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ANALYSIS RESOURCE AWARE FRAMEWORK BY COMBINING SUNSPOT AND IMOTE2 PLATFORM WIRELESS SENSOR NETWORKS USING DISTANCE VECTOR ALGORITHM

Jurnal Ilmu Komputer dan Informasi (JIKI) · Vol. 5 No. 2 (2012) · pp. 98–105

DOI
10.21609/jiki.v5i2.195
ISSN
2502-9274, 2088-7051
Published
2012-07-29
Publisher
Faculty of Computer Science - Universitas Indonesia
Language
eng

Abstract

Efficiency energy and stream data mining on Wireless Sensor Networks (WSNs) are a very interesting issue to be discussed. Routing protocols technology and resource-aware can be done to improve energy efficiency. In this paper we try to merge routing protocol technology using routing Distance Vector and Resource-Aware (RA) framework on heterogeneity wireless sensor networks by combining sun-SPOT and Imote2 platform wireless sensor networks. RA perform resource monitoring process of the battery, memory and CPU load more optimally and efficiently. The process uses Light-Weight Clustering (LWC) and Light Weight Frequent Item (LWF). The results obtained that by adapting Resource-Aware in wireless sensor networks, the lifetime of wireless sensor improve up to ± 16.62%. Efisiensi energi dan stream data mining pada Wireless Sensor Networks (WSN) adalah masalah yang sangat menarik untuk dibahas. Teknologi Routing Protocol dan Resource-Aware dapat dilakukan untuk meningkatkan efisiensi energi. Dalam penelitian ini peneliti mencoba untuk menggabungkan teknologi Routing Protocol menggunakan routing Distance Vector dan Resource-Aware (RA) framework pada Wireless Sensor Networks heterogen dengan menggabungkan sun-SPOT dan platform Imote2 Wireless Sensor Networks. RA melakukan proses pemantauan sumber daya dari memori, baterai, dan beban CPU lebih optimal dan efisien. Proses ini menggunakan Light-Weight Clustering (LWC) dan Light Weight Frequent Item (LWF). Hasil yang diperoleh bahwa dengan mengadaptasi Resource-Aware dalam Wireless Sensor Networks, masa pakai wireless sensor meningkatkan sampai ± 16,62%.

Keywords

Collaboration network of the authors

23 authors · 45 co-authorship links · 15 across different organisations

Hover or tap a name to highlight its co-authors. Double-click to open the author's page.

  • Institut Teknologi Sepuluh Nopember
  • Politeknik Negeri Ujung Pandang
  • State University of Makassar
  • Universitas Wijaya Kusuma Surabaya
  • Universitas Papua
  • Universitas Muhammadiyah Banjarmasin
  • Lambung Mangkurat University
  • Affiliation unknown
  • Different organisations
  • Same organisation
  • Affiliation unknown
  • Thicker line = more joint articles · bigger circle = more articles
Show as table
Co-authorOrganisationJoint articles
Radityo AnggoroInstitut Teknologi Sepuluh Nopember5
Ary Mazharuddin ShiddiqiInstitut Teknologi Sepuluh Nopember3
Muchammad HusniInstitut Teknologi Sepuluh Nopember2
Faosan MapaAffiliation unknown1
Rakhmadany PrimanandaAffiliation unknown1
Noven Indra PrasetyaUniversitas Wijaya Kusuma Surabaya1
Parma Hadi RantelinggiUniversitas Papua1
Wiwien WindiantoAffiliation unknown1
Muhammad Ziki ElfirmanUniversitas Muhammadiyah Banjarmasin1
Rachmat RachmatInstitut Teknologi Sepuluh Nopember1
Faishal Halim SaputraInstitut Teknologi Sepuluh Nopember1
Rizky Fenaldo MaulanaInstitut Teknologi Sepuluh Nopember1
Waskitho WibisonoInstitut Teknologi Sepuluh Nopember1
Wahyu SuadiInstitut Teknologi Sepuluh Nopember1
Henning Titi CiptaningtyasInstitut Teknologi Sepuluh Nopember1
Muhammad AlkaffLambung Mangkurat University1
Handayani TjandrasaInstitut Teknologi Sepuluh Nopember1
Edio da CostaInstitut Teknologi Sepuluh Nopember1

Affiliations come from OpenAlex; journal OAI-PMH metadata carries none. Authors without an OpenAlex ID are matched by name, which can merge or split people.

