abstract

Technology Migration Challenges in a Big Data Architecture Stack

Authors:

Rekha Singhal,

Shruti KundeAuthors Info & Claims

ICPE '17: Proceedings of the 8th ACM/SPEC on International Conference on Performance Engineering

Pages 159 - 160

https://doi.org/10.1145/3030207.3053670

Published: 17 April 2017 Publication History

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Abstract

Application and/or data migration is a result of limitations in existing system architecture to handle new requirements and the availability of newer, more efficient technology. In any big data architecture, technology migration is staggered across multiple levels and poses functional (related to components of the architecture and underlying infrastructure) and non-functional (QoS) challenges such as availability, reliability and performance guarantees in the target architecture. In this paper, (1) we outline a big data architecture stack and identify research problems arising out of the technology migration in this scenario (2) we propose a smart rule engine system which facilitates the decision making process for the technology to be used at different layers in the architecture during migration.

References

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Performance Evaluation of Messaging Brokers. http://www.eharmony.com/engineering/in-pursuitof-messaging-brokers/.

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Z. Bian, K. Wang, Z. Wang, G. Munce, I. Cremer, W. Zhou, Q. Chen, and G. Xu. Simulating big data clusters for system planning, evaluation and optimization. In Proceedings of 43rd International Conference on Parallel Processing, 2014.

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[4]

S. Mazumder. Big Data Tools and Platforms. Springer, 2016.

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Index Terms

Technology Migration Challenges in a Big Data Architecture Stack
1. Applied computing
  1. Enterprise computing
    1. Enterprise architectures
      1. Enterprise architecture frameworks
      2. Enterprise architecture modeling

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Published In

ICPE '17: Proceedings of the 8th ACM/SPEC on International Conference on Performance Engineering

April 2017

450 pages

ISBN:9781450344043

DOI:10.1145/3030207

General Chairs:
Walter Binder
Università della Svizzera Italiana, Switzerland
,
Vittorio Cortellessa
Università dell'Aquila, Italy
,
Program Chairs:
Anne Koziolek
Karlsruhe Institute of Technology, Germany
,
Evgenia Smirni
College of William & Mary, USA
,
Meikel Poess
Oracle Corporation, USA

Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 17 April 2017

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Conference

ICPE '17

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ICPE '17: ACM/SPEC International Conference on Performance Engineering

April 22 - 26, 2017

L'Aquila, Italy

Acceptance Rates

ICPE '17 Paper Acceptance Rate 27 of 83 submissions, 33%;

Overall Acceptance Rate 252 of 851 submissions, 30%

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