14 research outputs found
Throughput-Optimal Random Access with Order-Optimal Delay
In this paper, we consider CSMA policies for scheduling of multihop wireless
networks with one-hop traffic. The main contribution of this paper is to
propose Unlocking CSMA (U-CSMA) policy that enables to obtain high throughput
with low (average) packet delay for large wireless networks. In particular, the
delay under U-CSMA policy becomes order-optimal. For one-hop traffic, delay is
defined to be order-optimal if it is O(1), i.e., it stays bounded, as the
network-size increases to infinity. Using mean field theory techniques, we
analytically show that for torus (grid-like) interference topologies with
one-hop traffic, to achieve a network load of , the delay under U-CSMA
policy becomes as the network-size increases, and hence,
delay becomes order optimal. We conduct simulations for general random
geometric interference topologies under U-CSMA policy combined with congestion
control to maximize a network-wide utility. These simulations confirm that
order optimality holds, and that we can use U-CSMA policy jointly with
congestion control to operate close to the optimal utility with a low packet
delay in arbitrarily large random geometric topologies. To the best of our
knowledge, it is for the first time that a simple distributed scheduling policy
is proposed that in addition to throughput/utility-optimality exhibits delay
order-optimality.Comment: 44 page
A Fast-CSMA Algorithm for Deadline-Constrained Scheduling over Wireless Fading Channels
Recently, low-complexity and distributed Carrier Sense Multiple Access
(CSMA)-based scheduling algorithms have attracted extensive interest due to
their throughput-optimal characteristics in general network topologies.
However, these algorithms are not well-suited for serving real-time traffic
under time-varying channel conditions for two reasons: (1) the mixing time of
the underlying CSMA Markov Chain grows with the size of the network, which, for
large networks, generates unacceptable delay for deadline-constrained traffic;
(2) since the dynamic CSMA parameters are influenced by the arrival and channel
state processes, the underlying CSMA Markov Chain may not converge to a
steady-state under strict deadline constraints and fading channel conditions.
In this paper, we attack the problem of distributed scheduling for serving
real-time traffic over time-varying channels. Specifically, we consider
fully-connected topologies with independently fading channels (which can model
cellular networks) in which flows with short-term deadline constraints and
long-term drop rate requirements are served. To that end, we first characterize
the maximal set of satisfiable arrival processes for this system and, then,
propose a Fast-CSMA (FCSMA) policy that is shown to be optimal in supporting
any real-time traffic that is within the maximal satisfiable set. These
theoretical results are further validated through simulations to demonstrate
the relative efficiency of the FCSMA policy compared to some of the existing
CSMA-based algorithms.Comment: This work appears in workshop on Resource Allocation and Cooperation
in Wireless Networks (RAWNET), Princeton, NJ, May, 201
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
Optimal CSMA-based Wireless Communication with Worst-case Delay and Non-uniform Sizes
Carrier Sense Multiple Access (CSMA) protocols have been shown to reach the
full capacity region for data communication in wireless networks, with
polynomial complexity. However, current literature achieves the throughput
optimality with an exponential delay scaling with the network size, even in a
simplified scenario for transmission jobs with uniform sizes. Although CSMA
protocols with order-optimal average delay have been proposed for specific
topologies, no existing work can provide worst-case delay guarantee for each
job in general network settings, not to mention the case when the jobs have
non-uniform lengths while the throughput optimality is still targeted. In this
paper, we tackle on this issue by proposing a two-timescale CSMA-based data
communication protocol with dynamic decisions on rate control, link scheduling,
job transmission and dropping in polynomial complexity. Through rigorous
analysis, we demonstrate that the proposed protocol can achieve a throughput
utility arbitrarily close to its offline optima for jobs with non-uniform sizes
and worst-case delay guarantees, with a tradeoff of longer maximum allowable
delay
Scheduling strategies to mitigate the impact of bursty traffic in wireless networks
Recent work has shown that certain queue-length based scheduling algorithms, such as max-weight, can lead to poor delays in the presence of bursty traffic. To overcome this
phenomenon, we consider the problem of designing scheduling policies that are robust to bursty traffic, while also amenable to practical implementation. Specifically, we discuss two mechanisms, one based on adaptive CSMA, and the second based on maximum-weight scheduling with capped queue lengths. We consider a simple queueing network consisting of two conflicting links. The traffic served by the first link is bursty, and is modeled as being heavy-tailed, while traffic at the second link is modeled using a light-tailed arrival process. In this setting, previous work has shown that even the light-tailed traffic would experience heavy-tailed delays under max-weight scheduling. In contrast, we demonstrate a threshold phenomenon in the relationship between the arrival rates and the queue backlog distributions. In particular, we show that with an adaptive CSMA scheme, when the arrival rate of the light-tailed traffic is less than a threshold value, the light-tailed traffic experiences a light-tailed queue backlog at steady state, whereas for arrival rates above the same threshold, the light-tailed traffic experiences a heavy-tailed queue backlog. We also show that a similar threshold behavior for max-weight scheduling with capped queue lengthsNational Science Foundation (U.S.) (Grant CNS-0915988)National Science Foundation (U.S.) (Grant CNS-1217048)United States. Army Research Office. Multidisciplinary University Research Initiative (Grant W911NF-08-1-0238
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