I nternationalJournalofEngineeringTrendsandApplications(I JETA) Volume2I ssue4, July- Aug2015 ISSN:2393- 9516www.ijetajournal.orgPage 35 Implementationof Run-LengthEncoding In Examination For Lossless Data Compression ThirunavukkarasuE [1], Karuppusami G [2], EzhilarasuP [3] ProfessorandHead [1] Departmentof ComputerScienceand Engineering JairupaaCollegeof Engineering,Tiruppur Dean ResearchandInnovations [2] Departmentof MechanicalEngineering SriEshwarCollegeofEngineering,Coimbatore AssociateProfessor [3] Departmentof ComputerScienceand Engineering HindusthanCollegeof Engineeringand Technology,Coimbatore TamilNadu - India. ABSTRACT In this paper, we discussRun-length encoding data compression technique. Three type of input taken. First, more than twoinputcharacterswithfrequentrun-lengthconsidered.Then, two input character with almost equal frequency of occurrenceareconsidered.Finallytwoinputcharacter with one character having less frequency of occurrences and anotheronewithmorefrequencies of occurrences are considered. Its compression ratio, space savings, and average bits also calculated. Comparisonbetween each condition performed.Keywords:- Run-length, Compression, Encoding, Decoding.

I.INTRODUCTION Datacompressiondefinedasthe reorganization of data in such a way that, the volume of the resultant data (compressed data) is less than that of thevolumeofthesourcedata(uncompresseddata). Thedecompressiontechniqueapplied to get back the uncompressedsourcedata.Afterdecompressionif somedatadestroyedbecauseofcompressionand decompression,thenthecompressioncalledas lossy compression.Ifnoneofthedatadestroyedand availableinitsoriginaluncompressedform,thenthe compression called as lossless compression. The Run-lengthencodingcomesunderlosslesscompression. Timecomplexityandspacecomplexityarethetwo important complexitiesin data compression. Becauseof data suppression, only little amount of timeneededfordatatransferbetweensourcesystem andtargetsystem.Forinstance,if theoriginal size of the source data is 4GB and the transfer rate is 512 kbps. Thetimeneedforthetransferobtainedbythe given equation 1.Time needed for transfer of data = Input data / transfer rate (1) (1MB=1024KBand1KB=8 kb) Input data = 4 GB =4*1024*1024 * 8 =4*1024*1024 * 8 kbTransfer rate = 512kbps So timetaken for transfer of data =(4*1024 * 1024 * 8) / 512 = 4 *2* 1024* 8 = 65536seconds Ifthegivendatacompressedinto2.5GB, then the timetaken for transfer willbe 40960seconds.If the destination allowed amount of storage is 2TB, then the target machine can store the following number of files by using the equation 2.RESEARCHARTICLEOPENACCESS I nternationalJournalofEngineeringTrendsandApplications(I JETA) Volume2I ssue4, July- Aug2015 ISSN:2393- 9516www.ijetajournal.orgPage 36 Total number of files can be stored =Total amount of storage / Volume of the file (2) (1TB= 1024GB) = 2 * 1024GB/ 4 GB = 1024/ 2=512files Therefore,thedestinationsystemcanstore512 files for uncompressed data. For compressed file, it can store = 2 * 1024MB / 2.5GB = 2048/2.5 = 819files. Thecompressionratioaffectsboththe space and timecomplexity.Itcalculatedbyusingthefollowing equation 3.Compressionratio=Uncompressedoriginal data / Compressed Data(3) = 4 GB/ 2.5GB = 8:5 Space savings also calculated by using compressed anduncompresseddata.Itobtainedbyusingthe followingequation 4. Spacesavings=1-(Compressed Data/Uncompressed original data)(4) In compression, we have the following types 1.Lossy compression.2.Lossless compression.In this paper, we discuss Run-length encoding.II.RELATEDWORK Run-lengthencoding (RLE)isaverysimpleform of datacompression inwhich runs ofdata(thatis, sequences in which the same data value occurs in many consecutive data elements) are stored asa single data value and count, rather than as the original run. This is mostusefulondatathatcontainsmanysuchruns [1]. KhalidSayood[2000]delineatedanintroduction intothevariousareasofcodingalgorithms,both