Distributed stream processing at edge

Please use this identifier to cite or link to this item: http://repository.iiitd.edu.in/xmlui/handle/123456789/1409

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DC Field	Value	Language
dc.contributor.author	Choudhary, Aditya	-
dc.contributor.author	Chak, Ayush Raje	-
dc.contributor.author	Shah, Rajiv Ratn (Advisor)	-
dc.date.accessioned	2024-05-08T12:39:18Z	-
dc.date.available	2024-05-08T12:39:18Z	-
dc.date.issued	2023-11-23	-
dc.identifier.uri	http://repository.iiitd.edu.in/xmlui/handle/123456789/1409	-
dc.description.abstract	A vast amount of data is produced by billions of modern devices each year. An effective Stream Processing Engine (SPE) is needed to arrange and handle this data. Among the well-known SPEs are Apache Hadoop, Apache Spark, and Apache Storm. SPE researchers are working hard to improve their efficiency, and one area of study uses these techniques in a distributed edge setting. after reading through a number of SPE research papers. EdgeWise: A Better Stream Processing Engine for the Edge has been put into practice and tested. This study attempts to optimize Apache Storm's performance by adjusting the threads' OS-level scheduling. Driven by the same, our objective is to enhance Apache Storm's throughput and latency.	en_US
dc.language.iso	en_US	en_US
dc.publisher	IIIT-Delhi	en_US
dc.subject	Apache Storm	en_US
dc.subject	Edge Computing	en_US
dc.subject	Stream Processing	en_US
dc.title	Distributed stream processing at edge	en_US
dc.type	Other	en_US
Appears in Collections:	Year-2023

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