TY - GEN
T1 - Towards power consumption-delay tradeoff by workload allocation in cloud-fog computing
AU - Deng, Ruilong
AU - Lu, Rongxing
AU - Lai, Chengzhe
AU - Luan, Tom H.
N1 - Publisher Copyright:
© 2015 IEEE.
PY - 2015/9/9
Y1 - 2015/9/9
N2 - Fog computing, characterized by extending cloud computing to the edge of the network, has recently received considerable attention. The fog is not a substitute but a powerful complement to the cloud. It is worthy of studying the interplay and cooperation between the edge (fog) and the core (cloud). To address this issue, we study the tradeoff between power consumption and delay in a cloud-fog computing system. Specifically, we first mathematically formulate the workload allocation problem. After that, we develop an approximate solution to decompose the primal problem into three subproblems of corresponding subsystems, which can be independently solved. Finally, based on extensive simulations and numerical results, we show that by sacrificing modest computation resources to save communication bandwidth and reduce transmission latency, fog computing can significantly improve the performance of cloud computing.
AB - Fog computing, characterized by extending cloud computing to the edge of the network, has recently received considerable attention. The fog is not a substitute but a powerful complement to the cloud. It is worthy of studying the interplay and cooperation between the edge (fog) and the core (cloud). To address this issue, we study the tradeoff between power consumption and delay in a cloud-fog computing system. Specifically, we first mathematically formulate the workload allocation problem. After that, we develop an approximate solution to decompose the primal problem into three subproblems of corresponding subsystems, which can be independently solved. Finally, based on extensive simulations and numerical results, we show that by sacrificing modest computation resources to save communication bandwidth and reduce transmission latency, fog computing can significantly improve the performance of cloud computing.
UR - https://www.scopus.com/pages/publications/84953720896
U2 - 10.1109/ICC.2015.7248934
DO - 10.1109/ICC.2015.7248934
M3 - 会议稿件
AN - SCOPUS:84953720896
T3 - IEEE International Conference on Communications
SP - 3909
EP - 3914
BT - 2015 IEEE International Conference on Communications, ICC 2015
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - IEEE International Conference on Communications, ICC 2015
Y2 - 8 June 2015 through 12 June 2015
ER -