Description: Cloud computing provides on-demand access to services and data that are kept on infrastructure accessible through the internet, rather than on individual devices. By having computation and data handling carried out remotely, cloud computing offers a way to circumvent the resource limitations on the mobile phone (less memory, less compute power, and battery capacity limits).
In mobile cloud computing, the mobile device becomes an interface to cloud computing applications. where the application is run as a service in the cloud and the output is sent to the mobile phone. A key challenge when running the application remotely is how to deal with the network availability, high latencies, intermittency and large data transfer costs.
In this PhD project, the goal is to investigate how applications can be modeled, partitioned and deployed partially on the mobile phone and partially in the cloud so that various resource and quality of service constraints are automatically considered. Finding the best deployment and execution configuration becomes a multi-objective optimization problem considering both quality of service and quality of experience. Furthermore, the best configuration may evolve when the current situation changes.
The goal of this research is to investigate a middleware approach that leverages context-awareness to address this dynamic optimization problem effectively.
Applicants should have a MSc in computer science or similar and should be highly motivated to work in the field of software engineering and be familiar with middleware for distributed systems. Basic knowledge of cloud computing principles is strongly encouraged.
Key words: middleware, mobile computing, cloud computing, distributed systems
Latest application date: 2011-10-03
Financing: available
Type of Position: scholarship
Duration of the Project : 4 years
Research group: Department of Computer Science
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