Positive Harris recurrence and diffusion scale analysis of a push pull queueing network

2010 ◽  
Vol 67 (4) ◽  
pp. 201-217 ◽  
Author(s):  
Yoni Nazarathy ◽  
Gideon Weiss
Keyword(s):  
Queueing Network ◽  
Scale Analysis ◽  
Harris Recurrence ◽  
And Diffusion ◽  
Diffusion Scale

scholarly journals Heavy-Traffic Limits for a Many-Server Queueing Network with Switchover

2013 ◽  
Vol 45 (3) ◽  
pp. 645-672 ◽  
Author(s):  
Guodong Pang ◽  
David D. Yao
Keyword(s):  
Load Balancing ◽  
Differential Equations ◽  
Piecewise Linear ◽  
Heavy Traffic ◽  
Queueing Network ◽  
State Dependent ◽  
Diffusion Limits ◽  
Qed Regime ◽  
The Many ◽  
And Diffusion

We study a multiclass Markovian queueing network with switchover across a set of many-server stations. New arrivals to each station follow a nonstationary Poisson process. Each job waiting in queue may, after some exponentially distributed patience time, switch over to another station or leave the network following a probabilistic and state-dependent mechanism. We analyze the performance of such networks under the many-server heavy-traffic limiting regimes, including the critically loaded quality-and-efficiency-driven (QED) regime, and the overloaded efficiency-driven (ED) regime. We also study the limits corresponding to mixing the underloaded quality-driven (QD) regime with the QED and ED regimes. We establish fluid and diffusion limits of the queue-length processes in all regimes. The fluid limits are characterized by ordinary differential equations. The diffusion limits are characterized by stochastic differential equations, with a piecewise-linear drift term and a constant (QED) or time-varying (ED) covariance matrix. We investigate the load balancing effect of switchover in the mixed regimes, demonstrating the migration of workload from overloaded stations to underloaded stations and quantifying the load balancing impact of switchover probabilities.

scholarly journals Control of Fork-Join Processing Networks with Multiple Job Types and Parallel Shared Resources

2021 ◽  
Author(s):  
Erhun Özkan
Keyword(s):  
Queueing Networks ◽  
Queueing Network ◽  
Optimal Scheduling ◽  
Shared Resources ◽  
Asymptotically Optimal ◽  
Scheduling Policy ◽  
Synchronization Constraints ◽  
Processing Network ◽  
Diffusion Scale ◽  
Processing Networks

A fork-join processing network is a queueing network in which tasks associated with a job can be processed simultaneously. Fork-join processing networks are prevalent in computer systems, healthcare, manufacturing, project management, justice systems, and so on. Unlike the conventional queueing networks, fork-join processing networks have synchronization constraints that arise because of the parallel processing of tasks and can cause significant job delays. We study scheduling in fork-join processing networks with multiple job types and parallel shared resources. Jobs arriving in the system fork into arbitrary number of tasks, then those tasks are processed in parallel, and then they join and leave the network. There are shared resources processing multiple job types. We study the scheduling problem for those shared resources (i.e., which type of job to prioritize at any given time) and propose an asymptotically optimal scheduling policy in diffusion scale.

Atomic scale analysis of phase formation and diffusion kinetics in Ag/Al multilayer thin films

2016 ◽  
Vol 120 (19) ◽  
pp. 195306 ◽  
Author(s):  
Hisham Aboulfadl ◽  
Isabella Gallino ◽  
Ralf Busch ◽  
Frank Mücklich
Keyword(s):  
Thin Films ◽  
Phase Formation ◽  
Atomic Scale ◽  
Multilayer Thin Films ◽  
Scale Analysis ◽  
Diffusion Kinetics ◽  
And Diffusion

scholarly journals Heavy-Traffic Limits for a Many-Server Queueing Network with Switchover

2013 ◽  
Vol 45 (03) ◽  
pp. 645-672
Author(s):  
Guodong Pang ◽  
David D. Yao
Keyword(s):  
Load Balancing ◽  
Differential Equations ◽  
Piecewise Linear ◽  
Heavy Traffic ◽  
Queueing Network ◽  
State Dependent ◽  
Diffusion Limits ◽  
Qed Regime ◽  
The Many ◽  
And Diffusion

