Quality overhead ratio hop cluster-based service discovery method and mobility model establishing method

Abstract

The invention discloses a quality overhead ratio hop cluster-based service discovery method and a mobility model establishing method. The service discovery method improves a k-hop non-uniform cluster scheme in the conventional CASD scheme and provides a quantitative criteria for the cluster hop, namely the quality overhead ratio. By searching a hop value at the maximum quality overhead ratio and uniformly clustering according to the optimized hop, the load balance and the maximum quality overhead ratio of cluster-head nodes can be realized. In the mobility model establishing method, a random walking model is adopted to establish the mobility model for the network nodes. The quality overhead ratio hop cluster-based service discovery method avoids the probability of idle load or full load operation of the cluster-head nodes, and better realizes the load balance of the cluster-head nodes; and more importantly, the quality overhead ratio hop cluster-based service discovery method can realize the maximum ratio of the service and communication quality to the cluster and communication overhead, namely the maximum quality overhead ratio.

Description

technical field [0001] The invention relates to a service discovery method based on network clustering, in particular to a service discovery and mobile model establishment method based on quality cost ratio hop number clustering. Background technique [0002] With the improvement of computing power, the network tends to be dynamic and large-scale. In the ubiquitous computing environment, human beings can discover services and resources anytime and anywhere. But how to achieve these requirements? First, the network must have good scalability; second, the network must have good robustness; finally, the quality of service discovery and the overhead of the communication system must be balanced. [0003] Service discovery protocols in fixed networks and static networks, such as Jini and UPnP, are quite mature. But these service discovery protocols are no longer suitable for P2P networks. The DHT-based P2P network has been extensively studied, and the typical network structure...

AI Technical Summary

Problems solved by technology

When the number of clustering hops k is relatively small, the topology of the cluster is unstable. At this time, the probability of re-clustering increases, the number of clusters that need to be re-clustered in the entire network will increase accordingly, and the clustering overhead will increase; When it is large, the structure of the cluster is relatively stable, but the overhead of service registration, service query, and communication overhead will increase, because this part of overhead is proportional to the number of hops, and the quality of service and communication will decrease at this time

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