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        <identifier>oai:www.ideals.illinois.edu:2142/116124</identifier>
        <datestamp>2023-07-11</datestamp>
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          <dc:contributor>Mohan, Sibin</dc:contributor>
          <dc:date>2022-08</dc:date>
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          <dc:language>en</dc:language>
          <dc:type>text</dc:type>
          <dc:description>Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2024-08-01</dc:description>
          <dc:description>The student, Vishakh Suresh Babu, accepted the attached license on 2022-07-20 at 15:45.</dc:description>
          <dc:description>The student, Vishakh Suresh Babu, submitted this Thesis for approval on 2022-07-20 at 16:36.</dc:description>
          <dc:description>This Thesis was approved for publication on 2022-07-21 at 10:18.</dc:description>
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          <dc:title>Forecasting resource availability for supporting real-time container migration</dc:title>
          <dc:creator>Suresh Babu, Vishakh</dc:creator>
          <dc:date>2022-07-21</dc:date>
          <dc:subject>Real-time</dc:subject>
          <dc:subject>Container</dc:subject>
          <dc:subject>Migration</dc:subject>
          <dc:subject>Forecasting</dc:subject>
          <dc:description>Hard real-time applications have stringent response time requirements and failure to meet the deadlines can have catastrophic consequences. With the success of the edge computing paradigm, more edge applications have real-time requirements. User mobility and multi-tenancy on the edge nodes create new challenges for these real-time applications running inside containers. These problems can be resolved by migrating the container along with all of the underlying files to a new node where the application can run safely. However, single-target migration is prone to failure due to network issues or system crashes at the target. It is also hard to guarantee that applications will meet their real-time requirements during (or even after) the migration process.
To this end, we propose a framework for planning reliable real-time container migration. This framework monitors the container and nodes in the network and accurately predicts the future resource availability of the nodes. The forecasts are used to identify a subset of nodes that have sufficient resources to run the container. We migrate to multiple nodes in parallel to make it resilient to network issues and crashes.</dc:description>
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          <dc:identifier>https://hdl.handle.net/2142/116124</dc:identifier>
          <dc:rights>Copyright 2022 Vishakh Suresh Babu</dc:rights>
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            <level>Thesis</level>
            <discipline>Computer Science</discipline>
            <grantor>University of Illinois at Urbana-Champaign</grantor>
            <department>Computer Science</department>
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