TY - GEN
T1 - When D2D meets cloud
T2 - 2017 IEEE International Conference on Communications, ICC 2017
AU - Chen, Xu
AU - Zhang, Junshan
N1 - Funding Information:
ACKNOWLEDGEMENT This research is supported by the start-up fund of Sun Yat-sen University, Key Laboratory of Machine Intelligence and Advanced Computing, Ministry of Education of China, NSF Grant CNS-1457278 and DoD Grant DTRA-13-1-0029.
Funding Information:
This research is supported by the start-up fund of Sun Yatsen University, Key Laboratory of Machine Intelligence and Advanced Computing, Ministry of Education of China, NSF Grant CNS-1457278 and DoD Grant DTRA-13-1-0029.
Publisher Copyright:
© 2017 IEEE.
PY - 2017/7/28
Y1 - 2017/7/28
N2 - In this paper we propose HyFog, a novel hybrid task offloading framework in fog computing, where device users have the flexibility of choosing among multiple options for task executions, including local mobile execution, Device-to-Device (D2D) offloaded execution, and Cloud offloaded execution. We further develop a novel three-layer graph matching algorithm for efficient hybrid task offloading among the devices. Specifically, we first construct a three-layer graph to capture the choice space enabled by these three execution approaches, and then the problem of minimizing the total task execution cost is recast as a minimum weight matching problem over the constructed three-layer graph, which can be efficiently solved using the Edmonds's Blossom algorithm. Numerical results demonstrate that the proposed three-layer graph matching solution can achieve superior performance, with more than 50% cost reduction over the case of local task executions by all the devices.
AB - In this paper we propose HyFog, a novel hybrid task offloading framework in fog computing, where device users have the flexibility of choosing among multiple options for task executions, including local mobile execution, Device-to-Device (D2D) offloaded execution, and Cloud offloaded execution. We further develop a novel three-layer graph matching algorithm for efficient hybrid task offloading among the devices. Specifically, we first construct a three-layer graph to capture the choice space enabled by these three execution approaches, and then the problem of minimizing the total task execution cost is recast as a minimum weight matching problem over the constructed three-layer graph, which can be efficiently solved using the Edmonds's Blossom algorithm. Numerical results demonstrate that the proposed three-layer graph matching solution can achieve superior performance, with more than 50% cost reduction over the case of local task executions by all the devices.
UR - http://www.scopus.com/inward/record.url?scp=85028333097&partnerID=8YFLogxK
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U2 - 10.1109/ICC.2017.7996590
DO - 10.1109/ICC.2017.7996590
M3 - Conference contribution
AN - SCOPUS:85028333097
T3 - IEEE International Conference on Communications
BT - 2017 IEEE International Conference on Communications, ICC 2017
A2 - Debbah, Merouane
A2 - Gesbert, David
A2 - Mellouk, Abdelhamid
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 21 May 2017 through 25 May 2017
ER -