47 research outputs found
Delay Optimal Server Assignment to Symmetric Parallel Queues with Random Connectivities
In this paper, we investigate the problem of assignment of identical
servers to a set of parallel queues in a time slotted queueing system. The
connectivity of each queue to each server is randomly changing with time; each
server can serve at most one queue and each queue can be served by at most one
server per time slot. Such queueing systems were widely applied in modeling the
scheduling (or resource allocation) problem in wireless networks. It has been
previously proven that Maximum Weighted Matching (MWM) is a throughput optimal
server assignment policy for such queueing systems. In this paper, we prove
that for a symmetric system with i.i.d. Bernoulli packet arrivals and
connectivities, MWM minimizes, in stochastic ordering sense, a broad range of
cost functions of the queue lengths including total queue occupancy (or
equivalently average queueing delay).Comment: 6 pages, 4 figures, Proc. IEEE CDC-ECC 201
Queueing Networks of Random Link Topology: Stationary Dynamics of Maximal Throughput Schedules
In this paper, we study the stationary dynamics of a processing system comprised of several parallel queues and a single server of constant rate. The connectivity of the server to each queue is randomly modulated, taking values 1 (connected) or 0 (severed). At any given time, only the currently connected queues may receive service. A key issue is how to schedule the server on the connected queues in order to maximize the system throughput. We investigate two dynamic schedules, which are shown to stabilize the system under the highest possible traffic load, by scheduling the server on the connected queue of maximum backlog (workload or job number). They are analyzed under stationary ergodic traffic flows and connectivity modulation. The results also extend to the more general case of random server rate.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/47640/1/11134_2005_Article_858.pd
Achieving Optimal Throughput and Near-Optimal Asymptotic Delay Performance in Multi-Channel Wireless Networks with Low Complexity: A Practical Greedy Scheduling Policy
In this paper, we focus on the scheduling problem in multi-channel wireless
networks, e.g., the downlink of a single cell in fourth generation (4G)
OFDM-based cellular networks. Our goal is to design practical scheduling
policies that can achieve provably good performance in terms of both throughput
and delay, at a low complexity. While a class of -complexity
hybrid scheduling policies are recently developed to guarantee both
rate-function delay optimality (in the many-channel many-user asymptotic
regime) and throughput optimality (in the general non-asymptotic setting),
their practical complexity is typically high. To address this issue, we develop
a simple greedy policy called Delay-based Server-Side-Greedy (D-SSG) with a
\lower complexity , and rigorously prove that D-SSG not only achieves
throughput optimality, but also guarantees near-optimal asymptotic delay
performance. Specifically, we show that the rate-function attained by D-SSG for
any delay-violation threshold , is no smaller than the maximum achievable
rate-function by any scheduling policy for threshold . Thus, we are able
to achieve a reduction in complexity (from of the hybrid
policies to ) with a minimal drop in the delay performance. More
importantly, in practice, D-SSG generally has a substantially lower complexity
than the hybrid policies that typically have a large constant factor hidden in
the notation. Finally, we conduct numerical simulations to validate
our theoretical results in various scenarios. The simulation results show that
D-SSG not only guarantees a near-optimal rate-function, but also empirically is
virtually indistinguishable from delay-optimal policies.Comment: Accepted for publication by the IEEE/ACM Transactions on Networking,
February 2014. A preliminary version of this work was presented at IEEE
INFOCOM 2013, Turin, Italy, April 201