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2015•Research Archive of Indian Institute of Technology Hyderabad (Indian Institute of Technology Hyderabad)Requires access

Streaming Algorithms and Parameterized Streaming

B S Natti

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Abstract

Over the last few years, there has been considerable amount of study and work on developing algorithms for processing massive graphs in the data stream model. Storing massive graphs in the memory of a single machine is not practical which is what the motivation behind data stream algorithms. To obtain space and time efficient algorithms, we develop streaming/semi-streaming algorithms where it is reasonable to assume that the input graph arrives as a stream of edges. We can process the input in either one or multiple passes and the working memory space is restricted.

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What this paper is about

Over the last few years, there has been considerable amount of study and work on developing algorithms for processing massive graphs in the data stream model. Storing massive graphs in the memory of a single machine is not practical which is what the motivation behind data stream algorithms. To obtain space and time efficient algorithms, we develop streaming/semi-streaming algorithms where it is reasonable to assume that the input graph arrives as a stream of edges. We can process the input in either one or multiple passes and the working memory space is restricted.

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Available abstract

Over the last few years, there has been considerable amount of study and work on developing algorithms for processing massive graphs in the data stream model. Storing massive graphs in the memory of a single machine is not practical which is what the motivation behind data stream algorithms. To obtain space and time efficient algorithms, we develop streaming/semi-streaming algorithms where it is reasonable to assume that the input graph arrives as a stream of edges. We can process the input in either one or multiple passes and the working memory space is restricted.

Key concepts: Streaming algorithm, Streaming data, Computer science, Parameterized complexity, Data stream, Algorithm, Graph, Process (computing)

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