24,120 research outputs found
Optimisation of stochastic networks with blocking: a functional-form approach
This paper introduces a class of stochastic networks with blocking, motivated
by applications arising in cellular network planning, mobile cloud computing,
and spare parts supply chains. Blocking results in lost revenue due to
customers or jobs being permanently removed from the system. We are interested
in striking a balance between mitigating blocking by increasing service
capacity, and maintaining low costs for service capacity. This problem is
further complicated by the stochastic nature of the system. Owing to the
complexity of the system there are no analytical results available that
formulate and solve the relevant optimization problem in closed form.
Traditional simulation-based methods may work well for small instances, but the
associated computational costs are prohibitive for networks of realistic size.
We propose a hybrid functional-form based approach for finding the optimal
resource allocation, combining the speed of an analytical approach with the
accuracy of simulation-based optimisation. The key insight is to replace the
computationally expensive gradient estimation in simulation optimisation with a
closed-form analytical approximation that is calibrated using a single
simulation run. We develop two implementations of this approach and conduct
extensive computational experiments on complex examples to show that it is
capable of substantially improving system performance. We also provide evidence
that our approach has substantially lower computational costs compared to
stochastic approximation
A Survey on Delay-Aware Resource Control for Wireless Systems --- Large Deviation Theory, Stochastic Lyapunov Drift and Distributed Stochastic Learning
In this tutorial paper, a comprehensive survey is given on several major
systematic approaches in dealing with delay-aware control problems, namely the
equivalent rate constraint approach, the Lyapunov stability drift approach and
the approximate Markov Decision Process (MDP) approach using stochastic
learning. These approaches essentially embrace most of the existing literature
regarding delay-aware resource control in wireless systems. They have their
relative pros and cons in terms of performance, complexity and implementation
issues. For each of the approaches, the problem setup, the general solution and
the design methodology are discussed. Applications of these approaches to
delay-aware resource allocation are illustrated with examples in single-hop
wireless networks. Furthermore, recent results regarding delay-aware multi-hop
routing designs in general multi-hop networks are elaborated. Finally, the
delay performance of the various approaches are compared through simulations
using an example of the uplink OFDMA systems.Comment: 58 pages, 8 figures; IEEE Transactions on Information Theory, 201
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