Efficient task scheduling improves offloading performance in mobile edge computing (MEC) environment. The jobs offloaded by different users would have different dependent tasks with diverse resource demands at different times. Meanwhile, due to the heterogeneity of edge servers configurations in MEC, offloaded jobs may frequently have placement constraints, restricting them to run on a particular class of edge servers meeting specific software running settings. This spatio-temporal information gives the opportunity to improve the resource utilization of the computing system. In this paper, we study the scheduling method for the jobs consisting of dependent tasks offloaded by different users in MEC. A new task offloading scheduler, Horae, is proposed to not only improve the resource utilization of MEC environment but also guarantees to select the edge server which could satisfy placement constraints for each offloaded task. Concretely, considering the fact that each job would experience slack time as a result of competing for limited resource with other jobs in MEC, Horae minimizes the sum of all slack time values of all the jobs while guaranteeing placement constraints, and therefore improve the resource utilization of the system. Horae was validated for its feasibility and efficiency by means of extensive experiments, which are presented in this paper.

高效的任务调度可改善移动边缘计算（MEC）环境中的卸载性能。由不同用户分担的作业将在不同时间具有不同的依赖任务和不同的资源需求。同时，由于MEC中边缘服务器配置的异构性，卸载的作业可能经常具有放置限制，限制它们在满足特定软件运行设置的特定类别的边缘服务器上运行。该时空信息为改善计算系统的资源利用率提供了机会。在本文中，我们研究了由MEC中由不同用户分担的依赖任务组成的作业的调度方法。提出了一种新的任务卸载调度器Horae，不仅可以提高MEC环境的资源利用率，而且可以保证选择能够满足每个卸载任务的放置约束的边缘服务器。具体来说，考虑到每个工作都会因与MEC中其他工作竞争有限的资源而经历闲置时间的事实，因此Horae在保证布局约束的同时，将所有工作的所有闲置时间值的总和最小化，从而提高了系统的资源利用率。本文介绍了Horae，并通过广泛的实验验证了Horae的可行性和效率。