Multichannel scheduling and its connection to queueing network control problem

2010 ◽  
Author(s):  
Pouya Tehrani ◽  
Qing Zhao
Keyword(s):  
Control Problem ◽  
Queueing Network ◽  
Network Control

scholarly journals Online Self-Organizing Network Control with Time Averaged Weighted Throughput Objective

2018 ◽  
Vol 2018 ◽  
pp. 1-11
Author(s):  
Zhicong Zhang ◽  
Shuai Li ◽  
Xiaohui Yan
Keyword(s):  
Reinforcement Learning ◽  
Control Problem ◽  
Decision Model ◽  
Learning Algorithm ◽  
Queueing Network ◽  
Network Control ◽  
Learning Ability ◽  
Control Decision ◽  
Self Organizing ◽  
Reinforcement Learning Algorithm

We study an online multisource multisink queueing network control problem characterized with self-organizing network structure and self-organizing job routing. We decompose the self-organizing queueing network control problem into a series of interrelated Markov Decision Processes and construct a control decision model for them based on the coupled reinforcement learning (RL) architecture. To maximize the mean time averaged weighted throughput of the jobs through the network, we propose a reinforcement learning algorithm with time averaged reward to deal with the control decision model and obtain a control policy integrating the jobs routing selection strategy and the jobs sequencing strategy. Computational experiments verify the learning ability and the effectiveness of the proposed reinforcement learning algorithm applied in the investigated self-organizing network control problem.

Urban Oversaturated Traffic Network Control Based on Preference Multi-Objective Compatible Optimization Control

2011 ◽  
Vol 317-319 ◽  
pp. 1373-1384 ◽  
Author(s):  
Juan Chen ◽  
Chang Liang Yuan
Keyword(s):  
Control Problem ◽  
Control Algorithm ◽  
Control Method ◽  
Network Control ◽  
Feasible Region ◽  
Traffic Network ◽  
Total Delay ◽  
Multi Objective ◽  
Optimization Control ◽  
Objective Control

To solve the traffic congestion control problem on oversaturated network, the total delay is classified into two parts: the feeding delay and the non-feeding delay, and the control problem is formulated as a conflicted multi-objective control problem. The simultaneous control of multiple objectives is different from single objective control in that there is no unique solution to multi-objective control problems(MOPs). Multi-objective control usually involves many conflicting and incompatible objectives, therefore, a set of optimal trade-off solutions known as the Pareto-optimal solutions is required. Based on this background, a modified compatible control algorithm(MOCC) hunting for suboptimal and feasible region as the control aim rather than precise optimal point is proposed in this paper to solve the conflicted oversaturated traffic network control problem. Since it is impossible to avoid the inaccurate system model and input disturbance, the controller of the proposed multi-objective compatible control strategy is designed based on feedback control structure. Besides, considering the difference between control problem and optimization problem, user's preference are incorporated into multi-objective compatible control algorithm to guide the search direction. The proposed preference based compatible optimization control algorithm(PMOCC) is used to solve the oversaturated traffic network control problem in a core area of eleven junctions under the simulation environment. It is proved that the proposed compatible optimization control algorithm can handle the oversaturated traffic network control problem effectively than the fixed time control method.

scholarly journals Explicit Solution for a Network Control Problem in the Large Deviation Regime

2004 ◽  
Vol 46 (1/2) ◽  
pp. 159-176 ◽  
Author(s):  
Rami Atar ◽  
Adam Shwartz ◽  
Paul Dupuis
Keyword(s):  
Control Problem ◽  
Explicit Solution ◽  
Large Deviation ◽  
Network Control

Dynamic Scheduling of a Four-Station Queueing Network

1990 ◽  
Vol 4 (1) ◽  
pp. 131-156 ◽  
Author(s):  
C. N. Laws ◽  
G. M. Louth
Keyword(s):  
Control Problem ◽  
Dynamic Scheduling ◽  
Dynamic Control ◽  
Queueing Network ◽  
Single Server ◽  
Scheduling Policies ◽  
Resource Pooling ◽  
Static Scheduling ◽  
Open Queueing Network ◽  
Dynamic Policy

This paper is concerned with the problem of optimally scheduling a multiclass open queueing network with four single-server stations in which dynamic control policies are permitted. Under the assumption that the system is heavily loaded, the original scheduling problem can be approximated by a dynamic control problem involving Brownian motion. We reformulate and solve this problem and, from the interpretation of the solution, we obtain two dynamic scheduling policies for our queueing network. We compare the performance of these policies with two static scheduling policies and a lower bound via simulation. Our results suggest that under either dynamic policy the system, at least when heavily loaded, exhibits the form of resource pooling given by the solution to the approximating control problem. Furthermore, even when lightly loaded the system performs better under the dynamic policies than under either static policy.

Urban Oversaturated Traffic Network Control Based on Stability Preference Multi-Objective Compatible Optimization Control

2012 ◽  
Vol 151 ◽  
pp. 503-509
Author(s):  
Juan Chen ◽  
Qing Song Hu ◽  
Xiang Yang Sun
Keyword(s):  
Control Problem ◽  
Pareto Front ◽  
Control Method ◽  
Network Control ◽  
Selection Strategy ◽  
Traffic Network ◽  
Nsga Ii ◽  
Multi Objective ◽  
Optimization Control ◽  
Objective Control

To solve the traffic congestion control problem on oversaturated network, the control problem is formulated as a conflicted multi-objective control problem., a new stability preference multi-objective compatible optimization control(SPMOCC) algorithm is proposed to solve the conflicted multi-objective control problem. In the proposed SPMOCC algorithm, NSGA-II algorithm is adjusted by proposing non-even Pareto front spread preserving strategy to obtain some special area on the Pareto front; a stability preference selection strategy is proposed to obtain stable controller. The proposed SPMOCC is used to solve the oversaturated traffic network control problem in a core area of 11 junctions under the simulation environment. It is proved that the proposed compatible optimization control algorithm can handle the oversaturated traffic network control problem effectively than the fixed time control method.

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