Research Area:  Mobile Ad Hoc Networks

Abstract:

Mining the frequent pattern deals with the finding patterns in large set of data, subsequences and substructures that occur in a database frequently. Likewise, We can use Frequent pattern mining for MANET nodes in order to identify the paths which are participated in frequent data transaction among the various Mobile adhoc network nodes. The network data stream is a long and continuous sequence of data sets transmitted over the network. The OCA (Online Combinatorial Approximation) algorithm is used in the data stream for mining online data. The processing time of OCA was much less and accuracy of its approximate result was quite high like other traditional mining methods. The Data Path Combinatorial Approximation (DPCA) algorithm deals with a frequent pathset mining over the MANET data flow. The pathset is generation of path from the set of paths on any node which are provided paths to various other nodes participating in the data transmission. The mining algorithm is based on Approximate Inclusion–Exclusion technique. Without continual path scanning, approximate counts are calculated for the pathsets. Skip and complete technique and group count technique were combined together and integrated into the DPCA algorithm to improve the MANET performance in terms of identifying fool around (misbehaving) nodes.

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Author(s) Name:   S. Arun & K. Sudharson

Publisher name:  Springer

DOI:  10.1007/s12652-020-02606-7

Volume Information:  

Paper Link:   https://link.springer.com/article/10.1007/s12652-020-02606-7