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IoT 17(10): e4

Research Article

A Search Algorithm Based on K-Weighted Search Tree

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  • @ARTICLE{10.4108/eai.15-1-2018.154108,
        author={Lianhai Yuan and Xiangwen Li and Lin Zhou},
        title={A Search Algorithm Based on K-Weighted Search Tree},
        journal={EAI Endorsed Transactions on Internet of Things},
        volume={3},
        number={10},
        publisher={EAI},
        journal_a={IOT},
        year={2017},
        month={4},
        keywords={Searching algorithm, k-weighted search tree, Peer-to-Peer.},
        doi={10.4108/eai.15-1-2018.154108}
    }
    
  • Lianhai Yuan
    Xiangwen Li
    Lin Zhou
    Year: 2017
    A Search Algorithm Based on K-Weighted Search Tree
    IOT
    EAI
    DOI: 10.4108/eai.15-1-2018.154108
Lianhai Yuan1,*, Xiangwen Li1, Lin Zhou1
  • 1: Department of Electronic information and Computer Engineering, the Engineering &technical College of Chengdu University of Technology Leshan, China
*Contact email: 419129498@qq.com

Abstract

Aiming at the issue of low efficiency in Peer-to-Peer (P2P) network system, a search algorithm based on K-weighted search tree is proposed. The k-weighted search tree serving the search is constructed. The nodes are ranked from top to bottom in the tree according to the query hit rate, and the nodes with large hit rate and stable are on the tree layer, the search can thus determine the direction of the message diffusion. By caching the upper node, establishment of search results, using node index, overheated resource replication and add remote neighbours for leaf node, and other methods to improve search efficiency and balance load. The analysis and simulation results show that the proposed algorithm can greatly reduce the invalid message with higher search efficiency, and maintenance of the search tree is less expensive.

Keywords
Searching algorithm, k-weighted search tree, Peer-to-Peer.
Received
2017-02-18
Accepted
2017-04-05
Published
2017-04-14
Publisher
EAI
http://dx.doi.org/10.4108/eai.15-1-2018.154108

Copyright © 2017 Lianhai Yuan et al., licensed to EAI. This is an open access article distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/3.0/), which permits unlimited use, distribution and reproduction in any medium so long as the original work is properly cited.

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