@article{Diamantoulakis2021,

title = {Optimal Design and Orchestration of Mobile Edge Computing with Energy Awareness},

author = {P. Diamantoulakis and P. Bouzinis and P. Sarigiannidis and Z. Ding and G. Karagiannidis},

url = {https://www.researchgate.net/publication/352908814_Optimal_Design_and_Orchestration_of_Mobile_Edge_Computing_with_Energy_Awareness},

doi = {10.1109/TSUSC.2021.3103476},

year  = {2021},

date = {2021-08-13},

journal = {IEEE Transactions on Sustainable Computing },

volume = {1},

number = {1},

abstract = {In this work, we propose the use of an advanced multiple access technique and its joint design with adaptive task offloading, in order to reduce delay and energy consumption. More specifically, the use of generalized hybrid orthogonal/non-orthogonal multiple access (OMA/NOMA) for MEC is introduced, which is theoretically superior to other alternatives from the existing literature. In more detail, the proposed scheme is based on the joint utilization of dynamic user scheduling among OMA/NOMA phases and variable decoding order during the successive interference cancellation in NOMA phase. Also, the systems orchestration is optimized for both full and partial task offloading. Specifically, in full offloading scenario, the user scheduling, time allocation, and power control are jointly optimized. Regarding partial offloading, the computational resources, i.e., the clock speed of the local processors and the number of offloaded bits, are jointly optimized with the communication resources, taking into account the constraint of the energy that is consumed for both local processing and task offloading, which is particularly challenging due to the non-convex nature of the corresponding optimization problem. All optimization problems are efficiently solved by either using closed-form solutions that provide useful insights or low-complexity algorithms.},

keywords = {energy consumption, mobile edge computing, multiple access, task offloading},

pubstate = {published},

tppubtype = {article}

}