We consider job dispatching in systems with N parallel servers. In redundancy-d policies, replicas of an arriving job are assigned to d≤N servers selected uniformly at random (without replacement) with the objective to reduce the delay. We introduce a quite general workload model, in which job sizes have some probability distribution while the speeds (slowdown factors) of the various servers for a given job are allowed to be inter-dependent and non-identically distributed. This allows not only for inherent speed differences among different servers, but also for affinity relations. We further propose two novel redundancy policies, so-called delta-probe-d policies, where d probes of a fixed, small, size Δ are created for each incoming job, and assigned to d servers selected uniformly at random. As soon as the first of these d probe tasks finishes, the actual job is assigned for execution – with the same speed – to the corresponding server and the other probe tasks are abandoned. We also consider a delta-probe-d policy in which the probes receive preemptive-resume priority over regular jobs. The aim of these policies is to retain the benefits of redundancy-d policies while accounting for systematic speed differences and mitigating the risks of running replicas of the full job simultaneously for long periods of time. Analytical and numerical results are presented to evaluate the effect of both probing policies on the job latency, and to illustrate the potential performance improvements.
|Number of pages||15|
|Publication status||Published - 1 Nov 2018|
- Delay performance
- Parallel-server system
- Probing policies