losslessandlossy,withtheoreticalandmathematical backgroundinformation[2].MarkNelsonandJean-loupGailly[1995]representedthebasicsofdata compression algorithms. It includes lossless and lossy algorithms[3].DavidSalomon[2000]explainedmany differentcompressionalgorithmsaltogetherwith their uses,limitations,andcommonusages.Hegavean overview on lossless and lossy compression [4]. Many books[5,6,7,8and9]publishedaboutthedata compressiontechniques.Golomb[1966]explained about the golomb code which refers the case where the indexfunctionisf(z)=z/gwheregdenotesthe positiveintegerthenonlyeachmemberoftheset consists of g members [10]. III.RUN-LENGTHENCODING A.MORETHAN TWO CHARACTERS eeeeeeeeeeeeezzzzhhhhhhhhhhhhiiiiiiiiiiillllllllll after encoding e13z4h12i11l10 Total numberof characters =14 uuuuuuummmmmmmaaaaaddddddeeeeeeeeeeeeeeevvviiiiiii after encoding u7m7a5d6e15v3i7 Total numberof characters =15 ppppppppaaaaaaaaallllllllllaaaaaaaaaaaannnnniiiiii after encoding p8a9l10a12n5i6 Total numberof characters =14 B.TWOUNIQUECHARACTERSWITHAPPROXIMATEEQUALFREQUENCYANDCOMBINATIONOF LESS& MOREFREQUENCY The consolidated result for the nine theories are as shown in the table 1. S.NOREG.NOSUBJECTRESULT T1-3T2-3T3-3T4-3T5-3T6-3L1-3L2-3L3-3 1.9727K0201PPPPPPPPP 2.9727K0202PPPPPPPPP 3.9727K0203FPPFPPPPP 4.9727K0204FFPPPFPPP 5.9727K0205PPFPPPPPP I nternationalJournalofEngineeringTrendsandApplications(I JETA) Volume2I ssue4, July- Aug2015 ISSN:2393- 9516www.ijetajournal.orgPage 37 6.9727K0206PPPPPPPFP 7.9727K0207PPPPFPPPP 8.9727K0208FPPPPPPPP 9.9727K0209PPPPPPPPP 10.9727K0210FPPPPPPPP 11.9727K0211PPFPPPPPP 12.9727K0212PPPPPPPPP 13.9727K0213FPPPPFPFP 14.9727K0214PPPPPPPPP 15.9727K0215PPPPPPPPP 16.9727K0216FPPPPPPPP 17.9727K0217PFPPPPPPP 18.9727K0218PPPFPPPPP 19.9727K0219FPPPPPPPP 20.9727K0220PPPPPPPPP 21.9727K0221PPPPPPPPP 22.9727K0222PPPPFPPPP 23.9727K0223PPPPPPPPP 24.9727K0224PPPPPPPPP 25.9727K0225FPPPPFPPP 26.9727K0226PPPPPPPPP 27.9727K0227PPPPPPPPP 28.9727K0228PPPPPFPPP 29.9727K0229PPPPPPPPP 30.9727K0230PPPPPPPPP 31.9727K0231PPPPPPPPP 32.9727K0232PFPPPPPPP 33.9727K0233PPPPPPPPP 34.9727K0234FPPPFPPPP 35.9727K0235PPPPPPPPP 36.9727K0236PPPPFPPPP 37.9727K0237PPPPPPPPP 38.9727K0238PPPPPPPPP 39.9727K0239FPPPPFPPP 40.9727K0240FPPPPPPPP 41.9727K0241FPPPPPPPP 42.9727K0242PPPPPPPPP 43.9727K0243PPPPPPPPP 44.9727K0244PPPPPPPPP 45.9727K0245PPPPPPPPP 46.9727K0246PPPPPPPPP 47.9727K0247FFFFFFFFP 48.9727K0248PPPPPPPPF 49.9727K0249FPPPPPPPP 50.9727K0250PPPPPPPPP Table . 1.Consolidated results for nine subjects with six theory and three lab. I nternationalJournalofEngineeringTrendsandApplications(I JETA) Volume2I ssue4, July- Aug2015 ISSN:2393- 9516www.ijetajournal.orgPage 38 THEORY1 RESULT PPFFPPPFPFPPFPPFPPFPPPPPFPPPPPPPPFPPPPFFFPPPPPFPFP THEORY2 RESULT PPPFPPPPPPPPPPPPFPPPPPPPPPPPPPPFPPPPPPPPPPPPPPFPPP THEORY3 RESULT PPPPFPPPPPFPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPFPPP THEORY4 RESULT PPFPPPPPPPPPPPPPPFPPPPPPPPPPPPPPPPPPPPPPPPPPPPFPPP THEORY5 RESULT PPPPPPFPPPPPPPPPPPPPPFPPPPPPPPPPPFPFPPPPPPPPPPFPPP THEORY6 RESULT PPPFPPPPPPPPFPPPPPPPPPPPFPPFPPPPPPPPPPFPPPPPPPFPPP LAB1 RESULT PPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPFPPP LAB2 RESULT PPPPPFPPPPPPFPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPFPPP LAB3 RESULT PPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPFPP Replacing P by 1 and F by 0 the result willbe THEORY1 RESULT 11001110101101101101111101111111101111000111110101 THEORY2 RESULT 11101111111111110111111111111110111111111111110111 THEORY3 RESULT 11110111110111111111111111111111111111111111110111 THEORY4 RESULT 11011111111111111011111111111111111111111111110111 THEORY5 RESULT 11111101111111111111101111111111101011111111110111 THEORY6 RESULT 11101111111101111111111101101111111111011111110111 LAB1 RESULT 11111111111111111111111111111111111111111111110111 LAB2 RESULT 11111011111101111111111111111111111111111111110111 LAB3 RESULT 11111111111111111111111111111111111111111111111011 THEORY1 RESULT 