TY - JOUR
T1 - Optimal Code Partitioning over Time and Hierarchical Cloudlets
AU - Kiani, Abbas
AU - Ansari, Nirwan
N1 - Funding Information:
Manuscript received September 6, 2017; revised September 21, 2017; accepted October 17, 2017. Date of publication October 20, 2017; date of current version January 8, 2018. This work was supported in part by NSF under grant no. CNS-1647170. The associate editor coordinating the review of this paper and approving it for publication was D. W. K. Ng. (Corresponding author: Abbas Kiani.) The authors are with the Advanced Networking Laboratory, Department of Electrical and Computer Engineering, New Jersey Institute of Technology, Newark, NJ 07102 USA (e-mail: abbas.kiani@njit.edu; nirwan.ansari@njit.edu). Digital Object Identifier 10.1109/LCOMM.2017.2764904
Publisher Copyright:
© 1997-2012 IEEE.
PY - 2018/1
Y1 - 2018/1
N2 - This letter proposes a task scheduling scheme designed for code partitioning over time and the hierarchical cloudlets in a mobile edge network. To this end, we define the so called energy-time cost parameters to optimally schedule tasks over time and hierarchical cloudlet locations. Accordingly, we investigate two different optimization scenarios. In particular, the first scenario aims at finding the optimal task scheduling for given radio parameters. In the second scenario, we carry out the optimization of both the task scheduling and the mobile device's transmission power. More importantly, we show that by adopting the proposed code partitioning scheme in this letter, the transmission power optimization problem becomes a disjoint problem from the task scheduling problem.
AB - This letter proposes a task scheduling scheme designed for code partitioning over time and the hierarchical cloudlets in a mobile edge network. To this end, we define the so called energy-time cost parameters to optimally schedule tasks over time and hierarchical cloudlet locations. Accordingly, we investigate two different optimization scenarios. In particular, the first scenario aims at finding the optimal task scheduling for given radio parameters. In the second scenario, we carry out the optimization of both the task scheduling and the mobile device's transmission power. More importantly, we show that by adopting the proposed code partitioning scheme in this letter, the transmission power optimization problem becomes a disjoint problem from the task scheduling problem.
KW - Hierarchical mobile edge computing
KW - computation offloading
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U2 - 10.1109/LCOMM.2017.2764904
DO - 10.1109/LCOMM.2017.2764904
M3 - Article
AN - SCOPUS:85040699293
SN - 1089-7798
VL - 22
SP - 181
EP - 184
JO - IEEE Communications Letters
JF - IEEE Communications Letters
IS - 1
M1 - 8076894
ER -