Constructing method of self-organized cloud resource sharing distributed peer-to-peer network model

Abstract

The invention relates to a self-organized model constructing method of a cloud resource sharing peer-to-peer network, a distributed peer-to-peer network for short. The topology structure of the distributed peer-to-peer network is constructed through adoption of a space division concept. Physically closed cloud noses are self-organized. A reachable routing table is extended. The cloud peer-to-peer network which takes data as a core and is equipped with performances such as low delay and extensibility is realized. According to the method, in a large scale cloud resource distributed sharing environment, cloud node information is managed in real time, rapid resource positioning is carried out to the computing resource demand of each user, and an inquiring result is returned. Compared with the prior art, the method has the advantages that the method has clear average cloud resource inquiring delay advantage, the computing capabilities of the nodes are utilized fully, the actual performance of the cloud computing application is satisfied, and the method has wide application prospects in cloud resource sharing aspects.

Description

technical field [0001] The invention relates to the technical field of computer distributed peer-to-peer network, in particular to a self-organized cloud resource sharing distributed peer-to-peer network model construction method. Background technique [0002] The traditional distributed peer-to-peer network strategy can no longer meet the cloud application requirements in the new environment. Hardware resources may be "rare" resources and are no longer reproducible shared files; available cloud resources are dynamically changing, and it is not wise to back up resource information on cloud nodes to other nodes for query, because it will bring a lot of Update overhead. For another example, the server resources in the cloud peer-to-peer network are highly stable and can generally work for a long time, so that you don’t have to worry too much about the dynamic changes of the node topology; the computing power of the cloud nodes, the available storage space, and the throughput ...

AI Technical Summary

Problems solved by technology

For example, Chord and Kademlia can quickly locate distributed storage resources. However, while resources are optimally configured through distributed storage, the actual physical locations of logically adjacent nodes may be far apart. Communication with a low hop count does not mean must be low latency

Moreover, it also causes difficulties in the management of resources themselves, and cannot be directly used to solve the problems faced by cloud applications.

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