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1. 南京邮电大学物联网学院,江苏 南京 210003
2. 南京邮电大学自动化学院、人工智能学院,江苏 南京 210003
3. 南京邮电大学计算机学院,江苏 南京 210003
[ "亓晋(1983– ),男,山东莱芜人,博士,南京邮电大学副教授,主要研究方向为人工智能在工业互联网、能源互联网、智慧供应链和智慧健康等领域的关键技术与应用" ]
[ "孙海蓉(1994– ),女,江苏泰州人,南京邮电大学硕士生,主要研究方向为边缘计算在工业互联网和智能制造等领域的应用" ]
[ "巩锟(1999– ),女,山东莱芜人,南京邮电大学硕士生,主要研究方向为边缘计算、机器学习在工业互联网领域的应用" ]
[ "许斌(1981– ),男,江苏张家港人,博士,南京邮电大学副教授,主要研究方向为智能计算技术及其在工业互联网、能源互联网、复杂网络、智慧健康等领域的关键技术与应用" ]
[ "张顺颐(1944– ),男,江苏南京人,南京邮电大学教授,主要研究方向为移动互联网、网络管理与监控关键技术与产业应用" ]
[ "孙雁飞(1976– ),男,山东莱芜人,博士,南京邮电大学研究员,主要研究方向为人工智能在工业互联网、能源互联网、智慧供应链和智慧健康等领域的关键技术与应用" ]
网络出版日期:2020-07,
纸质出版日期:2020-07-25
移动端阅览
亓晋, 孙海蓉, 巩锟, 等. 移动边缘计算中基于信誉值的智能计算卸载模型研究[J]. 通信学报, 2020,41(7):141-151.
Jin QI, Hairong SUN, Kun GONG, et al. Research on intelligent computing offloading model based on reputation value in mobile edge computing[J]. Journal on communications, 2020, 41(7): 141-151.
亓晋, 孙海蓉, 巩锟, 等. 移动边缘计算中基于信誉值的智能计算卸载模型研究[J]. 通信学报, 2020,41(7):141-151. DOI: 10.11959/j.issn.1000-436x.2020105.
Jin QI, Hairong SUN, Kun GONG, et al. Research on intelligent computing offloading model based on reputation value in mobile edge computing[J]. Journal on communications, 2020, 41(7): 141-151. DOI: 10.11959/j.issn.1000-436x.2020105.
针对移动边缘计算环境下,爆炸式增长的物联网智能移动终端处理计算密集型和时延敏感型新兴移动应用时,面临的高时延、高能耗和低可靠性等问题,提出综合考虑时延和能耗的卸载决策模型和基于信誉值的计算资源博弈分配模型,并分别利用改进粒子群算法和拉格朗日乘数法求解。仿真结果表明,所提方法可满足新兴智能应用对于低时延、低能耗和高可靠性的服务需求,可有效实现计算卸载资源的整体优化配置。
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.
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