TY - GEN
T1 - Collaborative mobile-to-mobile computation offloading
AU - Mtibaa, Abderrahmen
AU - Snober, Mohammad Abu
AU - Carelli, Antonio
AU - Beraldi, Roberto
AU - Alnuweiri, Hussein
N1 - Publisher Copyright:
© 2014 ICST.
PY - 2015/1/19
Y1 - 2015/1/19
N2 - It is common practice for mobile devices to offload computationally heavy tasks off to a cloud, which has greater computational resources. In this paper, we consider an environment in which computational offloading is made among collaborative mobile devices.We call such an environment a mobile device cloud (MDC). We highlight the gain in computation time and energy consumption that can be achieved by offloading tasks with given characteristics to nearby devices inside a mobile device cloud. We adopt an experimental approach to measure power consumption in mobile to mobile opportunistic offloading using MDCs. Then, we adopt a data driven approach to evaluate and assess various offloading algorithms in MDCs. We believe that MDCs are not replacing the Cloud, however they present an offloading opportunity for a set of tasks with given characteristics or simply a solution when the cloud is unacceptable or costly. The promise of this approach shown by evaluating these algorithms using real datasets that include contact traces and social information of mobile devices in a conference setting.
AB - It is common practice for mobile devices to offload computationally heavy tasks off to a cloud, which has greater computational resources. In this paper, we consider an environment in which computational offloading is made among collaborative mobile devices.We call such an environment a mobile device cloud (MDC). We highlight the gain in computation time and energy consumption that can be achieved by offloading tasks with given characteristics to nearby devices inside a mobile device cloud. We adopt an experimental approach to measure power consumption in mobile to mobile opportunistic offloading using MDCs. Then, we adopt a data driven approach to evaluate and assess various offloading algorithms in MDCs. We believe that MDCs are not replacing the Cloud, however they present an offloading opportunity for a set of tasks with given characteristics or simply a solution when the cloud is unacceptable or costly. The promise of this approach shown by evaluating these algorithms using real datasets that include contact traces and social information of mobile devices in a conference setting.
UR - http://www.scopus.com/inward/record.url?scp=84923039598&partnerID=8YFLogxK
U2 - 10.4108/icst.collaboratecom.2014.257610
DO - 10.4108/icst.collaboratecom.2014.257610
M3 - Conference contribution
AN - SCOPUS:84923039598
T3 - CollaborateCom 2014 - Proceedings of the 10th IEEE International Conference on Collaborative Computing: Networking, Applications and Worksharing
SP - 460
EP - 465
BT - CollaborateCom 2014 - Proceedings of the 10th IEEE International Conference on Collaborative Computing
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 10th IEEE/EAI International Conference on Collaborative Computing, CollaborateCom 2014
Y2 - 22 October 2014 through 25 October 2014
ER -