Recent years have witnessed an increasing number of mobile devices such as smartphones and tablets characterized by low computing and storage capabilities. Meanwhile, there is an explosive growth of applications on mobile devices that require high computing and storage capabilities. These challenges lead to the introduction of cloud computing empowering mobile devices with remote computing and storage resources. However, cloud computing is centrally designed, thus encountering noticeable issues such as high communication latency and potential vulnerability. To tackle these problems posed by central cloud computing, Mobile Edge Cloud (MEC) has been recently introduced to bring the computing and storage resources in proximity to mobile devices, such as at base stations or shopping centers. Therefore, MEC has become a key enabling technology for various emerging use cases such as autonomous driving and tactile internet.
Despite such a potential benefit, the design of MEC is challenging for the deployment of applications. First, as MEC aims to bring computation and storage resources closer to mobile devices, MEC servers that provide those resources become incredibly diverse in the network. Moreover, MEC servers typically have a small footprint design to flexibly place at various locations, thus providing limited resources. The challenge is to deploy applications in a cost-efficient manner. Second, applications have stringent requirements such as high mobility or low latency. The challenge is to deploy applications in MEC to satisfy their needs.
Considering the above challenges, this thesis aims to study the orchestration of MEC applications. In particular, for computation offloading, we propose offloading schemes for immersive applications in MEC such as Augmented Reality or Virtual Reality (AR/VR) by employing application characteristics. For resource optimization, since many MEC applications such as gaming and streaming applications require the support of network functions such as encoder and decoder, we first present placement schemes that allow efficiently sharing network functions between multiple MEC applications. We then introduce the design of the proposed MANO framework in MEC, advocating the joint orchestration between MEC applications and network functions. For mobility support, low latency applications for use cases such as autonomous driving have to seamlessly migrate from one MEC server to another MEC server following the mobility of mobile device, to guarantee low latency communication. Traditional migration approaches based on virtual machine (VM) or container migration attempt to suspend the application at one MEC server and then recover it at another MEC server. These approaches require the transfer of the entire VM or container state and consequently lead to service interruption due to high migration time. Therefore, we advocate migration techniques that takes advantage of application states.
| Identifer | oai:union.ndltd.org:DRESDEN/oai:qucosa:de:qucosa:84173 |
| Date | 21 March 2023 |
| Creators | Doan, Tung |
| Contributors | Fitzek, Frank H. P., Granelli, Fabrizio, Lucani, Daniel, Technische Universität Dresden |
| Source Sets | Hochschulschriftenserver (HSSS) der SLUB Dresden |
| Language | English |
| Detected Language | English |
| Type | info:eu-repo/semantics/publishedVersion, doc-type:doctoralThesis, info:eu-repo/semantics/doctoralThesis, doc-type:Text |
| Rights | info:eu-repo/semantics/openAccess |
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