913 research outputs found
Dynamic Server Allocation over Time Varying Channels with Switchover Delay
We consider a dynamic server allocation problem over parallel queues with
randomly varying connectivity and server switchover delay between the queues.
At each time slot the server decides either to stay with the current queue or
switch to another queue based on the current connectivity and the queue length
information. Switchover delay occurs in many telecommunications applications
and is a new modeling component of this problem that has not been previously
addressed. We show that the simultaneous presence of randomly varying
connectivity and switchover delay changes the system stability region and the
structure of optimal policies. In the first part of the paper, we consider a
system of two parallel queues, and develop a novel approach to explicitly
characterize the stability region of the system using state-action frequencies
which are stationary solutions to a Markov Decision Process (MDP) formulation.
We then develop a frame-based dynamic control (FBDC) policy, based on the
state-action frequencies, and show that it is throughput-optimal asymptotically
in the frame length. The FBDC policy is applicable to a broad class of network
control systems and provides a new framework for developing throughput-optimal
network control policies using state-action frequencies. Furthermore, we
develop simple Myopic policies that provably achieve more than 90% of the
stability region. In the second part of the paper, we extend our results to
systems with an arbitrary but finite number of queues.Comment: 38 Pages, 18 figures. arXiv admin note: substantial text overlap with
arXiv:1008.234
Minimizing the Age of Information in Wireless Networks with Stochastic Arrivals
We consider a wireless network with a base station serving multiple traffic
streams to different destinations. Packets from each stream arrive to the base
station according to a stochastic process and are enqueued in a separate (per
stream) queue. The queueing discipline controls which packet within each queue
is available for transmission. The base station decides, at every time t, which
stream to serve to the corresponding destination. The goal of scheduling
decisions is to keep the information at the destinations fresh. Information
freshness is captured by the Age of Information (AoI) metric.
In this paper, we derive a lower bound on the AoI performance achievable by
any given network operating under any queueing discipline. Then, we consider
three common queueing disciplines and develop both an Optimal Stationary
Randomized policy and a Max-Weight policy under each discipline. Our approach
allows us to evaluate the combined impact of the stochastic arrivals, queueing
discipline and scheduling policy on AoI. We evaluate the AoI performance both
analytically and using simulations. Numerical results show that the performance
of the Max-Weight policy is close to the analytical lower bound
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
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