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SHORT PAPERInternational Journal of Recent Trends in Engineering, Vol 2, No. 3, November 2009

48

An Energy efficient data transmission

in Wireless Sensor NetworksM.Nesasudha 1 and M.L.Valarmathi 2

1Karunya University, Department of Electronics & Communication Engineering, Coimbatore, [email protected]

2 Government college of technology, Department of Computer Science and Engineering, Coimbatore, [email protected]

Abstract: Wireless sensor networks are undoubtedly one of the

largest growing types of networks today. Wireless sensor

networks are expected to consist of Thousands of inexpensive

nodes, each having sensing capability with limited computationaland communication power their reliability, cost-effectiveness,

ease of deployment and ability to operate in an unattended

environment, among other Positive characteristics make sensor

networks the leading choice of networks for these applications.

Here pattern generation for data aggregation is performed

securely by allowing a sensor network to aggregate encrypted

data without first decrypting it. In this pattern generation

process, initially when a sensor node senses an event from the

environment, a pattern code is generated and sends to the cluster

head. This generated pattern code is compared with the existing

pattern code in the cluster head and then reception of the

acknowledgement, Authentication and the transmission of actual

data then follows. The simulator used for the implementation is

GloMoSim Network Simulator . This is more efficient due to

aggregated data transmission, secure and bandwidth efficient.

Index terms- Wireless sensor networks, Security, Pattern codes,

pattern generation and comparison

I.INTRODUCTION

The primary function of a wireless sensor network is todetermine the state of the environment being monitored bysensing some physical event. Wireless sensor networksconsist of hundreds or thousands or, in some cases, evenmillions of sensor devices that have limited amounts of

processing power, computational abilities and memory and

are linked together through some wireless transmissionmedium such as radio and infrared media. Wireless sensornetworks are expected to consist of Thousands of inexpensive nodes,each having sensing capability with limited computational andcommunication power their reliability[2],[3].These sensors areequipped with sensing and data collection capabilities and areresponsible for collecting and transmitting data back to theobserver of the event. Sensors may be distributed randomlyand may be installed in fixed locations or they may bemobile. For example, dropping them from an aircraft as itflies over the environment to be monitored may deploy them.Once distributed, they may either remain in the locations inwhich they landed or they may begin to move if necessary.

Sensor networks are dynamic because of the addition andremoval of sensors due to device failure in addition tomobility issues. Security in wireless sensor networks is amajor challenge.[4] The limited amount of processing power,computational abilities and memory with which each sensordevice is equipped makes security a difficult problem tosolve. The GlomoSim network simulator (Global MobileInformation Systems Simulation Library) is the simulator[7]used which is a scalable simulation environment for largewireless and wired line communication networks.

II.PATTERN GENERATION (PG)

Input: Sensor reading D, Data parameters being sensed.Output: Pattern-code (PC)

This explains how PG algorithm[1] generates a pattern code.Let D (d1, d2, d3) denote the sensed data with three

parameters d1, d2, and d3 representing temperature, pressureand humidity respectively in a given environment. Each

parameter sensed is assumed to have threshold values between the ranges 0 to 100 as shown in Table 1.

A. Pattern Generation:

TABLE1LOOK UP TABLE FOR DATA INTERVALS AND

CRITICAL VALUES

Threshold

values 30 50 70 80 90 95 100

Interval values0-30

31-50

51-70

71-80

81-90

91-95

96-100

Critical values 5 3 7 8 1 4 3

Pattern codes with the same value are referred as a redundantset. In this example,[1] data sensed by sensor 1 and sensor 3are same with each other as determined from the comparisonof their pattern code values (pattern code value 747) and theyfor the Redundant Set #1. Similarly, data sensed by sensor 2,

© 2009 ACADEMY PUBLISHER

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sensor 4 and sensor 5 are the same (pattern code value 755),Redundant Set #2.

III.PATTERN COMPARISON

Pattern codes are given as input. Request sensor nodes in theselected-set to send actual encrypted data.The cluster-headruns the pattern comparison algorithm to eliminate theredundant pattern codes resulting in prevention of redundantdata transmission.[6] Cluster heads choose a sensor node foreach distinct pattern code to send corresponding data of that

pattern code, and then chosen sensor nodes send the data inencrypted form to the base station over the cluster-head. In

pattern comparison algorithm, upon receiving all of the pattern codes from sensor nodes in a period of T, cluster-headclassifies all he codes based on redundancy. The period Tvaries based on the environment and the application type ofthe sensor network. Unique patterns are then moved to the‘selected-set’ of codes. The sensors nodes that correspond tothe unique pattern set (‘selected-set’) are then requested totransmit the actual data. ACK signals may be broadcast toother sensors (‘de-selected set’) to discard their (redundant)data. While pattern based data aggregation ensures security, ithas limited precision as specified by user requirements [6]SDT is implemented in every session of data transmission,where session refers to the time interval from the moment thecommunication is established between a sensor node and thecluster-head until the communication terminates.

