25,550 research outputs found
Mixed Polling with Rerouting and Applications
Queueing systems with a single server in which customers wait to be served at
a finite number of distinct locations (buffers/queues) are called discrete
polling systems. Polling systems in which arrivals of users occur anywhere in a
continuum are called continuous polling systems. Often one encounters a
combination of the two systems: the users can either arrive in a continuum or
wait in a finite set (i.e. wait at a finite number of queues). We call these
systems mixed polling systems. Also, in some applications, customers are
rerouted to a new location (for another service) after their service is
completed. In this work, we study mixed polling systems with rerouting. We
obtain their steady state performance by discretization using the known pseudo
conservation laws of discrete polling systems. Their stationary expected
workload is obtained as a limit of the stationary expected workload of a
discrete system. The main tools for our analysis are: a) the fixed point
analysis of infinite dimensional operators and; b) the convergence of Riemann
sums to an integral.
We analyze two applications using our results on mixed polling systems and
discuss the optimal system design. We consider a local area network, in which a
moving ferry facilitates communication (data transfer) using a wireless link.
We also consider a distributed waste collection system and derive the optimal
collection point. In both examples, the service requests can arrive anywhere in
a subset of the two dimensional plane. Namely, some users arrive in a
continuous set while others wait for their service in a finite set. The only
polling systems that can model these applications are mixed systems with
rerouting as introduced in this manuscript.Comment: to appear in Performance Evaluatio
Age-Optimal Updates of Multiple Information Flows
In this paper, we study an age of information minimization problem, where
multiple flows of update packets are sent over multiple servers to their
destinations. Two online scheduling policies are proposed. When the packet
generation and arrival times are synchronized across the flows, the proposed
policies are shown to be (near) optimal for minimizing any time-dependent,
symmetric, and non-decreasing penalty function of the ages of the flows over
time in a stochastic ordering sense
Scheduling a multi class queue with many exponential servers: asymptotic optimality in heavy traffic
We consider the problem of scheduling a queueing system in which many
statistically identical servers cater to several classes of impatient
customers. Service times and impatience clocks are exponential while arrival
processes are renewal. Our cost is an expected cumulative discounted function,
linear or nonlinear, of appropriately normalized performance measures. As a
special case, the cost per unit time can be a function of the number of
customers waiting to be served in each class, the number actually being served,
the abandonment rate, the delay experienced by customers, the number of idling
servers, as well as certain combinations thereof. We study the system in an
asymptotic heavy-traffic regime where the number of servers n and the offered
load r are simultaneously scaled up and carefully balanced: n\approx r+\beta
\sqrtr for some scalar \beta. This yields an operation that enjoys the benefits
of both heavy traffic (high server utilization) and light traffic (high service
levels.
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