Three Node Tandem Communication Network Model with Dynamic Bandwidth Allocation and Non Homogeneous Poisson Arrivals (original) (raw)
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International Journal of Computer Applications, 2014
Tandem Queues are widely used in mathematical modeling of random processes describing the operation of Manufacturing systems , supply chains, Computer and telecommunication networks. In many of the communication systems the arrivals are time dependent and can be characterized by a non homogeneous Poisson process. In this paper we developed and analyzed three nodes connected in tandem Queue with feedback for the first and second nodes assuming that arrivals follow non homogeneous Poisson process. Using the difference-differential equations and a probability generating function of the number of packets in the buffer connected to the transmitter the System is analyzed. The System performance is analysed by deriving expressions for the performance measures of the network like mean content of the buffers, mean delays through put, transmitter utilization with mathematical illustrations. The sensitivity analysis of the model reveals that the non homogeneous Poisson arrivals and dynamic bandwidth allocation strategy can reduce burstness in buffer and improve quality of service.
International journal of computer applications, 2014
Queuing models play a dominant role in many communication systems for optimum utilization of the resources. In this paper, we develop and analyze a two node tandem communication network model with feedback for the first node, with an assumption that the arrivals follow homogeneous Poisson process. In this model, the service rates of each transmitter depends on the number of services in the buffer connected it. The model is analyzed using the difference-differential equations and a probability generating function of the number of packets in the buffer. Expressions are derived for performance measures including average number of packets in each buffer, the probability of emptiness of the network, the mean delay in the buffer and in the network, the throughput of the transmitters, and the variance of the number of packets in the buffer.
Three Node Tandem Communication Network Model with Duane Arrivals And Dynamic Bandwidth Allocation
IJCSIS, 2018
Conducting the laboratory experiments is time consuming and complicated. The mathematical models for the innovative communication networks is a prerequisite for designing and analyzing the communication networks. In Communication Systems such as Telecommunications, Satellite Communications, Computer Communications, the arrival of packets to the buffers are time dependent and bursty. This paper addresses a three node communication network model with time dependent arrivals having dynamic band width allocation. The time dependent arrivals are characterized by Duane process. It is further assumed that the inter transmission times in all nodes follow Exponential distribution. The joint probability of the number of packets in each buffer is derived. The explicit expressions for the system characteristics are obtained. The Sensitivity analysis of the model revealed that the time dependent arrival process can predict the performance measures more close to the reality. The DBA strategy can reduce the conjunction in buffer and avoid burstness. This model can also include some of the earlier model as particular cases. Keywords: Duane Process, Three node Tandem Communication networks, Performance Evaluation, Sensitivity Analysis.
INTERNATIONAL JOURNAL OF COMPUTERS & TECHNOLOGY, 2014
In this paper, we develop a two node tandem communication network model with dynamic bandwidth allocation and feedback for the first node. In most of the communication systems, the arrivals of packets follow Non-Homogeneous and arrival rate is time dependent. In this model, the transmission rate of each transmitter depends on the number of packets in the buffer connected it. The transmission rates at each transmitter are adjusted depending upon the content of the buffer connected to it. The packets transmitted through the first transmitter may be forwarded to the buffer connected to the second transmitter or returned back to the first buffer with certain probabilities. Using the difference-differential equations the performance measures including average number of packets in each buffer, the probability of emptiness of the network, the average waiting time in the buffer and in the network, the throughput of the transmitters, and the variance of the number of packets in the buffer ar...
Performance Analysis of A Two Node Tandem Communication Network with Feedback
A Communication Network needs optimal utilization of resources such as bandwidth, routers, transmitters, etc. In this paper we have developed and analyzed a communication network with two nodes with feedback. In this network, the arrival of packets characterized by homogeneous Poisson process and transmission of both the transmitters is characterized by Poisson process. Dynamic bandwidth allocation policy is proposed by adjusting the transmission rate at every transmitter just before transmission of each packet. The model is evaluated using the difference-differential equations and a probability generating function of the number of packets in the buffer. Through mathematical modeling, performance measures including average number of packets in each buffer, the probability of emptiness of the network, the average waiting time in the buffer and in the network, the throughput of the transmitters, utilization and the variance of the number of packets in the buffer are derived under tran...
Queueing models for the analysis of communication systems
Top, 2014
Queueing models can be used to model and analyze the performance of various subsystems in telecommunication networks; for instance, to estimate the packet loss and packet delay in network routers. Since time is usually synchronized, discretetime models come natural. We start this paper with a review of suitable discrete-time queueing models for communication systems. We pay special attention to two important characteristics of communication systems. First, traffic usually arrives in bursts, making the classic modeling of the arrival streams by Poisson processes inadequate and requiring the use of more advanced correlated arrival models. Second, different applications have different quality-of-service requirements (packet loss, packet delay, jitter, etc.). Consequently, the common first-come-first-served (FCFS) scheduling is not satisfactory and more elaborate scheduling disciplines are required. Both properties make common memoryless queueing models (M/M/1-type models) inadequate. After the review, we therefore concentrate on a discrete-time queueing analysis with two traffic classes, heterogeneous train arrivals and a priority scheduling discipline, as an example analysis where both time correlation and heterogeneity in the arrival This invited paper is discussed in the comments available
Analytical modelling of networks in multicomputer systems under bursty and batch arrival traffic
The Journal of Supercomputing, 2010
The hypercube and torus are two important message-passing network architectures of high-performance multicomputers. Analytical models of multicomputer networks under the non-bursty Poisson traffic have been widely reported. Motivated by the convincing evidence of bursty and batch arrival nature of traffic generated by many real-world parallel applications in high-performance computing environments, we develop a new and concise analytical model in this paper for hypercube and torus networks in the presence of batch message arrivals modelled by the compound Poisson process with geometrically distributed batch sizes. The average degree of virtual channel multiplexing is derived by employing a Markov chain which can capture the batch arrival nature. An attractive advantage of the model is its constant computation complexity independent of the network size. The accuracy of the analytical performance results is validated against those obtained from simulation experiments of an actual system.
