2,405 research outputs found
Load Balancing in Large-Scale Systems with Multiple Dispatchers
Load balancing algorithms play a crucial role in delivering robust
application performance in data centers and cloud networks. Recently, strong
interest has emerged in Join-the-Idle-Queue (JIQ) algorithms, which rely on
tokens issued by idle servers in dispatching tasks and outperform power-of-
policies. Specifically, JIQ strategies involve minimal information exchange,
and yet achieve zero blocking and wait in the many-server limit. The latter
property prevails in a multiple-dispatcher scenario when the loads are strictly
equal among dispatchers. For various reasons it is not uncommon however for
skewed load patterns to occur. We leverage product-form representations and
fluid limits to establish that the blocking and wait then no longer vanish,
even for arbitrarily low overall load. Remarkably, it is the least-loaded
dispatcher that throttles tokens and leaves idle servers stranded, thus acting
as bottleneck.
Motivated by the above issues, we introduce two enhancements of the ordinary
JIQ scheme where tokens are either distributed non-uniformly or occasionally
exchanged among the various dispatchers. We prove that these extensions can
achieve zero blocking and wait in the many-server limit, for any subcritical
overall load and arbitrarily skewed load profiles. Extensive simulation
experiments demonstrate that the asymptotic results are highly accurate, even
for moderately sized systems
GPS queues with heterogeneous traffic classes
We consider a queue fed by a mixture of light-tailed and heavy-tailed traffic. The two traffic classes are served in accordance with the generalized processor sharing (GPS) discipline. GPS-based scheduling algorithms, such as weighted fair queueing (WFQ), have emerged as an important mechanism for achieving service differentiation in integrated networks. We derive the asymptotic workload behavior of the light-tailed class for the situation where its GPS weight is larger than its traffic intensity. The GPS mechanism ensures that the workload is bounded above by that in an isolated system with the light-tailed class served in isolation at a constant rate equal to its GPS weight. We show that the workload distribution is in fact asymptotically equivalent to that in the isolated system, multiplied with a certain pre-factor, which accounts for the interaction with the heavy-tailed class. Specifically, the pre-factor represents the probability that the heavy-tailed class is backlogged long enough for the light-tailed class to reach overflow. The results provide crucial qualitative insight in the typical overflow scenario
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