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河北工业大学

J2M: a Java to MapReduce translator for cloud computing.

Title: J2M: a Java to MapReduce translator for cloud computing.
Authors: Li, Bing1
Zhang, Junbo2
Yu, Ning1
Pan, Yi1 pan@cs.gsu.edu
Source: Journal of Supercomputing. May2016, Vol. 72 Issue 5, p1928-1945. 18p.
Document Type: Article
Subject Terms: JAVA (Computer program language)
CLOUD computing
COMPUTER software
COMPUTER programming
CODING theory
Author-Supplied Keywords: Cloud computing ; Code migration ; Java ; MapReduce
NAICS/Industry Codes: 417310 Computer, computer peripheral and pre-packaged software merchant wholesalers ; 423430 Computer and Computer Peripheral Equipment and Software Merchant Wholesalers ; 443144 Computer and software stores ; 511211 Software publishers (except video game publishers) ; 541514 Computer systems design and related services (except video game design and development) ; 541519 Other Computer Related Services ; 541511 Custom Computer Programming Services ; 518210 Data Processing, Hosting, and Related Services
Abstract: Cloud computing has gradually evolved into an infrastructural tool for a variety of scientific research and computing. It has become a trend that lots of products have been migrated from local servers to cloud by many institutions and organizations. One of the challenges in cloud computing now is how to run software efficiently on cloud platforms since lots of original codes are not capable of being executed in parallel on cloud contexts, resulting in that the power of clouds cannot be exerted well. It is costly to redesign and convert current sequential codes into cloud platform. Thus, automatic translation from sequential code to cloud code is one of the directions that could be taken to resolve the problem of code migration in cloud infrastructure. In this paper, a new Java to MapReduce (J2M) translator is developed to achieve the automatic translation from sequential Java to cloud for specific data-parallel code with large loops. This paper will provide details about the design of our translator and evaluate our performance through experiments. The experimental results not only indicate that the translator can precisely translate the sequential Java into cloud codes, but also show that it can achieve very good speedup in performance, and we expect that an almost linear speedup is possible if larger enough data is processed. It is believed that the J2M translator is an ideal stereotype for code migration and will play an important role in the transition era of cloud computing. [ABSTRACT FROM AUTHOR]
(Copyright applies to all Abstracts.)
Author Affiliations: 1Department of Computer Science, Georgia State University, Atlanta 30303 USA ; 2School of Information Science and Technology, Southwest Jiaotong University, Chengdu 610031 China
ISSN: 0920-8542 (Sherpa/RoMEO, JCR)
PageCount: 1928-1946
volume: 72
issue: 5
issn: 09208542
pubdate: 2016
DOI: https://doi.org/10.1007/s11227-016-1695-x