A. Differential Data Transmission from Sensor Nodes to

Cluster head:

The differential data is securely sent to the base station usingthe security protocol described in this section [5]. The basestation converts the differential data to the raw data usingreference data. The cluster-head eliminates the redundancyafter obtaining the entire actual data from sensor nodes thusmaking it more energy efficient than the conventional dataaggregation technique because the number of transmitted

packets here will be much less than the conventional one. If Tis the total number of packets that sensor nodes want totransmit in a session, and R as the number of distinct packets,where R less than or equal to T . After eliminating redundancythe cluster-head sends R packets to base station. Therefore,

the total number of packets transmitted from sensor nodes to base station is (T + R).

IV.SLEEP-ACTIVE MODE COORDINATION

Each sensor node is set to either idle or active mode forsensing operation [2] on the connectivity and conditions ofthe sensing environment. Identifying nodes that haveoverlapping sensing ranges and turning off the sensing unitsof some of those nodes for a bounded amount of time reducesenergy wastage since these nodes will produce redundant datadue to the overlapping. Neighboring nodes can communicate

with each other via cluster-head. The total lifetime of thenetwork is divided into fixed length slots of duration T. Eachslot consists of observation, learning and decision phases.Each node that is awake updates its local buffer based on the

events in its observation phase..

V: ENERGY EFFICIENCY OF PATTERN BASED DATATRANSMISSION

Assuming that the pattern generation time as well as the propagation delay between sensor nodes and cluster-head isnegligible, the data transfer time from sensor nodes to cluster-head is computed below by including the data transmissiontime only [6]. Hence, in case of the conventional dataaggregation algorithm, the data transfer time equals:

TconventionaL =

Where R denote the transmission rate at which sensors cansend data (bps). N denote the total number of active sensornodes. Di denote the number of bits transmitted per session

by sensor node i. Pi denote the number of pattern code bitstransmitted per session by sensor node i.

T improved model = Pi/R + Di/R

TABLE 2PATTERN CODE GENERATIONS

The amount of data to be transmitted by a conventional dataaggregation algorithm can be expressed as

Di and in the proposed model this becomes

Di + Pi

SENSORS 1 2 3 4 5

DATA D(56,92,70) D(70,25,25) D(58,93,69) D(68,28,30) D(63,24,26)

CRITICAL

VALUE

FOR D1

7 7 7 7 7

CRITICAL

VALUE

FOR D2

4 5 4 5 5

CRITICAL

VALUE

FOR D3 7 5

7 5 5

PC

747 755 747 755 755


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VI.SIMULATION RESULTS

Figure.1: Generated Pattern Code

Figure.2: Selected unique set of pattern codes

Figure.3: The Configuration File

VII: CONCLUSION

Sensor nodes receive the secret pattern seed from the cluster

head. The interval values for the data are defined, based onthe given threshold values set for each environment parameter. The number of threshold values and the variationof intervals may depend on the user requirement and the

precision defined for the given environment in which thenetwork is deployed Pattern Generation (PG) algorithm firstmaps the sensor data to a set of numbers. PG algorithm thencomputes the critical values for each interval using the patternseed and generates the interval and critical value lookuptables. The cluster-head runs the pattern comparisonalgorithm to eliminate the redundant pattern codes resultingin prevention of redundant data transmission. Cluster-headschoose a sensor node for each distinct pattern code to sendcorresponding data of that pattern code, and then chosensensor nodes send the data in encrypted form to the basestation over the cluster-head. Compared to conventional dataaggregation algorithms, as the redundancy increases the

bandwidth efficiency of this model also increases.

REFERENCES

[1] H. Çam, S. Özdemir, Prashant Nair, and D. Muthuavinashiappan,“ESPDA: energy efficient and secure pattern-based data aggregationfor wireless sensor networks,'' Proc. of IEEE Sensors - The Second

IEEE Conference on Sensors, Oct. 22-24, 2005, Toronto, Canada, pp. 732-736.[2] W. Ye, J. Heidemann, and D. Estrin, “An Energy- EfficientMAC Protocol for Wireless Sensor Networks”, Proc. of INFOCOM

2002, vol. 3, pp. 1567-1576, June 2002.[3] A. Sinha and A. Chandrakasan, “Dynamic power management inwireless sensor networks”, IEEE Design and Test of Computers, vol.18(2), pp. 62-74, March- April 2006.[4] A. Perrig, R. Szewczyk, J.D. Tygar, V. Wen, and D.E. Culler,“SPINS: Security protocols for sensor network”, Wireless Networks,vol. 8, no. 5, pp. 521-534, 2002.[5] C. Intanagonwiwat, D. Estrin, R. Govindan, and J. Heidemann,“Impact of network density on Data Aggregation in wireless sensornetworks”, Proc. of the 22nd International Conference on

Distributed Computing Systems, pp. 575-578, July 2002.[6] H. Çam, S. Özdemir, D. Muthuavinashiappan, and Prashant Nair,“Energy-Efficient security protocol for Wireless Sensor Networks”,

IEEE VTC Fall 2003 Conference, October 2003, Orlando, Florida.[7] X. Zeng, R. Bagrodia, and M. Gerla, “GloMoSim: A Library forParallel Simulation of Large-scale Wireless Networks”, Proc. of the

12th Workshop on Parallel and Distributed Simulations, PADS'98,May 1998, Banff, Alberta, Canada.


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