Metadata source: OAI-PMH (metadata jurnal) https://jiki.cs.ui.ac.id/index.php/jiki/oai, first harvested 26 Okt 2026, last seen 26 Okt 2026.
Original metadata (oai_dc) 
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	<dc:title xml:lang="en-US">ANALYSIS RESOURCE AWARE FRAMEWORK BY COMBINING SUNSPOT AND IMOTE2 PLATFORM WIRELESS SENSOR NETWORKS USING DISTANCE VECTOR ALGORITHM</dc:title>
	<dc:creator>Syarif, Muhammad Ilyas</dc:creator>
	<dc:creator>Indrawan, Andi Wawan</dc:creator>
	<dc:creator>Parenreng, Jumadi M</dc:creator>
	<dc:creator>Djanali, Supeno</dc:creator>
	<dc:creator>Shiddiqi, Ary Masharuddin</dc:creator>
	<dc:subject xml:lang="en-US">distance vector</dc:subject>
	<dc:subject xml:lang="en-US">resource-aware</dc:subject>
	<dc:subject xml:lang="en-US">light weight clustering</dc:subject>
	<dc:subject xml:lang="en-US">light weight frequent item</dc:subject>
	<dc:subject xml:lang="en-US">sunspot</dc:subject>
	<dc:subject xml:lang="en-US">imote2</dc:subject>
	<dc:description xml:lang="en-US">Efficiency energy and stream data mining on Wireless Sensor Networks (WSNs) are a very interesting issue to be discussed. Routing protocols technology and resource-aware can be done to improve energy efficiency. In this paper we try to merge routing protocol technology using routing Distance Vector and Resource-Aware (RA) framework on heterogeneity wireless sensor networks by combining sun-SPOT and Imote2 platform wireless sensor networks. RA perform resource monitoring process of the battery, memory and CPU load more optimally and efficiently. The process uses Light-Weight Clustering (LWC) and Light Weight Frequent Item (LWF). The results obtained that by adapting Resource-Aware in wireless sensor networks, the lifetime  of wireless sensor improve up to ± 16.62%.

Efisiensi energi dan stream data mining pada Wireless Sensor Networks (WSN) adalah masalah yang sangat menarik untuk dibahas. Teknologi Routing Protocol dan Resource-Aware dapat dilakukan untuk meningkatkan efisiensi energi. Dalam penelitian ini peneliti mencoba untuk menggabungkan teknologi Routing Protocol menggunakan routing Distance Vector dan Resource-Aware (RA) framework pada Wireless Sensor Networks heterogen dengan menggabungkan sun-SPOT dan platform Imote2 Wireless Sensor Networks. RA melakukan proses pemantauan sumber daya dari memori, baterai, dan beban CPU lebih optimal dan efisien. Proses ini menggunakan Light-Weight Clustering (LWC) dan Light Weight Frequent Item (LWF). Hasil yang diperoleh bahwa dengan mengadaptasi Resource-Aware dalam Wireless Sensor Networks, masa pakai wireless sensor meningkatkan sampai ± 16,62%.</dc:description>
	<dc:publisher xml:lang="en-US">Faculty of Computer Science  - Universitas Indonesia</dc:publisher>
	<dc:date>2012-07-29</dc:date>
	<dc:type>info:eu-repo/semantics/article</dc:type>
	<dc:type>info:eu-repo/semantics/publishedVersion</dc:type>
	<dc:format>application/pdf</dc:format>
	<dc:identifier>https://jiki.cs.ui.ac.id/index.php/jiki/article/view/195</dc:identifier>
	<dc:identifier>10.21609/jiki.v5i2.195</dc:identifier>
	<dc:source xml:lang="en-US">Jurnal Ilmu Komputer dan Informasi; Vol. 5 No. 2 (2012): Jurnal Ilmu Komputer dan Informasi (Journal of Computer Science and Information); 98-105</dc:source>
	<dc:source>2502-9274</dc:source>
	<dc:source>2088-7051</dc:source>
	<dc:source>10.21609/jiki.v5i2</dc:source>
	<dc:language>eng</dc:language>
	<dc:relation>https://jiki.cs.ui.ac.id/index.php/jiki/article/view/195/293</dc:relation>
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