Electronic Thesis and Dissertation Repository

Thesis Format

Integrated Article

Degree

Doctor of Philosophy

Program

Computer Science

Supervisor

Lutfiyya, Hanan

Abstract

Mobile IoT applications often require low response time and high bandwidth. These applications include virtual reality, augmented reality, and online gaming. Currently, most data processing is done in the cloud. However, for latency-sensitive applications, the latency may need to be reduced. Edge and fog computing can be used to place application services close to mobile devices to reduce latency. However, as mobile devices move, latency increases, which can be decreased by moving the service to a closer edge/fog server. This can be addressed by migrating services so that the mobile device can receive services from the new server. These services can be run on a single or multiple virtual machines or containers.

Application services must be migrated together. Delays in multi-service migration can occur because some application services migrate faster than others, requiring them to wait for the rest of the services to migrate before continuing their tasks. However, in the last decade, most migration research has focused on cloud computing rather than edge and fog computing. Furthermore, migration methods and models are primarily intended for cloud applications.

This thesis focuses on migration techniques for managing IoT applications in edge and fog computing environments while considering the characteristics of IoT applications, the networking characteristics of the edge and fog servers, and the migration parameters of running IoT applications. This thesis contributes to the current state of the art by presenting the following contributions in fog and edge computing environments:

  1. A comprehensive literature review and limitations on the migration of IoT applications from different perspectives, namely downtime and migration time reduction strategies, optimization techniques, and identifying critical parameters of migration.
  2. A new migration method for latency-sensitive IoT applications to reduce downtime and migration time, including performance evaluations and comparisons to well-known migration methods.
  3. New comprehensive models with non-average parameter values for higher precision and accuracy, including comparative analysis of the parameters that impact the performance of the investigated migration methods.
  4. A new bandwidth allocation strategy for multi-service migrations of IoT applications to reduce downtime and migration time, including performance evaluations.

Summary for Lay Audience

Internet-of-things (IoT) and cloud computing have been well-known in the last decade. However, there will be a data surge soon with massive data generation by IoT applications that the cloud cannot tolerate. Furthermore, mobile IoT applications often require low response time and high bandwidth. These applications include virtual reality, augmented reality, and online gaming. Currently, most data processing is done in the cloud. However, for latency-sensitive applications, the latency may need to be reduced. Edge and fog computing can be used to place application services in servers close to mobile devices to reduce latency. However, as mobile devices move, latency increases, which can be decreased by moving the service to a closer edge/fog server. Migrating services can address this so the mobile device can receive services from the new server.

Mobile device service migration for multi-service applications is critical in edge and fog computing. With the growing use of multi-service applications, it is critical to ensure that all application services complete their migration in parallel to avoid waiting time and additional delays in latency-sensitive applications. Delays in multi-service migration can occur because some application services migrate faster than others, requiring them to wait for the rest of the services to migrate before continuing their tasks and remaining operational. However, in the last decade, most migration research has focused on cloud computing rather than edge and fog computing. Furthermore, migration methods and models are primarily intended for cloud applications. The advancement of technology, the introduction of 5G and 6G networks, and evolving applications create a demand for migration techniques in edge and fog computing to support mobility with low response time.

The edge and fog computing paradigms are dynamic, distributed, and heterogeneous. Therefore, it is challenging to fully exploit the capabilities of this computing paradigm for various IoT-driven application scenarios in the absence of effective migration strategies for IoT application management.

This thesis focuses on various migration techniques for managing IoT applications in edge and fog computing environments while considering the characteristics of IoT applications and networking of the edge and fog servers and the migration parameters of running IoT applications.

Creative Commons License

Creative Commons Attribution 4.0 License
This work is licensed under a Creative Commons Attribution 4.0 License.

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