A Simple Algorithm for Data Compression in Wireless Sensor Networks
Power saving is a critical issue in wireless sensor networks (WSNs) since sensor nodes are powered by batteries which cannot be generally changed or recharged. As radio communication is often the main cause of energy consumption, extension of sensor node lifetime is generally achieved by reducing tr...
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| Veröffentlicht in: | IEEE communications letters 2008-06, Vol.12 (6), p.411-413 |
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| container_title | IEEE communications letters |
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| creator | Marcelloni, F. Vecchio, M. |
| description | Power saving is a critical issue in wireless sensor networks (WSNs) since sensor nodes are powered by batteries which cannot be generally changed or recharged. As radio communication is often the main cause of energy consumption, extension of sensor node lifetime is generally achieved by reducing transmissions/receptions of data, for instance through data compression. Exploiting the natural correlation that exists in data typically collected by WSNs and the principles of entropy compression, in this Letter we propose a simple and efficient data compression algorithm particularly suited to be used on available commercial nodes of a WSN, where energy, memory and computational resources are very limited. Some experimental results and comparisons with, to the best of our knowledge, the only lossless compression algorithm previously proposed in the literature to be embedded in sensor nodes and with two well- known compression algorithms are shown and discussed. |
| doi_str_mv | 10.1109/LCOMM.2008.080300 |
| format | Article |
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As radio communication is often the main cause of energy consumption, extension of sensor node lifetime is generally achieved by reducing transmissions/receptions of data, for instance through data compression. Exploiting the natural correlation that exists in data typically collected by WSNs and the principles of entropy compression, in this Letter we propose a simple and efficient data compression algorithm particularly suited to be used on available commercial nodes of a WSN, where energy, memory and computational resources are very limited. Some experimental results and comparisons with, to the best of our knowledge, the only lossless compression algorithm previously proposed in the literature to be embedded in sensor nodes and with two well- known compression algorithms are shown and discussed.</description><identifier>ISSN: 1089-7798</identifier><identifier>EISSN: 1558-2558</identifier><identifier>DOI: 10.1109/LCOMM.2008.080300</identifier><identifier>CODEN: ICLEF6</identifier><language>eng</language><publisher>New York, NY: IEEE</publisher><subject>Algorithms ; Applied sciences ; Batteries ; Coding, codes ; Compressing ; Compression algorithms ; Data compression ; Energy consumption ; Energy use ; Entropy ; Exact sciences and technology ; Information, signal and communications theory ; Miscellaneous ; Monitoring ; Networks ; Radio communication ; Radio communications ; Sensor phenomena and characterization ; Sensors ; Services and terminals of telecommunications ; Signal and communications theory ; Signal processing ; Signal processing algorithms ; Systems, networks and services of telecommunications ; Telecommunications ; Telecommunications and information theory ; Telemetry. 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As radio communication is often the main cause of energy consumption, extension of sensor node lifetime is generally achieved by reducing transmissions/receptions of data, for instance through data compression. Exploiting the natural correlation that exists in data typically collected by WSNs and the principles of entropy compression, in this Letter we propose a simple and efficient data compression algorithm particularly suited to be used on available commercial nodes of a WSN, where energy, memory and computational resources are very limited. Some experimental results and comparisons with, to the best of our knowledge, the only lossless compression algorithm previously proposed in the literature to be embedded in sensor nodes and with two well- known compression algorithms are shown and discussed.</description><subject>Algorithms</subject><subject>Applied sciences</subject><subject>Batteries</subject><subject>Coding, codes</subject><subject>Compressing</subject><subject>Compression algorithms</subject><subject>Data compression</subject><subject>Energy consumption</subject><subject>Energy use</subject><subject>Entropy</subject><subject>Exact sciences and technology</subject><subject>Information, signal and communications theory</subject><subject>Miscellaneous</subject><subject>Monitoring</subject><subject>Networks</subject><subject>Radio communication</subject><subject>Radio communications</subject><subject>Sensor phenomena and characterization</subject><subject>Sensors</subject><subject>Services and terminals of telecommunications</subject><subject>Signal and communications theory</subject><subject>Signal processing</subject><subject>Signal processing algorithms</subject><subject>Systems, networks and services of telecommunications</subject><subject>Telecommunications</subject><subject>Telecommunications and information theory</subject><subject>Telemetry. 