TY - GEN
T1 - Joint uplink/downlink and offloading optimization for mobile cloud computing with limited backhaul
AU - Al-Shuwaili, Ali Najdi
AU - Bagheri, Alireza
AU - Simeone, Osvaldo
N1 - Publisher Copyright:
© 2016 IEEE.
PY - 2016/4/26
Y1 - 2016/4/26
N2 - Mobile cloud computing enables the offloading of computationally heavy applications, such as for gaming, object recognition or video processing, from mobile users (MUs) to a cloud server connected to wireless access points. The optimization of the operation of a mobile cloud computing system amounts to the problem of minimizing the energy required for offloading across all MUs under latency constraints at the application layer. In a scenario with multiple MUs transmitting over a shared wireless medium across multiple cells, this problem requires the management of interference for both the uplink, through which MUs offload the data needed for computation in the cloud, and for the downlink, through which the outcome of the cloud computation are fed back to the MUs, as well as the allocation of backhaul resources for communication between wireless edge and cloud and of computing resources at the cloud. In this paper, this problem is formulated for general multi-antenna, or MIMO, channels, and tackled by means of successive convex approximation methods. The numerical results illustrate the advantages of a joint allocation of computing and communication resources.
AB - Mobile cloud computing enables the offloading of computationally heavy applications, such as for gaming, object recognition or video processing, from mobile users (MUs) to a cloud server connected to wireless access points. The optimization of the operation of a mobile cloud computing system amounts to the problem of minimizing the energy required for offloading across all MUs under latency constraints at the application layer. In a scenario with multiple MUs transmitting over a shared wireless medium across multiple cells, this problem requires the management of interference for both the uplink, through which MUs offload the data needed for computation in the cloud, and for the downlink, through which the outcome of the cloud computation are fed back to the MUs, as well as the allocation of backhaul resources for communication between wireless edge and cloud and of computing resources at the cloud. In this paper, this problem is formulated for general multi-antenna, or MIMO, channels, and tackled by means of successive convex approximation methods. The numerical results illustrate the advantages of a joint allocation of computing and communication resources.
KW - 5G
KW - Application offloading
KW - Backhaul
KW - Mobile cloud computing
KW - Successive convex approximation
UR - http://www.scopus.com/inward/record.url?scp=84992316466&partnerID=8YFLogxK
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U2 - 10.1109/CISS.2016.7460540
DO - 10.1109/CISS.2016.7460540
M3 - Conference contribution
AN - SCOPUS:84992316466
T3 - 2016 50th Annual Conference on Information Systems and Sciences, CISS 2016
SP - 424
EP - 429
BT - 2016 50th Annual Conference on Information Systems and Sciences, CISS 2016
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 50th Annual Conference on Information Systems and Sciences, CISS 2016
Y2 - 16 March 2016 through 18 March 2016
ER -