车辆边缘网络中基于多参数MDP模型的动态服务迁移策略

Dynamic service migration strategy based on MDP model with multiple parameter in vehicular edge network

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。

To handle with the service interruption caused by vehicles’ mobility and limited service coverage of edge servers, a dynamic service migration algorithm based on multi-parameters Markov decision process(MDP) model was put forward for vehicular edge network, which was called as dynamic service migration algorithm based on multiple parameter(DSMMP). Combining delay, bandwidth, server capacity with vehicle motion information, DSMMP constructed a multi-parameters MDP revenue function to remedy the deficiency of distance-based schemes. By using vehicle motion and delay constraints, a candidate server set with several candidate servers was defined, and migration decision through long-term Bellman revenue values was made. In order to improve the dynamic adaptability of the proposed algorithm, the weight values were calculated and updated by leveraging historical information. Simulation results show that our strategy has a good performance in terms of delay, packet loss ratio and service migration times.