TY - GEN
T1 - Collaborative Computation Offloading in Heterogeneous Asynchronous Cloud Environment
AU - Ma, Lei
AU - Yu, Bing
AU - Sato, Hiroyuki
AU - Wang, Yadong
PY - 2017/9/7
Y1 - 2017/9/7
N2 - Computation offloading is a key technique to enhance the performance and interactivity of mobile application through migrating the computation-intensive tasks to the cloud. However, efficient offloading is challenging in practice in that a mobile application often consists of computation tasks that have dependency with execution order constraints as well as parallel tasks that can be executed non-deterministically. In addition, each mobile device executes its application as a separate process, and performs asynchronous communication with cloud environment with heterogeneous computing and storage resource that are shared among mobile devices. In this paper, we propose a collaborative asynchronous computation offloading framework to improve the interactivity and execution efficiency of mobile applications. Initially, each mobile application calculates its local offloading plan. At runtime, it follows the offloading plan for task execution and requests the offloading computation from the cloud system. Upon receiving the request, cloud system performs dynamic adjustment of the offloading request according to the cloud runtime status. We implement our proposed offloading framework. The evaluation on 11 real-world mobile applications demonstrates its effectiveness.
AB - Computation offloading is a key technique to enhance the performance and interactivity of mobile application through migrating the computation-intensive tasks to the cloud. However, efficient offloading is challenging in practice in that a mobile application often consists of computation tasks that have dependency with execution order constraints as well as parallel tasks that can be executed non-deterministically. In addition, each mobile device executes its application as a separate process, and performs asynchronous communication with cloud environment with heterogeneous computing and storage resource that are shared among mobile devices. In this paper, we propose a collaborative asynchronous computation offloading framework to improve the interactivity and execution efficiency of mobile applications. Initially, each mobile application calculates its local offloading plan. At runtime, it follows the offloading plan for task execution and requests the offloading computation from the cloud system. Upon receiving the request, cloud system performs dynamic adjustment of the offloading request according to the cloud runtime status. We implement our proposed offloading framework. The evaluation on 11 real-world mobile applications demonstrates its effectiveness.
UR - http://www.scopus.com/inward/record.url?scp=85031897359&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85031897359&partnerID=8YFLogxK
U2 - 10.1109/COMPSAC.2017.88
DO - 10.1109/COMPSAC.2017.88
M3 - Conference contribution
AN - SCOPUS:85031897359
T3 - Proceedings - International Computer Software and Applications Conference
SP - 929
EP - 934
BT - Proceedings - 2017 IEEE 41st Annual Computer Software and Applications Conference, COMPSAC 2017
A2 - Demartini, Claudio
A2 - Conte, Thomas
A2 - Nakamura, Motonori
A2 - Lung, Chung-Horng
A2 - Zhang, Zhiyong
A2 - Hasan, Kamrul
A2 - Reisman, Sorel
A2 - Liu, Ling
A2 - Claycomb, William
A2 - Takakura, Hiroki
A2 - Yang, Ji-Jiang
A2 - Tovar, Edmundo
A2 - Cimato, Stelvio
A2 - Ahamed, Sheikh Iqbal
A2 - Akiyama, Toyokazu
PB - IEEE Computer Society
T2 - 41st IEEE Annual Computer Software and Applications Conference, COMPSAC 2017
Y2 - 4 July 2017 through 8 July 2017
ER -