通信学报 ›› 2020, Vol. 41 ›› Issue (1): 1-14.doi: 10.11959/j.issn.1000-436x.2020012
• 学术论文 • 下一篇
郭辉,芮兰兰,高志鹏
修回日期:
2019-09-30
出版日期:
2020-01-25
发布日期:
2020-02-11
作者简介:
郭辉(1992- ),女,河北保定人,北京邮电大学博士生,主要研究方向为移动网络、边缘计算等|芮兰兰(1979- ),女,安徽潜山人,博士,北京邮电大学副教授、博士生导师,主要研究方向为网络管理、移动网络、边缘计算等|高志鹏(1980- ),男,山东滨州人,博士,北京邮电大学教授、博士生导师,主要研究方向为云计算、网络服务与管理、边缘计算等
基金资助:
Hui GUO,Lanlan RUI,Zhipeng GAO
Revised:
2019-09-30
Online:
2020-01-25
Published:
2020-02-11
Supported by:
摘要:
为解决车辆移动及边缘服务器有限服务范围造成的服务中断问题,为车辆边缘网络提出一种基于多参数马尔可夫决策过程的动态服务迁移算法。通过构造包含时延、带宽、服务器处理能力及车辆运动信息的多参数MDP 收益函数,弥补了单纯基于距离进行服务迁移方案的不足;不再使用单一迁移目标服务器,结合车辆运动及时延限制构造候选服务器集合,基于Bellman方程表示的长期收益值进行迁移决策;利用历史数据进行权重计算及数据更新,提高了算法对动态环境的适应能力。仿真结果表明,所提算法降低了服务时延、数据分组丢失率及服务迁移次数。
中图分类号:
郭辉,芮兰兰,高志鹏. 车辆边缘网络中基于多参数MDP模型的动态服务迁移策略[J]. 通信学报, 2020, 41(1): 1-14.
Hui GUO,Lanlan RUI,Zhipeng GAO. Dynamic service migration strategy based on MDP model with multiple parameter in vehicular edge network[J]. Journal on Communications, 2020, 41(1): 1-14.
表1
已有方案对比"
方案 | 设计 | 优点 | 缺点 |
文献[ | 利用基于跳数的 MDP 状态函数对蜂窝网络中的用户运动进行聚类,迭代求解 | 提高了对用户行为预测的准确度 | 可扩展性低 |
文献[ | 利用“常数+指数”的形式具体化MDP开销函数,改进策略迭代以获得更优策略 | 实现了MDP函数具体化 | 计算复杂度高、动态适应性弱 |
文献[ | 利用Lyapunov优化及MDP的解耦特性将约束的MDP问题转化为简单的确定性问题,获得高效求解 | 简化MDP模型,提高了求解效率 | 忽略了环境的动态性,可靠性差 |
文献[ | 基于服务器响应时间变化检测性能冲突并进行迁移决策,选择一个累计QoS收益最高的ES作为目标ES | 利用时延冲突主动进行服务迁移,与被动方案相比更及时、可靠 | 忽略了动态环境特点,缺乏监测数据准确性的保障机制 |
文献[ | 考虑了每个虚拟机的多个属性因素并建立相应的决策矩阵,通过决策矩阵来决策迁移 | 充分考虑了能量、时延等开销的影响,实用性较高 | 忽略了网络环境的动态性,缺乏参数的实时更新机制 |
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