Method for providing download recommendation service, structured peer-to-peer network and node therein
A structured peer-to-peer and peer-to-peer network technology, applied in the field of nodes, can solve problems such as single point of failure, inability to fully consider user preferences, low scalability, etc.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- Publication Date
- 2011-04-20
- Estimated Expiration
- Not applicable · inactive patent
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Abstract
Description
technical field
[0001] The present invention relates to the technical field of structured peer-to-peer networks, in particular to a method for providing download recommendation services based on structured peer-to-peer networks, a download method, a structured peer-to-peer network and nodes in three structured peer-to-peer networks . Background technique
[0002] Compared with the unstructured peer-to-peer network, the structured peer-to-peer network has the advantages of high scalability and fast query speed. In the application of structured peer-to-peer network, the basic operations of storing and obtaining a storage object are Put and Get. Among them, the Put operation hashes an object to be stored to obtain a key value, and then transfers the object to the node responsible for indexing the key value for storage. The Get operation hashes the request object of the request node into a key value, and then the system routes it to the node responsible for indexing the key va...
Examples
Embodiment Construction
[0039] Since the technical solution in the embodiment of the present invention is based on the position-sensitive hash function, the related concepts of the position-sensitive hash function are introduced first.
[0040] The so-called location-sensitive hash function refers to a hash function that can preserve the distance characteristics of objects. Its specific definition is: a family (several) of hash functions H={h: S1→S2} is called the similarity measure N is ( r1, r2, p1, p2)-sensitive if it satisfies for any q, p, p' ∈ S1:
[0041] a. If p∈B(q,r1), then Pr H[h(q)=h(p)]≥p1,
[0042] b.if Then Pr H[h(q)=h(p’)]≤p2,
[0043] Wherein, p1>p2, r1
[0044] An explanation of the above definitions is given below:
[0045] 1. The object distance in the above definition, or the degree of similarity between objects, is measured by the similarity measure N. For example: in a three-dimensional space, the Euclidean distance betw...