Journal of the ACM (JACM)
Computation offloading to save energy on handheld devices: a partition scheme
CASES '01 Proceedings of the 2001 international conference on Compilers, architecture, and synthesis for embedded systems
Towards a Distributed Platform for Resource-Constrained Devices
ICDCS '02 Proceedings of the 22 nd International Conference on Distributed Computing Systems (ICDCS'02)
Journal of Network and Computer Applications
Partitioning of Java Applications to Support Dynamic Updates
APSEC '04 Proceedings of the 11th Asia-Pacific Software Engineering Conference
A Compiler and Runtime Infrastructure for Automatic Program Distribution
IPDPS '05 Proceedings of the 19th IEEE International Parallel and Distributed Processing Symposium (IPDPS'05) - Papers - Volume 01
An effective offloading middleware for pervasive services on mobile devices
Pervasive and Mobile Computing
Adaptive computation offloading for energy conservation on battery-powered systems
ICPADS '07 Proceedings of the 13th International Conference on Parallel and Distributed Systems - Volume 01
ICPADS '08 Proceedings of the 2008 14th IEEE International Conference on Parallel and Distributed Systems
eyeDentify: Multimedia Cyber Foraging from a Smartphone
ISM '09 Proceedings of the 2009 11th IEEE International Symposium on Multimedia
Using Bytecode Instruction Counting as Portable CPU Consumption Metric
Electronic Notes in Theoretical Computer Science (ENTCS)
A compilation framework for power and energy management on mobile computers
LCPC'01 Proceedings of the 14th international conference on Languages and compilers for parallel computing
Users and batteries: interactions and adaptive energy management in mobile systems
UbiComp '07 Proceedings of the 9th international conference on Ubiquitous computing
Dynamically partitioning applications between weak devices and clouds
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
Augmented smartphone applications through clone cloud execution
HotOS'09 Proceedings of the 12th conference on Hot topics in operating systems
CloneCloud: elastic execution between mobile device and cloud
Proceedings of the sixth conference on Computer systems
Review: Task assignment policies in distributed server systems: A survey
Journal of Network and Computer Applications
Techniques for Fine-Grained, Multi-site Computation Offloading
CCGRID '11 Proceedings of the 2011 11th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing
MobiCom '11 Proceedings of the 17th annual international conference on Mobile computing and networking
Identity-based online/offline signcryption for low power devices
Journal of Network and Computer Applications
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Mobile applications are becoming increasingly ubiquitous and provide ever richer functionality on mobile devices, while such applications drain increasingly more battery power of mobile devices. Offloading some parts of the application running on mobile devices onto remote servers/clouds is a promising approach to extend the battery life of mobile devices. However, as data transmission of offloading causes delay and energy costs for mobile devices, it is necessary to carefully design application partitioning/offloading schemes to weigh the benefits against the transmission delay and costs. Due to bandwidth fluctuations in the wireless environment, static partitionings in previous work are unsuitable for mobile platforms with a fixed bandwidth assumption, while dynamic partitionings result in high overhead of continuous partitioning for mobile devices. Therefore, we propose a novel partitioning scheme taking the bandwidth as a variable to improve static partitioning and avoid high costs of dynamic partitioning. Firstly, we construct application Object Relation Graphs (ORGs) by combining static analysis and dynamic profiling to propose partitioning optimization models. Then based on our novel execution-time and energy optimization partitioning models, we propose the Branch-and-Bound based Application Partitioning (BBAP) algorithm and Min-Cut based Greedy Application Partitioning (MCGAP) algorithm. BBAP is suited to finding the optimal partitioning solutions for small applications, while MCGAP is applicable to quickly obtaining suboptimal solutions for large-scale applications. Experimental results demonstrate that both algorithms can adapt to bandwidth fluctuations well, and significantly reduce application execution time and energy consumption by optimally distributing components between mobile devices and servers.