Peer-Assisted Web Transfer Using Cached Parallel Data Chunks
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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 handling dynamic content effectively, as existing solutions like proxies and peer-to-peer file sharing systems are either impractical or economically unfeasible due to the massive capital investments required.
Innovation Solution
A network architecture that includes client, agent, and peer communication devices, with an acceleration server assigning devices to serve data requests, utilizing a cache database to store and manage data chunks, and an acceleration application to intercept and route requests for optimized data transfer.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If traditional proxy servers are deployed to cache and serve data locally, then data communication speed is improved, but infrastructure costs and capital investment become prohibitively large
Solution Approach 1:
Instead of deploying physical proxy servers at every location, the system creates virtual copies of data (caches) that are distributed across peer devices. These cached copies are then served to users without requiring expensive infrastructure, as the same data is replicated across multiple user devices rather than requiring dedicated server hardware at each location
Solution Approach 2:
The system enables end-user devices to serve as their own content delivery infrastructure by caching data locally. Users' devices automatically store and serve data to themselves and others, eliminating the need for ISPs to maintain expensive dedicated proxy infrastructure. The infrastructure is self-provided by the users themselves
2Device complexity
If peer-to-peer file sharing systems are used, then infrastructure costs are reduced, but they cannot effectively handle dynamic content and require massive capital investment for comprehensive solutions
Solution Approach 1:
The system dynamically determines which data should be cached on which peer devices based on real-time factors such as user behavior patterns, content popularity, and network conditions. This dynamic approach allows the system to adapt to changing content requirements and user needs, enabling effective handling of dynamic content while maintaining low infrastructure costs
Solution Approach 2:
The system changes the parameters of content delivery by adjusting cache validity periods, cache sizes, and data replication strategies based on content type and user behavior. This allows the system to optimize performance for different types of dynamic content without requiring expensive infrastructure, as the optimization is achieved through software parameter adjustment rather than hardware investment
3Ease of operation
If content is dynamically created per user session, then user experience is improved, but it becomes impossible to store and provide content to others seeking similar content
Solution Approach 1:
The system segments dynamically created content into discrete data chunks that can be independently cached and shared. Instead of treating each user session as completely unique, the system identifies common patterns and segments content into reusable units that can be stored and redistributed to other users with similar needs, thereby preserving the benefits of dynamic personalization while enabling content reuse
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.