[vc_empty_space][vc_empty_space]
Arithmetic coding modification to compress SMS
Husodo A.Y.a, Munir R.a
a Informatics Department, School of Electrical Engineering and Informatics, Institut Teknologi Bandung, Indonesia
[vc_row][vc_column][vc_row_inner][vc_column_inner][vc_separator css=”.vc_custom_1624529070653{padding-top: 30px !important;padding-bottom: 30px !important;}”][/vc_column_inner][/vc_row_inner][vc_row_inner layout=”boxed”][vc_column_inner width=”3/4″ css=”.vc_custom_1624695412187{border-right-width: 1px !important;border-right-color: #dddddd !important;border-right-style: solid !important;border-radius: 1px !important;}”][vc_empty_space][megatron_heading title=”Abstract” size=”size-sm” text_align=”text-left”][vc_column_text]This paper proposes an effective method to compress SMS by doing some modifications to arithmetic coding data compression mechanism. The aim of this proposal is to optimize the maximum character capacity of SMS body. Every character in SMS is mostly encoded in 7 bit and the maximum capacity of one SMS is only 1120 bit. Those SMS characteristics require a very efficient compression method to compress SMS. Arithmetic coding is a compression mechanism that works by converting a data message to a real code number between 0 and 1. Arithmetic coding provides nearly optimal data compression. However, it requires additional memory space in compresseddata to save arithmetic coding probability table for decompressing the compressed-data. Besides, it requires highprecision and effective encoder-decoder to calculate and represent its code number (compressed-data). In very limited data space like SMS, the need of additional memory space to save arithmetic coding probability table is inefficient. It will make the compressed-SMS size bigger than the original SMS (uncompressed SMS) size. To overcome this inefficiency, in this paper, the need of memory space is erased. This paper proposes semi dynamic probability table usage to compress and decompress SMS for overcoming the inefficient need of memory space. To more optimize the effectiveness and efficiency of proposed-method compression ratio, this paper also proposes a smart data representation to represent code number so that the number of bits needed to represent compressed-SMS can be well-minimized. By using this smart data representation, 2k digit decimal code number value in base-10 can be written by only using k default GSM 7 bit characters. The proposed compression mechanism in this paper has been researched plainly in mobile phone that uses Android operating system. The SMS data test language used on the research is Bahasa Indonesia. Based on the research, the compression ratio of proposed compression mechanism is vary depends on the content of SMS. The average compression ratio of proposed compression mechanism is 71%, while the maximum compression ratio is able to reach less than 25%, i.e. 500 character SMS can be compressed to 121 character SMS. © 2011 IEEE.[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Author keywords” size=”size-sm” text_align=”text-left”][vc_column_text]Arithmetic Coding,Code numbers,Compression mechanism,Compression methods,Data messages,Encoder-decoder,High-precision,Indonesia,Limited data,Memory space,modification,Probability tables,Real code,SMART datum,SMS,Test language[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Indexed keywords” size=”size-sm” text_align=”text-left”][vc_column_text]arithmetic coding,compression,modification,SMS[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Funding details” size=”size-sm” text_align=”text-left”][vc_column_text][/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”DOI” size=”size-sm” text_align=”text-left”][vc_column_text]https://doi.org/10.1109/ICEEI.2011.6021688[/vc_column_text][/vc_column_inner][vc_column_inner width=”1/4″][vc_column_text]Widget Plumx[/vc_column_text][/vc_column_inner][/vc_row_inner][/vc_column][/vc_row][vc_row][vc_column][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][/vc_column][/vc_row]