论文标题
基于阈值的重复和复制来解决工作服务器亲和力关系
Threshold-based rerouting and replication for resolving job-server affinity relations
论文作者
论文摘要
我们考虑一个具有多种作业类型和两个并行服务器池的系统。在池中，服务器是均匀的，但是在跨池之间可能不是在某种意义上，在作业的服务速度可能取决于其类型以及服务器池。到达后，立即将作业分配到服务器池。这可能基于对其类型的（部分）知识，但可能无法使用这些知识。但是，可以在工作中获得有关工作类型的信息；随着服务的进展，该作业类型的服务速度较低的可能性增加了，从而激励了在不同，可能更快的服务器上执行作业的动力。考虑了两种策略：将作业重新路由到另一个服务器池，或在此处复制。 我们确定了完全未知和部分已知的工作类型的重新路由和复制策略下的每台服务器的有效负载。我们还研究了这些政策对稳定性结合的影响，并发现工作类型的不确定性可能会大大降低绩效。对于（高度）不平衡的服务速度，充分复制实现了最大的稳定性，而（几乎）平衡的服务速度没有复制速度最大化稳定性。最后，我们讨论了基于阈值的策略的使用如何帮助改善完全或部分未知的工作类型的预期延迟。
We consider a system with several job types and two parallel server pools. Within the pools the servers are homogeneous, but across pools possibly not in the sense that the service speed of a job may depend on its type as well as the server pool. Immediately upon arrival, jobs are assigned to a server pool. This could be based on (partial) knowledge of their type, but such knowledge might not be available. Information about the job type can however be obtained while the job is in service; as the service progresses, the likelihood that the service speed of this job type is low increases, creating an incentive to execute the job on different, possibly faster, server(s). Two policies are considered: reroute the job to the other server pool, or replicate it there. We determine the effective load per server under both the rerouting and replication policy for completely unknown as well as partly known job types. We also examine the impact of these policies on the stability bound, and find that the uncertainty in job types may significantly degrade the performance. For (highly) unbalanced service speeds full replication achieves the largest stability bound while for (nearly) balanced service speeds no replication maximizes the stability bound. Finally, we discuss how the use of threshold-based policies can help improve the expected latency for completely or partly unknown job types.
