THE ISRAELI QUEUE WITH INFINITE NUMBER OF GROUPS

2013 ◽  
Vol 28 (1) ◽  
pp. 1-19 ◽  
Author(s):  
Nir Perel ◽  
Uri Yechiali
Keyword(s):  
Finite Number ◽  
Performance Measures ◽  
Infinite Number ◽  
Batch Service ◽  
Single Server ◽  
Polling System ◽  
Priority Class ◽  
Lower Priority ◽  
The One ◽  
Priority Model

The so called “Israeli Queue” is a single server polling system with batch service of an unlimited size, where the next queue to be visited is the one in which the first customer in line has been waiting for the longest time. The case with finite number of queues (groups) was introduced by Boxma, Van der Wal and Yechiali [3]. In this paper we extend the model to the case with a (possibly) infinite number of queues. We analyze the M/M/1, M/M/c, and M/M/1/N—type queues, as well as a priority model with (at most) M high-priority classes and a single lower priority class. In all models we present an extensive probabilistic analysis and calculate key performance measures.

scholarly journals A Taylor Series Approach for Service-Coupled Queueing Systems with Intermediate Load

2017 ◽  
Vol 2017 ◽  
pp. 1-10 ◽  
Author(s):  
Ekaterina Evdokimova ◽  
Sabine Wittevrongel ◽  
Dieter Fiems
Keyword(s):  
Performance Measures ◽  
Queueing Systems ◽  
Poisson Processes ◽  
Series Expansions ◽  
Service Rate ◽  
Single Server ◽  
Queueing Model ◽  
State Space Explosion ◽  
Finite Queues ◽  
Service Rates

This paper investigates the performance of a queueing model with multiple finite queues and a single server. Departures from the queues are synchronised or coupled which means that a service completion leads to a departure in every queue and that service is temporarily interrupted whenever any of the queues is empty. We focus on the numerical analysis of this queueing model in a Markovian setting: the arrivals in the different queues constitute Poisson processes and the service times are exponentially distributed. Taking into account the state space explosion problem associated with multidimensional Markov processes, we calculate the terms in the series expansion in the service rate of the stationary distribution of the Markov chain as well as various performance measures when the system is (i) overloaded and (ii) under intermediate load. Our numerical results reveal that, by calculating the series expansions of performance measures around a few service rates, we get accurate estimates of various performance measures once the load is above 40% to 50%.

An Infinite Number of Laminagrams from a Finite Number of Radiographs

Radiology ◽  
1971 ◽  
Vol 98 (2) ◽  
pp. 249-255 ◽  
Author(s):  
Earl R. Miller ◽  
Edward M. MoCurry ◽  
Bernard Hruska
Keyword(s):  
Finite Number ◽  
Infinite Number

Some comments on positron–atom scattering at intermediate energy

1982 ◽  
Vol 60 (4) ◽  
pp. 558-564 ◽  
Author(s):  
F. W. Byron Jr.
Keyword(s):  
Finite Number ◽  
Cross Sections ◽  
Infinite Number ◽  
Intermediate Energy ◽  
Total Cross Sections ◽  
Type Approximation ◽  
Atom Scattering ◽  
Target States

A brief survey of available theoretical techniques is given for positron–atom scattering. The distinction between methods involving a finite number of target states and those with an infinite number of target states is emphasized. The situation regarding total cross sections is summarized, and a new, non-perturbative, eikonal-type approximation, based on the work of Wallace, is introduced.

A single server Markovian queuing system with limited buffer and reverse balking

2021 ◽  
Vol 12 (7) ◽  
pp. 1774-1784
Author(s):  
Girin Saikia ◽  
Amit Choudhury
Keyword(s):  
Steady State ◽  
Performance Measures ◽  
Mutual Fund ◽  
System Size ◽  
Queuing System ◽  
Single Server ◽  
Insurance Company ◽  
Number Of Customers ◽  
Steady State Probabilities

The phenomena are balking can be said to have been observed when a customer who has arrived into queuing system decides not to join it. Reverse balking is a particular type of balking wherein the probability that a customer will balk goes down as the system size goes up and vice versa. Such behavior can be observed in investment firms (insurance company, Mutual Fund Company, banks etc.). As the number of customers in the firm goes up, it creates trust among potential investors. Fewer customers would like to balk as the number of customers goes up. In this paper, we develop an M/M/1/k queuing system with reverse balking. The steady-state probabilities of the model are obtained and closed forms of expression of a number of performance measures are derived.

