Cache Location Server for Peer-to-Peer Network Optimization
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Solution Overview
Problem
In peer-to-peer networks, selecting the optimal cache for digital data download is challenging due to the lack of efficient methods for determining the closest cache location to the client, leading to increased network traffic and download times.
Innovation Solution
A method and server that utilize a client's location identifier to select the preferred cache from a plurality of caches, incorporating a Cache Location Server (CLS) connected to a database for determining the closest cache based on network addresses, reducing network traffic and download times by directing requests to the nearest cache.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If a client in a peer-to-peer network requests digital data without efficient cache location determination, then the client can access data from any cache in the network, but network traffic increases and download times are extended due to suboptimal cache selection
Solution Approach 1:
The patent introduces a Cache Location Server (CLS) as an intermediary between the client and caches. The CLS receives location identifiers from clients, determines the optimal cache based on network distance or topology, and returns the selected cache's address. This mediator resolves the contradiction by enabling efficient cache selection without requiring clients to scan the entire network, thus reducing network traffic and download time.
Solution Approach 2:
The system performs preliminary cache selection before actual data transfer begins. The CLS pre-determines the optimal cache location by processing the client's location identifier and selecting the best cache in advance. This preliminary action prevents unnecessary network traffic during the data retrieval phase and ensures minimal download time from the outset.
2Reliability
If multiple caches are available for data download, then data redundancy and availability are improved, but selecting the optimal cache becomes complex without location-based selection mechanisms
Solution Approach 1:
The Cache Location Server operates autonomously to handle cache selection. It automatically processes client location identifiers, queries its database of cache locations, and determines the optimal cache without requiring complex client-side logic. This self-service approach maintains data availability through multiple cache options while eliminating selection complexity for clients.
Solution Approach 2:
The system changes the selection parameter from arbitrary or random cache choice to location-based selection. By using location identifiers and comparing them against cache locations stored in the CLS database, the system transforms the selection process into a straightforward parameter-matching operation, reducing complexity while maintaining reliability through multiple available caches.
Data Source
AI summary
A method for selecting a preferred cache for the download of digital data from a plurality of caches is disclosed. The method comprises the steps of requesting an address of the preferred cache and selecting the preferred cache from the plurality of caches. The selection of the preferred cache is derived from a location identifier of a client requesting the download of the digital data.