Fog Computing (FC) extends the Cloud towards the network edge. It provides end devices with access to resources and services that are located in topological proximity to them. This proximity enables key benefits (e.g., low latencies, reduced bandwidth consumption) that are not achievable when relying on Cloud-only solutions. FC is a horizontal paradigm in the sense that it is generic enough to be leveraged in a number of different application domains. However, its characteristics make it particularly suitable for the Internet of Things (IoT). After providing a survey on FC for the IoT, this thesis focuses on a specific research problem introduced with FC: the issue raised by device mobility in a FC environment. When a (IoT) device moves, the topological distance to the current Fog node (i.e., the Fog resource hosting the Fog service) may increase. Therefore, device mobility may impair the FC benefits, which are a result of Fog proximity. The objective is to support device mobility, namely to provide the FC benefits even in the presence of mobile devices. The most popular approach in literature to achieve this purpose is by migrating the Fog service across the Fog infrastructure, thus to let it be always close enough to the served mobile device. We refer to this paradigm as Companion Fog Computing (CFC), an extension of standard FC where the Fog service behaves as a "companion" of the mobile application. In this thesis, we first analyse the different aspects that characterise CFC, by reporting the state of the art for each aspect and highlighting the open issues and research opportunities. Then, we propose our own solutions. Specifically, we first consider Fog services as application containers and set up a small-scale FC testbed to perform a quantitative evaluation and comparison of the existing container migration techniques. The objective of this work is twofold: (i) clarify whether there exists a technique that performs the best under any condition or, otherwise, understand which technique is the most appropriate under which condition; (ii) better understand the inner workings of container migration. The second contribution is the proposal and validation of a platform, which we call Companion Fog Platform(CFP), that provides the necessary mechanisms to support device mobility in the Fog. Our CFP implements Fog services as containers and migrates them between Fog nodes according to the state-of-the-art container migration techniques. The third work described in this thesis is MobFogSim, a simulator that extends iFogSim to model device mobility and service migration in FC. After providing its design and implementation details, we validate the simulator. This is done by reproducing in MobFogSim the same conditions under which we evaluated the container migration techniques and by comparing the simulation results against those over the real testbed.

Companion fog computing: Migrating the fog service to support IoT device mobility / Carlo Puliafito. - (2020).

Companion fog computing: Migrating the fog service to support IoT device mobility

Carlo Puliafito
2020

Abstract

Fog Computing (FC) extends the Cloud towards the network edge. It provides end devices with access to resources and services that are located in topological proximity to them. This proximity enables key benefits (e.g., low latencies, reduced bandwidth consumption) that are not achievable when relying on Cloud-only solutions. FC is a horizontal paradigm in the sense that it is generic enough to be leveraged in a number of different application domains. However, its characteristics make it particularly suitable for the Internet of Things (IoT). After providing a survey on FC for the IoT, this thesis focuses on a specific research problem introduced with FC: the issue raised by device mobility in a FC environment. When a (IoT) device moves, the topological distance to the current Fog node (i.e., the Fog resource hosting the Fog service) may increase. Therefore, device mobility may impair the FC benefits, which are a result of Fog proximity. The objective is to support device mobility, namely to provide the FC benefits even in the presence of mobile devices. The most popular approach in literature to achieve this purpose is by migrating the Fog service across the Fog infrastructure, thus to let it be always close enough to the served mobile device. We refer to this paradigm as Companion Fog Computing (CFC), an extension of standard FC where the Fog service behaves as a "companion" of the mobile application. In this thesis, we first analyse the different aspects that characterise CFC, by reporting the state of the art for each aspect and highlighting the open issues and research opportunities. Then, we propose our own solutions. Specifically, we first consider Fog services as application containers and set up a small-scale FC testbed to perform a quantitative evaluation and comparison of the existing container migration techniques. The objective of this work is twofold: (i) clarify whether there exists a technique that performs the best under any condition or, otherwise, understand which technique is the most appropriate under which condition; (ii) better understand the inner workings of container migration. The second contribution is the proposal and validation of a platform, which we call Companion Fog Platform(CFP), that provides the necessary mechanisms to support device mobility in the Fog. Our CFP implements Fog services as containers and migrates them between Fog nodes according to the state-of-the-art container migration techniques. The third work described in this thesis is MobFogSim, a simulator that extends iFogSim to model device mobility and service migration in FC. After providing its design and implementation details, we validate the simulator. This is done by reproducing in MobFogSim the same conditions under which we evaluated the container migration techniques and by comparing the simulation results against those over the real testbed.
2020
Enzo Mingozzi, Giuseppe Anastasi
ITALIA
Goal 9: Industry, Innovation, and Infrastructure
Carlo Puliafito
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Utilizza questo identificatore per citare o creare un link a questa risorsa: https://hdl.handle.net/2158/1198302
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