197,686 research outputs found
Delay performance in random-access grid networks
We examine the impact of torpid mixing and meta-stability issues on the delay
performance in wireless random-access networks. Focusing on regular meshes as
prototypical scenarios, we show that the mean delays in an toric
grid with normalized load are of the order . This
superlinear delay scaling is to be contrasted with the usual linear growth of
the order in conventional queueing networks. The intuitive
explanation for the poor delay characteristics is that (i) high load requires a
high activity factor, (ii) a high activity factor implies extremely slow
transitions between dominant activity states, and (iii) slow transitions cause
starvation and hence excessively long queues and delays. Our proof method
combines both renewal and conductance arguments. A critical ingredient in
quantifying the long transition times is the derivation of the communication
height of the uniformized Markov chain associated with the activity process. We
also discuss connections with Glauber dynamics, conductance and mixing times.
Our proof framework can be applied to other topologies as well, and is also
relevant for the hard-core model in statistical physics and the sampling from
independent sets using single-site update Markov chains
Delay Performance and Mixing Times in Random-Access Networks
We explore the achievable delay performance in wireless random-access
networks. While relatively simple and inherently distributed in nature,
suitably designed queue-based random-access schemes provide the striking
capability to match the optimal throughput performance of centralized
scheduling mechanisms in a wide range of scenarios. The specific type of
activation rules for which throughput optimality has been established, may
however yield excessive queues and delays.
Motivated by that issue, we examine whether the poor delay performance is
inherent to the basic operation of these schemes, or caused by the specific
kind of activation rules. We derive delay lower bounds for queue-based
activation rules, which offer fundamental insight in the cause of the excessive
delays. For fixed activation rates we obtain lower bounds indicating that
delays and mixing times can grow dramatically with the load in certain
topologies as well
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
Queue-Based Random-Access Algorithms: Fluid Limits and Stability Issues
We use fluid limits to explore the (in)stability properties of wireless
networks with queue-based random-access algorithms. Queue-based random-access
schemes are simple and inherently distributed in nature, yet provide the
capability to match the optimal throughput performance of centralized
scheduling mechanisms in a wide range of scenarios. Unfortunately, the type of
activation rules for which throughput optimality has been established, may
result in excessive queue lengths and delays. The use of more
aggressive/persistent access schemes can improve the delay performance, but
does not offer any universal maximum-stability guarantees. In order to gain
qualitative insight and investigate the (in)stability properties of more
aggressive/persistent activation rules, we examine fluid limits where the
dynamics are scaled in space and time. In some situations, the fluid limits
have smooth deterministic features and maximum stability is maintained, while
in other scenarios they exhibit random oscillatory characteristics, giving rise
to major technical challenges. In the latter regime, more aggressive access
schemes continue to provide maximum stability in some networks, but may cause
instability in others. Simulation experiments are conducted to illustrate and
validate the analytical results
D2D-Based Grouped Random Access to Mitigate Mobile Access Congestion in 5G Sensor Networks
The Fifth Generation (5G) wireless service of sensor networks involves
significant challenges when dealing with the coordination of ever-increasing
number of devices accessing shared resources. This has drawn major interest
from the research community as many existing works focus on the radio access
network congestion control to efficiently manage resources in the context of
device-to-device (D2D) interaction in huge sensor networks. In this context,
this paper pioneers a study on the impact of D2D link reliability in
group-assisted random access protocols, by shedding the light on beneficial
performance and potential limitations of approaches of this kind against
tunable parameters such as group size, number of sensors and reliability of D2D
links. Additionally, we leverage on the association with a Geolocation Database
(GDB) capability to assist the grouping decisions by drawing parallels with
recent regulatory-driven initiatives around GDBs and arguing benefits of the
suggested proposal. Finally, the proposed method is approved to significantly
reduce the delay over random access channels, by means of an exhaustive
simulation campaign.Comment: First submission to IEEE Communications Magazine on Oct.28.2017.
Accepted on Aug.18.2019. This is the camera-ready versio
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