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Framework for Green Search Engine Design

IJCA Proceedings on National Conference on Knowledge, Innovation in Technology and Engineering (NCKITE 2015)
© 2015 by IJCA Journal
NCKITE 2015 - Number 3
Year of Publication: 2015
Kapil Kumar Nagwanshi
Praval Kumar Jha
Sipi Dubey

Kapil Kumar Nagwanshi, Praval Kumar Jha and Sipi Dubey. Article: Framework for Green Search Engine Design. IJCA Proceedings on National Conference on Knowledge, Innovation in Technology and Engineering (NCKITE 2015) NCKITE 2015(3):25-28, July 2015. Full text available. BibTeX

	author = {Kapil Kumar Nagwanshi and Praval Kumar Jha and Sipi Dubey},
	title = {Article: Framework for Green Search Engine Design},
	journal = {IJCA Proceedings on National Conference on Knowledge, Innovation in Technology and Engineering (NCKITE 2015)},
	year = {2015},
	volume = {NCKITE 2015},
	number = {3},
	pages = {25-28},
	month = {July},
	note = {Full text available}


Traditional search engines use a thin client, distributed model for crawling. This crawler based approach has certain drawbacks which could be removed with a proposed rich client based model. The rich client based search engine offers faster crawling and better updation time using lesser resources than thin client model, and it covers more of the World Wide Web than normal crawler based search engines. Although modern day search engine giants have improvised on various features such as ergonomics and utilities, along with several added goodies, little work is done to improve energy efficiency of such Large Scale Search Engines. As the Internet is increasing exponentially the search engines will involve more and more servers thus costing more and more energy. This ever increasing demand of search engines needs to be curbed down. Rather than multiplying server resources it is better to use existing servers which work in a congenial environment, using communication methods to reduce redundant downloading of data from different servers by the crawlers. This paper proposes a rich client based architecture for search engines along with analysis and comparison with present search engines. This could help into reducing the challenges of global warming, keeping up the speed and efficiency requirements.


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