China
Africa
Explore chapters and articles related to this topic
Introduction to Algorithms and Data Structures
Published in Sriraman Sridharan, R. Balakrishnan, Foundations of Discrete Mathematics with Algorithms and Programming, 2019
Sriraman Sridharan, R. Balakrishnan
We shall now study another access restricted data structure called “queue.” A common example of a queue is persons waiting at the booking counter in a railway station. A queue is a special kind of list in which the operation of insertion is performed at one end of the list called the “end” or “rear” or “tail” of the list, and the operation of deletion is performed at the other end of the list, called the “front” or “head” of the list. The elementary operations associated with a queue are the following: Initializing an empty queue, finding the element at the head of the queue, insertion of a new element at the end of the queue (enqueue), deletion of the element at the front of the queue (dequeue), etc. As for stacks, we study two queue implementations: 1. implementation by linked list 2. Implementation by circular array.
Parallel Simulation of DEVS and Cell-DEVS Models in PCD ++
Published in Gabriel A. Wainer, Pieter J. Mosterman, Discrete-Event Modeling and Simulation, 2018
Gabriel A. Wainer, Qi Liu, Shafagh Jafer
The volatile input queue has two appealing properties that allow us to reduce the memory footprint and the cost of queue operations significantly: Events in the queue are discarded and their memory reclaimed immediately after execution (reducing the memory footprint of the system).Events in the queue always have the same time stamp. They are inserted into the queue as the simulation moves into each phase of a WCTS, and removed as the execution proceeds. At the end of each phase, the queue becomes empty. This means that a simple FIFO queue suffices, and queue operations can be performed efficiently in O(1) time.
Introduction
Published in Randall L. Eubank, Ana Kupresanin, Statistical Computing in C++ and R, 2011
Randall L. Eubank, Ana Kupresanin
The vector class is an implementation of a dynamic array ADT. The name deque stands for “double-ended queue”. Thus, as might be expected, objects can be inserted or removed from either end of this container. The random access that deque provides to its contents as well as other features make it a dynamic array rather than a queue in the usual first-in firstout sense of the term. The list container is a doubly-linked list class. The map container is a dictionary where the objects in the container have both a key and a data component. For map the keys must be unique while multimap allows for repeated keys. The set containers are simplified versions of map containers where objects have a single member that serves as both the key and data component.
Analysis of Customers’ Impatience in a Repairable Retrial Queue under Postponed Preventive Actions
Published in American Journal of Mathematical and Management Sciences, 2019
Amar Aissani, Ferhat Lounis, Djamel Hamadouche, Samira Taleb
Queueing theory is concerned with the mathematical modeling and analysis of systems that provide service to random demands (Bhat, 2008; Choudhury, 2008; Choudhury & Borthakur, 2007; Cooper, 1981; Daigle, 2005; Gnedenko & Kovalenko, 1989; Hieghem, 2006; Keijzer, Mullenders, van Reeken, & Kleijnen, 1981; Kleinrock, 1975; Medhi, 2002; Parthasarathy & Vasudevant, 2010; Yang, Kim, Park, & Lim, 2016). Retrial queues occupy an intermediate situation between an Erlang model with loss and classical model with wait, which constitute their limiting models in the case of low and high retrial rates. The study of such queues is motivated by many applications, particularly in Switching networks, wireless sensor networks, and call centers (Anisimov, 2008; Artalejo & Gómez-Corral, 2008; Do, Takahashi, Yue, & Nguyen, 2016; Gómez-Corral & Phung-Duc, 2016; Medvedev, 1994).
A hybrid simulation-based assessment framework of smart manufacturing systems
Published in International Journal of Computer Integrated Manufacturing, 2018
Khalid Nagadi, Luis Rabelo, Mohammed Basingab, Alfonso T. Sarmiento, Albert Jones, Ahmad Rahal
In this model, machines are modelled autonomous agents and queues are modelled as part of the discrete-event simulation. In this model, agents control the queues by (1) communicating with them and (2) ensuring a smooth flow. In building this system-level model, we made several assumptions. They include as follows: Raw material is always available for production.Transport times are negligible.No constraints on adding new machines.Queue discipline is FIFO (first in first out).Quality control is embedded in the system.On behaviour metric for all the machines.
On the joint distribution of an infinite-buffer discrete-time batch-size-dependent service queue with single and multiple vacations
Published in Quality Technology & Quantitative Management, 2021
Nilanjan Nandy, Sourav Pradhan
In several real-life circumstances, it is observed that after the service completion of a batch, the server may be unavailable for a random period of time if the server finds less number of customers than the minimum threshold. The server may utilize this time in order to carry out some additional work. These types of queues are known as vacation queues which have potential applications in polling protocols frequently used in high-speed telecommunication networks, designing of local area networks, processor schedules in computer and switching systems, shared resources maintenance, manufacturing system with server breakdown, etc. The literature clearly exhibits the extensive studies on vacation queues, for example, see Doshi (1986), Lee et al. (1994), Gupta and Sikdar (2006), Banik et al. (2006), Tadj et al. (2006), Ke (2007), Tadj and Ke (2008), Vijayashree and Anjuka (2018), and Ke et al. (2019) and the references therein. Ke et al. (2010) provided a brief and concise survey on the recent developments of vacation queues with different vacation rules such as single/multiple vacations, Bernoulli vacation, multiple adaptive vacations, working vacation, etc. They have also provided some literatures on multi-server vacation models. Based on the supplementary variable technique (SVT) and the difference equation method Barbhuiya and Gupta (2020) analyzed an infinite buffer batch arrival queue with threshold policy in which as soon as the system becomes empty, the server enters into an idle phase. The service will be resumed when the number of customers in the queue reaches or more. They have obtained the probability distribution of the system-size and waiting time in the steady-state.