350 research outputs found
Approaching Throughput-optimality in Distributed CSMA Scheduling Algorithms with Collisions
It was shown recently that CSMA (Carrier Sense Multiple Access)-like
distributed algorithms can achieve the maximal throughput in wireless networks
(and task processing networks) under certain assumptions. One important, but
idealized assumption is that the sensing time is negligible, so that there is
no collision. In this paper, we study more practical CSMA-based scheduling
algorithms with collisions. First, we provide a Markov chain model and give an
explicit throughput formula which takes into account the cost of collisions and
overhead. The formula has a simple form since the Markov chain is "almost"
time-reversible. Second, we propose transmission-length control algorithms to
approach throughput optimality in this case. Sufficient conditions are given to
ensure the convergence and stability of the proposed algorithms. Finally, we
characterize the relationship between the CSMA parameters (such as the maximum
packet lengths) and the achievable capacity region.Comment: To appear in IEEE/ACM Transactions on Networking. This is the longer
versio
Distributed Random Access Algorithm: Scheduling and Congesion Control
This paper provides proofs of the rate stability, Harris recurrence, and
epsilon-optimality of CSMA algorithms where the backoff parameter of each node
is based on its backlog. These algorithms require only local information and
are easy to implement.
The setup is a network of wireless nodes with a fixed conflict graph that
identifies pairs of nodes whose simultaneous transmissions conflict. The paper
studies two algorithms. The first algorithm schedules transmissions to keep up
with given arrival rates of packets. The second algorithm controls the arrivals
in addition to the scheduling and attempts to maximize the sum of the utilities
of the flows of packets at the different nodes. For the first algorithm, the
paper proves rate stability for strictly feasible arrival rates and also Harris
recurrence of the queues. For the second algorithm, the paper proves the
epsilon-optimality. Both algorithms operate with strictly local information in
the case of decreasing step sizes, and operate with the additional information
of the number of nodes in the network in the case of constant step size
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