Distributed Computing Systems Group

Mobile-Cloud Integration


Mobile devices, such as smartphones and tablets, are becoming the universal interface to online services and applications. However, such devices have limited computational power, storage capacity, and battery life, which reduces their ability to execute rich, resource-intensive applications. In this project, we are exploring the use of the cloud as a mobile application outsourcing platform, i.e., using cloud resources to execute the resource- and data-intensive components of mobile applications. Our research is exploring different ways to leverage the cloud for scalability, elasticity, and multi-user code/data sharing across a variety of applications.

We are specifically investigating the role of user profiling strategies in cloud-based mobile application optimization. Rich sources of user data allow us to employ personalized optimization strategies. Moreover, the cloud is especially suited for this task because it offers abundant storage capacity to maintain user data as well as the computational power to process this data.


Personalized Content Aggregation

Many mobile applications access and process remotely stored content on behalf of the user. Utilizing such content introduces latency that is perceived by the user as they work with a mobile application. Furthermore, bandwidth and energy costs are incurred when remote resources are accessed. We are developing techniques to address these issues. In particular, we are interested in aggregating the tasks of different users and forecasting a user's future needs in order to carry out the required computations ahead of time.

Real-Time Collaborative Editing

We are also looking at mobile applications that involve concurrent document editing by multiple users. Such applications must send updates to their users in order to maintain consistency. We are working on optimizations to reduce the energy and bandwidth cost of these updates. These optimizations include batching updates as well as identifying and prioritizing the updates that are most relevant to a particular user.

Recent Poster

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Data-Driven Optimization thumbnail

Exploiting User Interest in Data-Driven Cloud-based Mobile Optimization John Kolb, William Myott, Thao Nguyen, Abhishek Chandra, and Jon Weissman. To appear in the Proceedings of the Second IEEE International Conference on Mobile Cloud Computing, Services, and Engineering. Oxford, UK. .

Sharing-Aware Paper thumbnail

Sharing-aware Cloud-based Mobile Outsourcing. Chonglei Mei, Daniel Taylor, Chenyu Wang, Abhishek Chandra, and Jon Weissman. In the Proceedings of the IEEE Fifth International Conference on Cloud Computing. Honolulu, HI. .

TR11-029 thumbnail

Mobilizing the Cloud: Enabling Multi-User Mobile Outsourcing in the Cloud. Chonglei Mei, Daniel Taylor, Chenyu Wang, Abhishek Chandra, and Jon Weissman. Technical Report 11-029. Department of Computer Science and Engineering, University of Minnesota. .