2017
Communication network models are important for design, development and monitoring the communication systems. Recently much emphasis is given for communication network with time dependent arrivals. In many practical situations the output of one transmitter is an input to other. In this transmission, in some system the packet after getting transmission first node may or may not get into second buffer. This type of transmission is called phase type transmission. In this paper, we develop and analyse a three node communication network model with assumption that the arrivals to each buffer are time dependent and follows a non homogeneous poisson process. The transmission at every node is dependent on content of buffer and its rate changes dynamically using difference differential equation. The joint probability generating function is derived. The system performance measures are enhanced. The sensitivity analysis of model reveals that the time dependent and DBA has significant influence o...
1994
In communication networks the transmission of information packets is usually not an instantaneous process, but requires temporary storage of the packets in buffers at various points in the network. The use of such buffers makes it possible, for example, to apply multiplexers and concentrators to the collection of different data streams to share a single transmission channel, thus improving resource utilization tremendously. Buffers are also used to regulate bursty and unstable traffic and hold low priority packets preempted by higher priority data streams. Thus buffers are some of the most important components of a network and are essential tools in providing a better and more efficient transmission of information packets to their destinations. Many factors can make it very difficult, however, to determine the actual buffer sizes needed and avoid costly loss of packets due to buffer overflow. Although buffers have increased in size and have become less expensive in recent years, buffer overflow considerations are still very much of interest today in systems where failures can cause iii long interruptions of transmission or where traffic intensities and transmission rates vary enormously. Some of the factors that may influence the buffer size requirements are, for example, that the arrival streams of data packets at the buffers may not only be very bursty and irregular but may even be interrupted from time to time. At the same time, the transmission lines serving the buffers may not always be permanently available; arriving packets must then be stored in buffers until the service interruptions are over and transmission of the information packets can continue. Such server interruptions could be built-in as in priority systems where high priority packets may interrupt the transmission of lower priority packets, and as in integrated voice-data systems which only transmit data packets during speech gaps. These interruptions could also be caused by unreliable transmission lines, noise or other types of failure. Arrival interruptions occur when the arrivals at a buffer are traffic streams from another buffer overflow situation and in packet switching networks when arrivals are suddenly generated for another destination and arrive at a different buffer. Arrival interruptions can also occur if failures cause the interruptions of the input traffic. Since both types of interruptions are very likely and commonplace, performance measures of a buffer system with iv both random arrival and server interruptions are of great interest and importance. Hence, both interruptions need further investigation. Rationale A discrete-time queueing model is a viable tool to obtain performance predictions and descriptions of the buffer behavior, traffic flow and delay of a system. Compared to continuous-time models, discrete-time systems have not been as thoroughly researched in the past. Discrete-time systems feature synchronous and time-slotted service, which makes them applicable to BISDN (Broadband Integrated Services Digital Network) systems, or any other types of time-slotted packet switching systems and synchronous communication systems. In any communication system both server and arrival interruptions can occur and can have many different causes and applications. A data stream from an overflowing buffer, for instance, has always an interrupted and irregular traffic flow, since a buffer's capacity will not be constantly and continuously exceeded. Server interruptions for low priority data packets due to the arrival of higher priority information units are also a very common situation. A model with both server and arrival interruptions allows for great fluctuations and variations in the arrival stream v or service and therefore gives valuable insight in optimum buffer size requirements and processing delay whenever transmissions deviate from a regular and continuous flow. Whenever both types of interruptions occur in the same system, they need not be due to the same single incident, but can occur independently from each other and without any correlation, since different events can be responsible for the interruptions. A discrete-time buffer system with both interruptions in the arrival stream as well as in the output process can be modeled as a single server queue, where the input and output channel are each interrupted by (independent and uncorrelated) random switches which will block arrivals or interrupt service when open. The interruption processes themselves can then be described as sequences of independent and identically distributed Bernoulli random variables. The application of this Bernoulli model implies that the availability or interruption of an input or output channel during a discrete time slot is completely independent of the state of the channel in the previous slot and interruptions occur independently from one slot to the other without any slot-to-slot correlation. This assumption is especially justified when interruptions are due to failures or noise in the channel, as well as in the case of server interruptions when high and low priority data messages arrive independently from each other and the state vi of the system in one discrete time unit has no bearing on the state of the model in the following interval. Another feature of this single server queueing model with independent Bernoulli interruptions is that the intervals during which the arrivals or the service are available or blocked are then geometrically distributed-a distribution that is widely applicable in discrete-time systems since it is the only memoryless discrete distribution, i.e., as mentioned above, the discrete random variable is independent of its past history in previous slots. An arrival stream with long interruptions as found in the processing of overflow traffic from an independent source can be modeled through an Interrupted Poisson Process with geometrically distributed interarrival times-since in a discrete-time model, events can only take place at regularly spaced points in time. At the same time the output process of the server during a noninterrupted interval can be modeled as constant, with the length of a time slot necessary to transmit exactly one fixed-length packet from the buffer. Interesting performance measures of this system include the mean time delay of the data packets and the number of data packets in the system at various time points as the model is subjected to these random arrival and server interruptions, and their investigation will provide improved vii estimations concerning buffer size requirements and time delay that apply even in failure situations. viii CONTENTS PREFACE iii Purpose iii Rationale v LIST OF ILLUSTRATIONS xi