Computer Science

Computer Science ›› 2023, Vol. 50 ›› Issue (6A): 211200229-5.doi: 10.11896/jsjkx.211200229

• Network & Communication • Previous Articles     Next Articles

MEC Offloading Model Based on Linear Programming Relaxation

LEI Xuemei1, LIU Li2, WANG Qian2   

  1. 1 Office of Information Construction and Management,University of Science and Technology Beijing,Beijing 100083,China;
    2 School of Automation and Engineering,University of Science and Technology Beijing,Beijing 100083,China
  • Online:2023-06-10 Published:2023-06-12
  • About author:LEI Xuemei,born in 1972,Ph.D,senior engineer.Her main research interests include mobile computing,network optimization and data analysis. LIU li,born in 1968,Ph.D,professor.Her main research interests include mobile computing and multi-objective optimization.
  • Supported by:
    National Natural Science Foundation of China(12071025)and Scientific and Technological Innovation Foundation of Foshan Municipal People’s Government(BK20AE004).

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Abstract: In the mobile edge computing(MEC),the local device can offload tasks to the edge node near the network for computation processing,thereby reducing the delay,power consumption and overload of the client,also the computing loading core network.For the complex MEC environment of multi-type edge nodes,a three-stage computing offloading decision is modeled based on linear programming relaxation,that is CART-CRITIC-LR(CCLR) algorithm.First,the classification and regression decision tree algorithm(CART) is used to screen out the locally executed calculation tasks.Secondly,the multi-attribute decision-making algorithm(CRITIC) is used to determine the weight of the three performance indicators respectively.Then the calculation offloa-ding problem is modeled as a linear programming relaxation(LR ) to optimize the equilibrium solutions among the total delay,total energy consumption and total cost.Each offloading strategy is analyzed by comprehensively comparing the energy consumption,cost,delay.experimental results show that the CCLR algorithm achieves the shortest total delay while ensuring the multi-objective global optimization,which illustrates the effectiveness and applicability of the algorithm.

Key words: Mobile edge computing, Task offloading, Multi-attribute decision, Classification and regression tree, Linear programming

CLC Number: 

  • TP393
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