Resourceful data Accretion in radiation in a Hefty WSN

Resourceful data Accretion in radiation in a Hefty WSN

Akash Manish Lad Vellore Institute of Technology Chennai

Abstract: Wireless Sensor Network is a distribution of nodes connected wirelessly to form a wireless topology. Having wide applications, these are prone to misconduct. The most prevalent misconduct is the ability of a node to send data under influence of radiation and such nodes are called defective nodes. The defective node affected due to radiation and a void is created due to this node in the network topology. Such defective nodes due to its inability to perform triggers loss of data. Many algorithms/techniques were proposed but none among those were capable for over thousand sensor nodes. More than thousand nodes are considered here. Sensor nodes with radio frequency mode and acoustic mode of communication are considered. Audio mode is implemented in nodes left out with voids and RF-mode is used in nodes located at the boundary of void-nodes. Transfer of defective nodes in a network can be foretold depending upon its past behaviour.

Keywords: Data Accretion, RF-Communication, Audio-Communication, defective nodes, Prediction technique, testing methods.

Introduction

With advancements in technology and miniaturization, wireless devices could communicate over very-small ranges and due to this wireless sensor networks came into play. Such devices are called as sensor nodes. These nodes are organized in a random fashion to form a topology network so as to cover large area possible geographically. There are large applications of sensor nodes such as sensing important information, sensing ranges and transmitting sensed information to any stations using single/multi hop communication. These nodes which receive and transmit information are connected wirelessly. In a general WSN network several nodes are connected to one another and it can be extended to over a few thousand nodes. WSN network trails IEEE 802.11 format for wireless local area network protocols. The sensor nodes detects , senses and then transmits the message to nearby station wirelessly.

The nodes in WSN are widely used in real-world applications due to its capability to sense various features like temperature , smoke, proportion of chemical substances and other physical quantities. Many other applications include predictions of natural disasters, weather predictions, air-pollution quality index, military application etc. In this technique the data loss is handled due to the presence of defective-nodes. The defective nodes caused due to excessive influence of radiation has been studied and few techniques have been presented. The main reason for data loss is mainly due to the effect of radiation.

The nature of the defective nodes are dynamic as these nodes are created mainly under the course of electromagnetic radiation when under an influence for a long time. The sensor nodes start sensing and transmit communication when the radiation is over. There are cases when the radiations lasts for shorter duration of time. Using the conventional Brute-force approach is not reliable as it involves removal of the defective nodes from a particular network and it is not a solution to the concerned problem. The maintenance cost, using such kinds of approach, is quite high and does not address to the solution of problem. To solve this problem, there is a method involving specialized nodes which communicate using RF and audio means. To obtain the information and details from affected area certain prediction algorithms are used. Most of the testing algorithms are very costly when in failure. One such way to solve the issue is by observing behavior of defective nodes and particular prediction techniques can be applied accordingly.

PREDICTION TECHNIQUE

In this paper, defective node has been incorporated with prediction logic which will predict that if a node is defective or not. The Sink have NET_INFO table which has tuple <node_id, initial_nbr_list, current_nbr_list> besides to every wireless node in observed network. Tuples having count of entries in current_nbr_list than in initial_nbr_list are interesting to sink. Sink looks for tuples in which initial_nbr_list > current_nbr_list, and node besides to this tuple is a boundary node. Sink tells this boundary node to switch to dual communication mode. Sensor nodes besides to tuples in which current_nbr_list is empty are candidates for transfaulty node. The algorithm employs testing techniques to find out communication failure nodes. The applied algorithm is a 2-phase algorithm namely,

i. finding of defective and boundary nodes.
ii. grouping of nodes using special algorithms and bringing out approximate information.

Predict transfaultyness of sensor nodes.

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Observation Phase:

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