The M/G/1 queue with negative customers

1996 ◽  
Vol 28 (02) ◽  
pp. 540-566 ◽  
Author(s):  
Peter G. Harrison ◽  
Edwige Pitel
Keyword(s):  
Iterative Solution ◽  
Single Server ◽  
Negative Customers ◽  
Poisson Arrival ◽  
First Case ◽  
Full Study ◽  
Service Times ◽  
The Stability ◽  
The One ◽  
Iterative Solution Method

We derive expressions for the generating function of the equilibrium queue length probability distribution in a single server queue with general service times and independent Poisson arrival streams of both ordinary, positive customers and negative customers which eliminate a positive customer if present. For the case of first come first served queueing discipline for the positive customers, we compare the killing strategies in which either the last customer in the queue or the one in service is removed by a negative customer. We then consider preemptive-restart with resampling last come first served queueing discipline for the positive customers, combined with the elimination of the customer in service by a negative customer—the case of elimination of the last customer yields an analysis similar to first come first served discipline for positive customers. The results show different generating functions in contrast to the case where service times are exponentially distributed. This is also reflected in the stability conditions. Incidently, this leads to a full study of the preemptive-restart with resampling last come first served case without negative customers. Finally, approaches to solving the Fredholm integral equation of the first kind which arises, for instance, in the first case are considered as well as an alternative iterative solution method.

scholarly journals Research of Register Pressure Aware Loop Unrolling Optimizations for Compiler

2018 ◽  
Vol 228 ◽  
pp. 03008
Author(s):  
Xuehua Liu ◽  
Liping Ding ◽  
Yanfeng Li ◽  
Guangxuan Chen ◽  
Jin Du
Keyword(s):  
Finite Number ◽  
Infinite Number ◽  
Performance Degradation ◽  
Transformation Process ◽  
Fine Grained ◽  
Loop Unrolling ◽  
Average Improvement ◽  
Register Pressure ◽  
Linpack Benchmark ◽  
Loop Optimizations

Register pressure problem has been a known problem for compiler because of the mismatch between the infinite number of pseudo registers and the finite number of hard registers. Too heavy register pressure may results in register spilling and then leads to performance degradation. There are a lot of optimizations, especially loop optimizations suffer from register spilling in compiler. In order to fight register pressure and therefore improve the effectiveness of compiler, this research takes the register pressure into account to improve loop unrolling optimization during the transformation process. In addition, a register pressure aware transformation is able to reduce the performance overhead of some fine-grained randomization transformations which can be used to defend against ROP attacks. Experiments showed a peak improvement of about 3.6% and an average improvement of about 1% for SPEC CPU 2006 benchmarks and a peak improvement of about 3% and an average improvement of about 1% for the LINPACK benchmark.

Special Topics in Queueing Theory

2018 ◽  
pp. 212-254
Keyword(s):  
Queueing Theory ◽  
Finite Population ◽  
Service Process ◽  
Batch Service ◽  
Priority Level ◽  
Priority System ◽  
Priority Systems ◽  
The One ◽  
Number Of Customers

Topics covered in Chapter 7 are priority systems with preemptive or non-preemptive system, systems with N classes of customers, customers in groups: bulk arrivals, batch service, balking and reneging, and finite population. In a priority system, it is assumed that there are 1, 2, 3, …, N different classes or types of customers, where Type 1 customers are the most important while class N ones are the least important. When a server is available to serve a customer from the queue, the one with the highest priority level will go to the server to start their service process. In batch service, before starting the service process, a group or batch needs to be formed with a certain number of customers.

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