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E-storm: real-time energy efficient data analysis adapting storm platform
Rajasekhara, Babu M1, Patan, Rizwan2.
It is necessary to model an energy efficient and stream optimization towards achieve
high energy efficiency for Streaming data without degrading response time in big data
stream computing. This paper proposes an Energy Efficient Traffic aware resource
scheduling and Re-Streaming Stream Structure to replace a default scheduling
strategy of storm is entitled as re-storm. The model described in three parts; First, a
mathematical relation among energy consumption, low response time and high traffic
streams. Second, various approaches provided for reducing an energy without
affecting response time and which provides high performance in overall stream
computing in big data. Third, re-storm deployed energy efficient traffic aware
scheduling on the storm platform. It allocates worker nodes online by using hotswapping
technique with task utilizing by energy consolidation through graph
partitioning. Moreover, re-storm is achieved high energy efficiency, low response time
in all types of data arriving speeds.it is suitable for allocation of worker nodes in a storm
topology. Experiment results have been demonstrated the comparing existing
strategies which are dealing with energy issues without affecting or reducing response
time for a different data stream speed levels. Finally, it shows that the re-storm platform
achieved high energy efficiency and low response time when compared to all existing
approaches.
Affiliation:
- VIT University, India
- VIT University, India
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Indexation |
Indexed by |
MyJurnal (2021) |
H-Index
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6 |
Immediacy Index
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0.000 |
Rank |
0 |
Indexed by |
Scopus 2020 |
Impact Factor
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CiteScore (1.4) |
Rank |
Q3 (Engineering (all)) |
Additional Information |
SJR (0.191) |
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