Multiple Objective Fairness Scheduling Optimization Algorithms Based on Multiple DAGs in Heterogeneous Edge Computing
Multiple Objective Fairness Scheduling Optimization Algorithms Based on Multiple DAGs in Heterogeneous Edge Computing
复制标题
异构边缘计算中基于多DAG的多目标公平调度优化算法
DOI：
10.1142/s0218126623501414
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发表时间：
2022-11
期刊：
影响因子：
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通讯作者：
Guoqi Xie
中科院分区：
文献类型：
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作者：
Fan Yang;Kelei Zhan;Jiayi Du;Zhilin Huang;Guoqi Xie
边缘计算的快速发展推动了应用需求的不断增长。服务质量（QoS），必须提高，因为这个指标涉及的问题，如不公平和短有向无环图（DAG）调度长度。为了有效地解决多DAG任务的不公平性问题，提出了一种多DAG深度公平任务调度算法（MDDF），该算法在测量DAG中任务深度的基础上，提高了多DAG的公平性，提高了用户的QoS，获得了快速的响应。通过与四种常见的启发式调度方法的比较，验证了该算法的有效性.我们提出了另一种算法称为快速多DAG深度公平任务调度（FMDDF）具有高的平均减速，以减少短DAG的调度长度，加快响应时间。实验结果表明，与其他算法相比，FMDDF能有效提高调度效率，缩短短DAG调度长度约5%，MDDF能在缩短短DAG调度长度的同时提高公平性约2%.
The rapid development of edge computing has promoted the growing demand of applications. Quality of service (QoS) must be improved because this index involves issues such as unfairness and short Directed Acyclic Graph (DAG) schedule length. We propose a new algorithm named Multiple DAGs Depth Fairness Task Scheduling (MDDF) in this study to solve the multi-DAG task unfairness problem effectively, the algorithm on the basis of the measured depth of the task in the DAG, improves the fairness of multiple DAG, enhance the user QoS and obtain a fast response. The proposed algorithm is then compared with four common heuristic scheduling methods to verify its effectiveness. We propose another algorithm called Fast Multi-DAG Depth Fairness Task Scheduling (FMDDF) with high average slowdown to reduce the schedule length of short DAG and accelerate the response time. Experimental results show that FMDDF can improve scheduling and shorten the schedule length of short DAG by about 5% and MDDF can enhance fairness by about 2% while reducing the short DAG schedule length compared with other algorithms.