Abstract
This paper addresses the energy minimization problem
in Device-to-Device (D2D) assisted Mobile Edge Computing
(MEC) networks under the latency constraint of each individual
task and the computing resource constraint of each computing
entity. The energy minimization problem is formed as a twostage
optimization problem. Specifically, in the first stage, an
initial feasibility problem is formed to maximize the number
of executed tasks and the global energy minimization problem
is tackled in the second stage while maintaining the maximum
number of executed tasks. Both of the optimization problems in
two stages are NP-hard, therefore a low-complexity algorithm is
developed for the initial feasibility problem with a supplementary
algorithm further proposed for energy minimization. Simulation
results demonstrate the near-optimal performance of the proposed
algorithms and the fact that with the assistance of D2D
communication, the number of executed tasks is greatly increased
and the energy consumption per executed task is significantly
reduced in MEC networks, especially in dense user scenario.
Original language | English |
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Title of host publication | Not Known |
Pages | 1-6 |
Publication status | Accepted/In press - 4 Feb 2019 |
Keywords
- Mobile edge computing
- device-to-device communication
- energy minimization
- task offloading