caches, content distributors, and coordination nodes. This multi-functionality eliminates the need for specialized infrastructure for different content types, allowing the same low-cost device architecture to handle diverse content effectively.
4Ease of manufacture
If peer-to-peer file sharing systems are used, then infrastructure investment is reduced, but data transfer speed and reliability deteriorate
Solution Approach 1:
The system incorporates feedback mechanisms where devices report their data availability status and transfer performance. This feedback enables intelligent routing decisions that prioritize fast and reliable data paths, maintaining high transfer speeds while avoiding the infrastructure investment required by traditional servers.
Solution Approach 2:
The system segments data transfer into multiple parallel connections with different reliability characteristics. It can simultaneously use fast but less reliable paths and slower but more reliable paths, then combine the results. This segmentation enables high overall speed while maintaining reliability without expensive infrastructure.
Data Source
AI summary
A system designed for increasing network communication speed for users, while lowering network congestion for content owners and ISPs. The system employs network elements including an acceleration server, clients, agents, and peers, where communication requests generated by applications are intercepted by the client on the same machine. The IP address of the server in the communication request is transmitted to the acceleration server, which provides a list of agents to use for this IP address. The communication request is sent to the agents. One or more of the agents respond with a list of peers that have previously seen some or all of the content which is the response to this request (after checking whether this data is still valid). The client then downloads the data from these peers in parts and in parallel, thereby speeding up the Web transfer, releasing congestion from the Web by fetching the information from multiple sources, and relieving traffic from Web servers by offloading the data transfers from them to nearby peers.