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Remote control</subject><subject>Wireless sensor networks</subject><issn>1089-7798</issn><issn>1558-2558</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2008</creationdate><recordtype>article</recordtype><sourceid>RIE</sourceid><recordid>eNp90LtOwzAUBuAIgQQUHgCxREgglpTja5yxClephQEQY-S6J-CSxMVOhXh7XFoxMLD4In_n2P6T5IjAkBAoLsblw2QypABqCAoYwFayR4RQGY3DdlyDKrI8L9Rush_CHCKkguwl5Sh9tO2iwXTUvDpv-7c2rZ1PL3Wv09K1C48hWNeltktfrMcmbtNH7EI099h_Ov8eDpKdWjcBDzfzIHm-vnoqb7Pxw81dORpnhgvaZ0iIlIrMBEKOQKjRjIJmjGgmABinxjDgDFmR1zWfstlUzySIXE2VBmJqNkjO1n0X3n0sMfRVa4PBptEdumWoWLxGsAIiPP8XEmCEUUlzGunJHzp3S9_Fb1RKUhXfJXlEZI2MdyF4rKuFt632X7FTtYq_-om_WsVfreOPNaebxjoY3dRed8aG30IKnEjBVXTHa2cR8feYC05zKdk32c2LTQ</recordid><startdate>20080601</startdate><enddate>20080601</enddate><creator>Marcelloni, F.</creator><creator>Vecchio, M.</creator><general>IEEE</general><general>Institute of Electrical and Electronics Engineers</general><general>The Institute of Electrical and Electronics Engineers, Inc. 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Remote supervision. Telewarning. Remote control</topic><topic>Wireless sensor networks</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Marcelloni, F.</creatorcontrib><creatorcontrib>Vecchio, M.</creatorcontrib><collection>IEEE All-Society Periodicals Package (ASPP) 2005-present</collection><collection>IEEE All-Society Periodicals Package (ASPP) 1998-Present</collection><collection>IEEE Electronic Library (IEL)</collection><collection>Pascal-Francis</collection><collection>CrossRef</collection><collection>Electronics & Communications Abstracts</collection><collection>Technology Research Database</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>ANTE: Abstracts in New Technology & Engineering</collection><collection>Engineering Research Database</collection><jtitle>IEEE communications letters</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Marcelloni, F.</au><au>Vecchio, M.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>A Simple Algorithm for Data Compression in Wireless Sensor Networks</atitle><jtitle>IEEE communications letters</jtitle><stitle>COML</stitle><date>2008-06-01</date><risdate>2008</risdate><volume>12</volume><issue>6</issue><spage>411</spage><epage>413</epage><pages>411-413</pages><issn>1089-7798</issn><eissn>1558-2558</eissn><coden>ICLEF6</coden><abstract>Power saving is a critical issue in wireless sensor networks (WSNs) since sensor nodes are powered by batteries which cannot be generally changed or recharged. As radio communication is often the main cause of energy consumption, extension of sensor node lifetime is generally achieved by reducing transmissions/receptions of data, for instance through data compression. Exploiting the natural correlation that exists in data typically collected by WSNs and the principles of entropy compression, in this Letter we propose a simple and efficient data compression algorithm particularly suited to be used on available commercial nodes of a WSN, where energy, memory and computational resources are very limited. Some experimental results and comparisons with, to the best of our knowledge, the only lossless compression algorithm previously proposed in the literature to be embedded in sensor nodes and with two well- known compression algorithms are shown and discussed.</abstract><cop>New York, NY</cop><pub>IEEE</pub><doi>10.1109/LCOMM.2008.080300</doi><tpages>3</tpages></addata></record> |
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| ispartof | IEEE communications letters, 2008-06, Vol.12 (6), p.411-413 |
| issn | 1089-7798 1558-2558 |
| language | eng |
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| source | IEEE Electronic Library (IEL) |
| subjects | Algorithms Applied sciences Batteries Coding, codes Compressing Compression algorithms Data compression Energy consumption Energy use Entropy Exact sciences and technology Information, signal and communications theory Miscellaneous Monitoring Networks Radio communication Radio communications Sensor phenomena and characterization Sensors Services and terminals of telecommunications Signal and communications theory Signal processing Signal processing algorithms Systems, networks and services of telecommunications Telecommunications Telecommunications and information theory Telemetry. Remote supervision. Telewarning. Remote control Wireless sensor networks |
| title | A Simple Algorithm for Data Compression in Wireless Sensor Networks |
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