Steady state analysis and transient solution of an M/M/2 queueing system with differentiated vacations and breakdown

Single Server Markovian Queue With Time‐Homogeneous Partial and Complete Breakdowns and Cost Optimization by Genetic Algorithm

This paper investigates the steady‐state performance of an queueing system subject to random and time‐homogeneous partial and complete server breakdowns. Under partial breakdown conditions, the server continues to provide service at a reduced rate, while service is entirely suspended during complete breakdown periods...

Analysis of PH/M/c Queueing Model with Two-Threshold Control for P2P Network

The results show that the proposed analytical framework can effectively characterize the steady-state behavior of P2P systems under two-threshold control and provide quantitative support for parameter design.

Staffing for many-server systems facing non-standard arrival processes

Inferential aspects of a M/M/1 queuing system using bivariate prior

This paper presents a Bayesian framework for estimating the performance measures of a single-server Markovian queue. A bivariate prior is employed to naturally incorporate the system's ergodicity condition along with the traditional likelihood function, which fundamentally differentiates this work from that of the exis...

New estimation for the tra ffi c intensity parameter of a single-server queueing system with finite capacity

This paper focuses on the M / M / 1 / K single-server queueing model and estimates the tra ffi c intensity using Bayesian, E -Bayesian, hierarchical Bayesian, and a new EE -Bayesian method.

Performance Analysis of a Time-Sharing Queue with Server Breakdown, Discouraging Arrivals and Reneging

This paper investigates a single-server time-sharing queueing system with server breakdowns, discouraging arrivals and customer reneging. Customers arrive according to a Poisson process with rate λ while the server is operational. During server breakdowns, the arrival rate is reduced to represent customer discouragemen...