11001110101101101101111101111111101111000111110101 22311121212151814351111 Total Numberof Character after encoding = 23 THEORY2 RESULT 11101111111111110111111111111110111111111111110111 319031905190513 Total Numberof Character after encoding = 15 THEORY3 RESULT 11110111110111111111111111111111111111111111110111 4151909090813 Total Numberof Character after encoding = 13 THEORY4 RESULT 11011111111111111011111111111111111111111111110111 219051909090113 Total Numberof Character after encoding = 15 THEORY5 RESULT 11111101111111111111101111111111101011111111110111 619051902111190113 Total Numberof Character after encoding = 18 THEORY6 RESULT 11101111111101111111111101101111111111011111110111 31819021219011713 Total Numberof Character after encoding = 17 LAB1 RESULT 11111111111111111111111111111111111111111111110111 9090909090113 Total Numberof Character after encoding = 13 LAB2 RESULT 11111011111101111111111111111111111111111111110111 5161909090613 Total Numberof Character after encoding = 13 LAB3 RESULT 11111111111111111111111111111111111111111111111011 9090909090212 Total Numberof Character after encoding = 13 IV.RESULTAND DISCUSSION The compression ratio, space savings and average bits calculated for the examplesare I nternationalJournalofEngineeringTrendsandApplications(I JETA) Volume2I ssue4, July- Aug2015 ISSN:2393- 9516www.ijetajournal.orgPage 39 For the input : eeeeeeeeeeeeezzzzhhhhhhhhhhhhiiiiiiiiiiillllllllll Compression ratio= 400/112 = 50:14 =3.57:1 Space savings=1-(112/400) = 1-(7/25) = 1-0.28 = 0.72 = 72% Average bits = 112/50 = 2.24bits per character For the input : uuuuuuummmmmmmaaaaaddddddeeeeeeeeeeeeeeevvviiiiiii Compression ratio= 400/120 = 50:15 =3.66:1 Space savings=1-(120/400) = 1-(15/50) = 1-0.3 = 0.7= 70% Average bits = 120/50 = 2.4 bits per character For the input :ppppppppaaaaaaaaallllllllllaaaaaaaaaaaannnnniiiiii Compression ratio= 400/112 = 50:14 =3.57:1 Space savings=1-(112/400) = 1-(7/25) = 1-0.28 = 0.72 = 72% Average bits = 112/50 = 2.24bits per character TheConsolidatedCompressionratio,Space savings andAveragebitsforninesubjectsare as shown in the table 2. S.NoSubjectCompression Ratio Space savings Average bits 1Theory12.17391354%3.68 2Theory23.33333370%2.4 3Theory33.84615474%2.08 4Theory43.33333370%2.4 5Theory52.77777864%2.88 6Theory62.94117666%2.72 7Lab13.84615474%2.08 8Lab23.84615474%2.08 9Lab33.84615474%2.08 Table . 2.Consolidated Compression ratio, Space savings and Average bits for nine subjects with six theory and three lab. V.CONCLUSION TheobtainedresultsdepictsthattheRun-Length encodinggives better compression ratio, space savings, and average bitsfor the input with the long Run-Length. TheRun-LengthEncodinggivesbettercompression ratio,spacesavings, and average bits as compared with the uncompressed data. REFERENCE [1]https://en.wikipedia.org/wiki/Run-length_encoding [2]KhalidSayood,IntroductiontoData Compression,MorganKaufmannPublishers, Burlington,UnitedStatesofAmerica,2ndedition, 600pages, 2000. [3]MarkNelsonandJean-loupGailly,TheData CompressionBook,M&TBooks,NewYork, UnitedStatesofAmerica,2ndedition,541pages, 1995. [4]DavidSalomon,DataCompression:TheComplete Reference,Springer,NewYork,Berlin, Heidelberg,UnitedStatesofAmerica,Germany, 2nd edition, 823pages, 2000. [5]DavidSalomonandGiovanni Motta, Handbook of Data Compression, Springer London, 2000. [6]J.A.Storer,DataCompression,Computer Science Press, Rockville,MD,1988. I nternationalJournalofEngineeringTrendsandApplications(I JETA) Volume2I ssue4, July- Aug2015 ISSN:2393- 9516www.ijetajournal.orgPage 40 [7]E.Blelloch,IntroductiontoDataCompression, ComputerScienceDepartment,CarnegieMellon University, 2002. [8]Lynch,J.Thomas,DataCompression: Techniques andApplications,LifetimeLearningPublications, Belmont,CA, 1985 [9]RafaelC.Gonzalez,RichardE.Woods,Digital ImageProcessing, Pearson Education, 2002 [10] S.W.Golomb,Run-LengthEncodings,IEEE TransactionsonInformation Theory, vol. IT-12, no. 3, pp. 399401,July 1966.