On the online bin packing problem
Journal of the ACM (JACM)
Task Allocation for Distributed Multimedia Processing on Wirelessly Networked Handheld Devices
IPDPS '02 Proceedings of the 16th International Parallel and Distributed Processing Symposium
Distinctive Image Features from Scale-Invariant Keypoints
International Journal of Computer Vision
MapReduce: simplified data processing on large clusters
OSDI'04 Proceedings of the 6th conference on Symposium on Opearting Systems Design & Implementation - Volume 6
Dryad: distributed data-parallel programs from sequential building blocks
Proceedings of the 2nd ACM SIGOPS/EuroSys European Conference on Computer Systems 2007
AlfredO: an architecture for flexible interaction with electronic devices
Proceedings of the 9th ACM/IFIP/USENIX International Conference on Middleware
The Case for VM-Based Cloudlets in Mobile Computing
IEEE Pervasive Computing
Calling the cloud: enabling mobile phones as interfaces to cloud applications
Proceedings of the 10th ACM/IFIP/USENIX International Conference on Middleware
A virtual cloud computing provider for mobile devices
Proceedings of the 1st ACM Workshop on Mobile Cloud Computing & Services: Social Networks and Beyond
MAUI: making smartphones last longer with code offload
Proceedings of the 8th international conference on Mobile systems, applications, and services
Flow-Based Programming, 2nd Edition: A New Approach to Application Development
Flow-Based Programming, 2nd Edition: A New Approach to Application Development
CloneCloud: elastic execution between mobile device and cloud
Proceedings of the sixth conference on Computer systems
Mobile Networks and Applications
Odessa: enabling interactive perception applications on mobile devices
MobiSys '11 Proceedings of the 9th international conference on Mobile systems, applications, and services
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The contribution of cloud computing and mobile computing technologies lead to the newly emerging mobile cloud computing paradigm. Three major approaches have been proposed for mobile cloud applications: 1) extending the access to cloud services to mobile devices; 2) enabling mobile devices to work collaboratively as cloud resource providers; 3) augmenting the execution of mobile applications on portable devices using cloud resources. In this paper, we focus on the third approach in supporting mobile data stream applications. More specifically, we study how to optimize the computation partitioning of a data stream application between mobile and cloud to achieve maximum speed/throughput in processing the streaming data. To the best of our knowledge, it is the first work to study the partitioning problem for mobile data stream applications, where the optimization is placed on achieving high throughput of processing the streaming data rather than minimizing the makespan of executions as in other applications. We first propose a framework to provide runtime support for the dynamic computation partitioning and execution of the application. Different from existing works, the framework not only allows the dynamic partitioning for a single user but also supports the sharing of computation instances among multiple users in the cloud to achieve efficient utilization of the underlying cloud resources. Meanwhile, the framework has better scalability because it is designed on the elastic cloud fabrics. Based on the framework, we design a genetic algorithm for optimal computation partition. Both numerical evaluation and real world experiment have been performed, and the results show that the partitioned application can achieve at least two times better performance in terms of throughput than the application without partitioning.