移动边缘计算中基于信誉值的智能计算卸载模型研究

doi:10.11959/j.issn.1000-436x.2020105

Abstract

Abstract:

Aiming at the problem of high-latency,high-energy-consumption,and low-reliability mobile caused by computing-intensive and delay-sensitive emerging mobile applications in the explosive growth of IoT smart mobile terminals in the mobile edge computing environment,an offload decision-making model where delay and energy consumption were comprehensively included,and a computing resource game allocation model based on reputation that took into account was proposed,then improved particle swarm algorithm and the method of Lagrange multipliers were used respectively to solve models.Simulation results show that the proposed method can meet the service requirements of emerging intelligent applications for low latency,low energy consumption and high reliability,and effectively implement the overall optimized allocation of computing offload resources.

Key words: mobile edge computing, reputation value, game allocation, offloading decision, resource allocation

CLC Number:

TP393

Jin QI,Hairong SUN,Kun GONG,Bin XU,Shunyi ZHANG,Yanfei SUN. Research on intelligent computing offloading model based on reputation value in mobile edge computing[J]. Journal on Communications, 2020, 41(7): 141-151.

Figures/Tables 9

实验参数	数值
移动智能终端自身计算能力L_i/GHz	0.5,1.0]
当前信誉值R_i	0,10]
时间权衡因子 $φ_{i}^{T}$	0,1]
MEC能力F/GHz	10
功率p/mW	100
终端与基站之间的增益g_i,s	10^-6
背景噪声功率N/dBm	-100
i向宏基站发送上行计算请求的实际带宽/kHz	15
计算任务数据最大值 $D_{i}^{\max} / K B$	5 000
MEC单个CPU能耗δ/W	5
任务所需的CPU周期总数C /兆周	1 000

References 26

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改进的PSO算法	卸载决策问题
空间维度	数量
种群	不同卸载决策的集合
粒子位置	不同的卸载决策
适应度值	系统总消耗

Research on intelligent computing offloading model based on reputation value in mobile edge computing

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