The crux of this paper is to demonstrate how it is possible to model systems of vehicular trafic by means of complex queuing network models. The objects comprising the library that we define in this work all follow the approach whereby they are composed of one or more queuing networks of service systems that are traversed by customers (vehicles).
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This study is included in a research programme developed by the authors at the University of Studies in Camerino for the construction of traffic flow simulators in computer and telecommunication networks [1–4]. The article contains the definition of a library of object types whose architecture is based on the queue networks, for a simulation of the VOIP traffic in P2P networks. Basing on this library, we simulate the traffic in a P2P network that is locally implemented with three different technology types: 1. Fast Ethernet, 2. Wireless, 3. ADSL2+. In this context, we simulate traffic flows due to file-sharing applications in the network and due to voice communications through the VOIP technology. Thus, we evaluate the impact of the VOIP traffic for procedures of file-sharing in a P2P network.
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A technique is introduced for the construction of simulators of telecommunication networks based on the P2P protocol with a decentralized directory. The context of the application concerns P2P networks used both by sharing software and by telecommunication applications, as in VoIP applications. P2P systems have the advantages of boundless scalability and the break-up insensibility of devices, but suffer from heavy traffic of signals and network delays. Therefore, simulation of signal traffic in P2P networks is an important issue. The technique we have developed enables individuation of a generic P2P network's components and their functional characterization. We have worked at this level of description in order to determine the architecture of every component as a model of queues' networks. We have therefore defined a library of new types of objects for the construction of P2P network simulators with the Qnap2.V9 programming language. In this context, we have defined a procedure automatically generating the simulator of an any P2P network. During its execution, the procedure reads data from a file containing a description of the structure of the considered P2P network and values of the characteristic parameters of its components. Results related to the simulation of three configurations of a P2P network are introduced in Section 5 below. They differ according to the technology used to realize the local interconnection networks. The context of the present paper is a research program developed at the University of Camerino in defining specific computer procedures aimed at construction of simulators of telecommunication and computing networks. This technique also enables simulation of the software elaboration phases on computer networks and evaluation of the impact of specific choices concerning the structure of transmission protocols and operation paradigms of software applications [1, 2].
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In this study we build a library of new object types whose architecture is based on models of networks-of-queues to simulate communication networks. We also define a class of procedures to automatically generate a simulator of a generic communication network described by the library's objects.
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In a previous work [Pasini L and Sabatini S 2016 TASK Quart. 20 (1) 9], we described a technique that allows a specific system of urban traffic to be associated to a description file system, called Model.dat. This file contains a list of data objects that are defined in the library [Pasini L and Feliziani S 2013 TASK Quart. 17 (3) 155] and that form the architecture model of a vehicular traffic system. This model turns out to be a network of queuing systems. In this work, we illustrate how we adapted the old procedure to study a new urban traffic system. Moreover, through a new tracking procedure, we illustrate how we developed a graphic simulation able to reinterpret the data from the simulation of the queuing networks model, in order to make it easier to check the effectiveness of the simulator and to have a graphical way to analyze the data.
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