We study a multiclass Markovian queueing network with switchover across a set of many-server stations. New arrivals to each station follow a nonstationary Poisson process. Each job waiting in queue may, after some exponentially distributed patience time, switch over to another station or leave the network following a probabilistic and state-dependent mechanism. We analyze the performance of such networks under the many-server heavy-traffic limiting regimes, including the critically loaded quality-and-efficiency-driven (QED) regime, and the overloaded efficiency-driven (ED) regime. We also study the limits corresponding to mixing the underloaded quality-driven (QD) regime with the QED and ED regimes. We establish fluid and diffusion limits of the queue-length processes in all regimes. The fluid limits are characterized by ordinary differential equations. The diffusion limits are characterized by stochastic differential equations, with a piecewise-linear drift term and a constant (QED) or time-varying (ED) covariance matrix. We investigate the load balancing effect of switchover in the mixed regimes, demonstrating the migration of workload from overloaded stations to underloaded stations and quantifying the load balancing impact of switchover probabilities.

scholarly journals The Operational Mesogamma-Scale Analysis and Forecast System of the U.S. Army Test and Evaluation Command. Part III: Forecasting with Secondary-Applications Models

2008 ◽  
Vol 47 (4) ◽  
pp. 1105-1122 ◽  
Author(s):  
Robert D. Sharman ◽  
Yubao Liu ◽  
Rong-Shyang Sheu ◽  
Thomas T. Warner ◽  
Daran L. Rife ◽  
...  
Keyword(s):  
Sound Propagation ◽  
Mesoscale Model ◽  
Propagation Model ◽  
Scale Analysis ◽  
Forecast System ◽  
Test And Evaluation ◽  
Transport And Diffusion ◽  
Accuracy Assessments ◽  
And Diffusion ◽  
Range Test

Abstract Output from the Army Test and Evaluation Command’s Four-Dimensional Weather System’s mesoscale model is used to drive secondary-applications models to produce forecasts of quantities of importance for daily decision making at U.S. Army test ranges. Examples of three specific applications—a sound propagation model, a missile trajectory model, and a transport and diffusion model—are given, along with accuracy assessments using cases in which observational data are available for verification. Ensembles of application model forecasts are used to derive probabilities of exceedance of quantities that can be used to help range test directors to make test go–no-go decisions. The ensembles can be based on multiple meteorological forecast runs or on spatial ensembles derived from different soundings extracted from a single meteorological forecast. In most cases, the accuracies of the secondary-application forecasts are sufficient to meet operational needs at the test ranges.

Keypoint Recognition for 3D Head Model Using Geometry Image

2014 ◽  
Vol 654 ◽  
pp. 287-290
Author(s):  
Lu Feng ◽  
Quan Fu ◽  
Xiang Long ◽  
Zhuang Zhi Wu
Keyword(s):  
Conformal Mapping ◽  
Human Head ◽  
Scale Space ◽  
Head Model ◽  
3D Head Model ◽  
And Diffusion ◽  
Diffusion Scale ◽  
Geometry Image

This paper presents a novel and efficient 3D head model keypoint recognition framework based on the geometry image. Based on conformal mapping and diffusion scale space, our method can utilize the SIFT method to extract and describe the keypoint of 3D head model. We use this framework to identify the keypoint of the human head. The experiments shows the robust and efficiency of our method.

Meridional Circulation, Turbulence, and Diffusion Processes in Stars

1976 ◽  
Vol 32 ◽  
pp. 109-116 ◽  
Author(s):  
S. Vauclair
Keyword(s):  
Convection Zone ◽  
Diffusion Processes ◽  
Meridional Circulation ◽  
Diffusion Time ◽  
Work In Progress ◽  
First Results ◽  
Stellar Envelopes ◽  
And Diffusion ◽  
Turbulence And Diffusion ◽  
Hr Diagram

This paper gives the first results of a work in progress, in collaboration with G. Michaud and G. Vauclair. It is a first attempt to compute the effects of meridional circulation and turbulence on diffusion processes in stellar envelopes. Computations have been made for a 2 Mʘstar, which lies in the Am - δ Scuti region of the HR diagram.Let us recall that in Am stars diffusion cannot occur between the two outer convection zones, contrary to what was assumed by Watson (1970, 1971) and Smith (1971), since they are linked by overshooting (Latour, 1972; Toomre et al., 1975). But diffusion may occur at the bottom of the second convection zone. According to Vauclair et al. (1974), the second convection zone, due to He II ionization, disappears after a time equal to the helium diffusion time, and then diffusion may happen at the bottom of the first convection zone, so that the arguments by Watson and Smith are preserved.

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