Data collection and restoration for heterogeneous process migration

Authors

  • Kasidit Chanchio,

    1. Department of Computer Science, Illinois Institute of Technology, Chicago, IL 60616, U.S.A.
    Current affiliation:
    1. Computer Science and Mathematics Division, Oak Ridge National Laboratory
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  • Xian-He Sun

    Corresponding author
    1. Department of Computer Science, Illinois Institute of Technology, Chicago, IL 60616, U.S.A.
    • Department of Computer Science, Illinois Institute of Technology, Chicago, IL 60616, U.S.A.
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Abstract

This study presents a practical solution for data collection and restoration to migrate a process written in high-level stack-based languages such as C and Fortran over a network of heterogeneous computers. We first introduce a logical data model, namely the Memory Space Representation (MSR) model, to recognize complex data structures in process address space. Then, novel methods are developed to incorporate the MSR model into a process, and to collect and restore data efficiently. We have implemented prototype software and performed experiments on different programs. Experimental and analytical results show that: (1) a user-level process can be migrated across different computing platforms; (2) semantic information of data structures in the process's memory space can be correctly collected and restored; (3) costs of data collection and restoration depend on the complexity of the MSR graph in the memory space and the amount of data involved; and (4) the implantation of the MSR model into the process is not a decisive factor of incurring execution overheads. With appropriate program analysis, we can practically achieve low overhead. Copyright © 2002 John Wiley & Sons, Ltd.

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