Abstract
We consider job dispatching in systems with N parallel servers, where jobs arrive according to a Poisson process of rate λ. 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 ∆ 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.
Original language | English |
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Pages (from-to) | 72-73 |
Number of pages | 2 |
Journal | Performance Evaluation Review |
Volume | 46 |
Issue number | 3 |
DOIs | |
Publication status | Published - 25 Jan 2019 |
Event | 36th IFIP Performance Conference 2018 - Toulouse, France Duration: 5 Dec 2018 → 7 Dec 2018 |
Keywords
- Delay performance
- Dispatching
- Parallel-server system
- Probing policies
- Redundancy