An analysis on data reduction methods for MANETS to reduce incoming data as a preprocessing technique

Abstract

Ad hoc network is characterized as a group of nodes coming together to form a network where each node is independently contributing into all network related activities having limited or scarce resources in terms of energy memory capacity, etc. Maintaining a resilient and attack free communication among these nodes become a huge challenge. Incorporating any new technique or algorithm with the existing incoming dataset flowing into a node may result in lowering the efficiency of the nodes adversely thereby reducing the lifetime of the network. The data regression on an incoming data in the node may be beneficial for increasing efficiency with respect to time, space, thereby improving performance. The technique removes the noise factor from the data before undergoing any process done on the incoming data. The paper provides an overview on the different reduction techniques which can be performed on wide range of data types as a part of data preprocessing. The major focus of the paper is in applying these techniques on the data incoming into MANETS in an ad hoc network.