2,657 research outputs found
Asymptotically Optimal Load Balancing Topologies
We consider a system of servers inter-connected by some underlying graph
topology . Tasks arrive at the various servers as independent Poisson
processes of rate . Each incoming task is irrevocably assigned to
whichever server has the smallest number of tasks among the one where it
appears and its neighbors in . Tasks have unit-mean exponential service
times and leave the system upon service completion.
The above model has been extensively investigated in the case is a
clique. Since the servers are exchangeable in that case, the queue length
process is quite tractable, and it has been proved that for any ,
the fraction of servers with two or more tasks vanishes in the limit as . For an arbitrary graph , the lack of exchangeability severely
complicates the analysis, and the queue length process tends to be worse than
for a clique. Accordingly, a graph is said to be -optimal or
-optimal when the occupancy process on is equivalent to that on
a clique on an -scale or -scale, respectively.
We prove that if is an Erd\H{o}s-R\'enyi random graph with average
degree , then it is with high probability -optimal and
-optimal if and as , respectively. This demonstrates that optimality can
be maintained at -scale and -scale while reducing the number of
connections by nearly a factor and compared to a
clique, provided the topology is suitably random. It is further shown that if
contains bounded-degree nodes, then it cannot be -optimal.
In addition, we establish that an arbitrary graph is -optimal when its
minimum degree is , and may not be -optimal even when its minimum
degree is for any .Comment: A few relevant results from arXiv:1612.00723 are included for
convenienc
Mixing Properties of CSMA Networks on Partite Graphs
We consider a stylized stochastic model for a wireless CSMA network.
Experimental results in prior studies indicate that the model provides
remarkably accurate throughput estimates for IEEE 802.11 systems. In
particular, the model offers an explanation for the severe spatial unfairness
in throughputs observed in such networks with asymmetric interference
conditions. Even in symmetric scenarios, however, it may take a long time for
the activity process to move between dominant states, giving rise to potential
starvation issues. In order to gain insight in the transient throughput
characteristics and associated starvation effects, we examine in the present
paper the behavior of the transition time between dominant activity states. We
focus on partite interference graphs, and establish how the magnitude of the
transition time scales with the activation rate and the sizes of the various
network components. We also prove that in several cases the scaled transition
time has an asymptotically exponential distribution as the activation rate
grows large, and point out interesting connections with related exponentiality
results for rare events and meta-stability phenomena in statistical physics. In
addition, we investigate the convergence rate to equilibrium of the activity
process in terms of mixing times.Comment: Valuetools, 6th International Conference on Performance Evaluation
Methodologies and Tools, October 9-12, 2012, Carg\`ese, Franc
Slow transitions, slow mixing and starvation in dense random-access networks
We consider dense wireless random-access networks, modeled as systems of
particles with hard-core interaction. The particles represent the network users
that try to become active after an exponential back-off time, and stay active
for an exponential transmission time. Due to wireless interference, active
users prevent other nearby users from simultaneous activity, which we describe
as hard-core interaction on a conflict graph. We show that dense networks with
aggressive back-off schemes lead to extremely slow transitions between dominant
states, and inevitably cause long mixing times and starvation effects.Comment: 29 pages, 5 figure
Achievable Performance in Product-Form Networks
We characterize the achievable range of performance measures in product-form
networks where one or more system parameters can be freely set by a network
operator. Given a product-form network and a set of configurable parameters, we
identify which performance measures can be controlled and which target values
can be attained. We also discuss an online optimization algorithm, which allows
a network operator to set the system parameters so as to achieve target
performance metrics. In some cases, the algorithm can be implemented in a
distributed fashion, of which we give several examples. Finally, we give
conditions that guarantee convergence of the algorithm, under the assumption
that the target performance metrics are within the achievable range.Comment: 50th Annual Allerton Conference on Communication, Control and
Computing - 201
Universality of Load Balancing Schemes on Diffusion Scale
We consider a system of parallel queues with identical exponential
service rates and a single dispatcher where tasks arrive as a Poisson process.
When a task arrives, the dispatcher always assigns it to an idle server, if
there is any, and to a server with the shortest queue among randomly
selected servers otherwise . This load balancing scheme
subsumes the so-called Join-the-Idle Queue (JIQ) policy and the
celebrated Join-the-Shortest Queue (JSQ) policy as two crucial
special cases. We develop a stochastic coupling construction to obtain the
diffusion limit of the queue process in the Halfin-Whitt heavy-traffic regime,
and establish that it does not depend on the value of , implying that
assigning tasks to idle servers is sufficient for diffusion level optimality
Queues with random back-offs
We consider a broad class of queueing models with random state-dependent
vacation periods, which arise in the analysis of queue-based back-off
algorithms in wireless random-access networks. In contrast to conventional
models, the vacation periods may be initiated after each service completion,
and can be randomly terminated with certain probabilities that depend on the
queue length. We examine the scaled queue length and delay in a heavy-traffic
regime, and demonstrate a sharp trichotomy, depending on how the activation
rate and vacation probability behave as function of the queue length. In
particular, the effect of the vacation periods may either (i) completely vanish
in heavy-traffic conditions, (ii) contribute an additional term to the queue
lengths and delays of similar magnitude, or even (iii) give rise to an
order-of-magnitude increase. The heavy-traffic asymptotics are obtained by
combining stochastic lower and upper bounds with exact results for some
specific cases. The heavy-traffic trichotomy provides valuable insight in the
impact of the back-off algorithms on the delay performance in wireless
random-access networks
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