Elastic Process: A Framework for Joint Disaggregation of Memory and Computation in Linux / Zaid Alali.

Scaling is essential in cloud computing to accommodate the variable need for resources by different applications. Scaling is always associated with the challenge of distributing resources, and this challenge usually stems from the fact that the underlying operating system is designed to be monolithi...

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Bibliographic Details
Online Access: Connect to online resource
Main Author: Alali, Zaid (Author)
Format: Thesis Electronic eBook
Language:English
Published: Ann Arbor : ProQuest Dissertations & Theses, 2023
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245 1 0 |a Elastic Process: A Framework for Joint Disaggregation of Memory and Computation in Linux /  |c Zaid Alali. 
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500 |a Source: Dissertations Abstracts International, Volume: 84-11, Section: B. 
500 |a Advisors: Han, Richard Committee members: Keller, Eric; Rozner, Eric; Ha, Sangtae; Mishra, Shiv. 
502 |b Ph.D.  |c University of Colorado at Boulder  |d 2023. 
506 |a This item is not available from ProQuest Dissertations & Theses. 
520 |a Scaling is essential in cloud computing to accommodate the variable need for resources by different applications. Scaling is always associated with the challenge of distributing resources, and this challenge usually stems from the fact that the underlying operating system is designed to be monolithic. Past efforts have attempted to break the monolithic design of the operating system like "ElasticOS" and "LegoOS" and introduce distributed resource management primitives to the operating system. However, previous efforts either suffered from performance degradation or faced a severe development challenge that requires modifying the complex monolithic source code of Linux kernel. We propose Elastic Process; an auto scaling framework with a new approach to achieve joint disaggregation of memory and compute primarily in userspace. By using tools like "Ptrace" and "CRIU" we were able to build a prototype that demonstrates joint disaggregation of memory and computation. Our test results on macro applications and off-the-shelf application shows execution time performance improvement as well as network traffic reduction when compared to remote swap approach. Our results for macro application also shows more performance improvement when using multiple threads. 
546 |a English 
590 |a School code: 0051 
650 4 |a Computer science. 
650 4 |a Computer engineering. 
650 4 |a Information technology. 
653 |a Auto-scaling 
653 |a Cloud computing 
653 |a CRIU 
653 |a Ptrace 
653 |a Scaling 
653 |a Operating system 
653 |a Performance improvement 
655 |a Theses  |x CU Boulder  |x Computer Science.  |2 local. 
700 1 |a Han, Richard  |e degree supervisor. 
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791 |a Ph.D. 
792 |a 2023 
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