Abstract
This letter investigates a multiuser mobile-edge computing (MEC) system with data compression technique to reduce the redundancy of sensed data, save the energy consumption and reduce the latency for wireless transmission. In this regard, the problem of minimizing the total energy consumption by jointly optimizing the transmission bandwidth allocation and data compression ratio is firstly considered under the constraints of latency and limited computation resource. Moreover, Lagragian and iterative-based algorithms are proposed to solve the non-convex optimization problem. Finally, simulation results are shown to verify the efficiency of the proposed algorithms and demonstrate that the application of data compression technique into MEC system can effectively reduce the energy consumption and latency.
Published Version
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call