On-off Traffic Model Research Articles

Traffic modelling challenges on 10 Gbit/s links using netmap platform

Network devices are using a growing number of 10 Gbit/s links. Such throughput upgrade imposes new challenges on creating high-speed packet generators that can provide real network conditions. Traffic generators implemented as software solutions have challenges in achieving a required performance, as they are commonly using a kernel network stack for packet I/O. We describe different techniques for implementing the Poisson and on-off traffic model in a software-based traffic generator that is using netmap API as fast packet I/O.

Traffic-Aware Green Cognitive Radio

Cognitive Radio Network (CRN) has emerged as an effective solution to the spectrum under-utilization problem, by providing secondary users (SUs) an opportunistic access to the unoccupied frequency bands of primary users (PUs). Most of the current research on CRN are based on the assumption that the SU always has a large amount of data to transmit. This leads to the objective of SU throughput maximization with a constraint on the allowable interference to the PU. However, in many of the practical scenarios, the data arrival process of the SU closely follows an ON–OFF traffic model, and thus the usual throughput optimization framework may no longer be suitable. In this paper, we propose an intelligent data scheduling strategy which minimizes the average transmission power of the SU while maintaining the transmission delay to be sufficiently small. The data scheduling problem has been formulated as a finite horizon Markov Decision Process (MDP) with an appropriate cost function. Dynamic programming approach has been adopted to arrive at an optimal solution. Our findings show that the average transmitted power for our proposed approach can be as small as 36.5% of the power required for usual throughput maximization technique with insignificant increase in average delay.

Dual Threshold Scheduling for VoIP Traffic on Downlink of WiMAX Networks

Previous downlink scheduling algorithms of WiMAX (Worldwide Interoperability for Microwave Access), like DRR (Deficit Round-Robin) and WRR (Weighted Round-Robin), usually reserve minimum rate to each type of traffic and cannot consider the status of queue length of each connection, thus making it unsuitable for VoIP on-off traffic model. One well-designed scheduling algorithm is expected to coordinate QoS-related functional entities in WiMAX architecture. We address an efficient downlink scheduling algorithm, which allocate the bandwidth based on dual threshold of queue length. We compare the proposed scheme with DRR and WRR by estimating the system performance such as average delay, loss rate and throughput under several traffic scenario and system parameters value.

The Economic Implications of Burstiness of Cell Arrival Processes in Network Design

Burstiness has a great influence on network architectures as well as network dimensioning. Hence, the knowledge of the different traffic models goes a long way in helping the network designer to make good choices concerning end buffer parameters, protocol selection as well as functional specifications, and QoS parameters. This paper takes a comparison of three traffic models- the Interrupted Poisson Process, the Interrupted Bernuolli Process and the ON-OFF traffic model with constant distribution. The comparison is based on buffer occupancy, cell delay and utilization; with the aim of investigating the economic implications of using these traffic models. The results of the simulation show that the ON-OFF (Constant distribution) and the IPP have similar impacts which are far better than that of the IBP.

Exponential On-Off Traffic Models for Quality of Experience and Quality of Service Assessment

Article Exponential On-Off Traffic Models for Quality of Experience and Quality of Service Assessment was published on December 1, 2014 in the journal PIK - Praxis der Informationsverarbeitung und Kommunikation (volume 37, issue 4).

Modeling and Analysis of Bandwidth Allocation in IEEE 802.16 MAC: A Stochastic Reward Net Approach

In this paper, we present a stochastic reward net (SRN) approach to analyse the performance of IEEE 802.16 MAC with multiple traffic classes. The SRN model captures the quality of service requirements of the traffic classes. The model also takes into account pre-emption, priority and timeout characteristics associated with the traffic classes under consideration. The performance of the system is evaluated in terms of mean delay and normalized throughput considering the on-off traffic model. Our analytical model is validated by simulations.

An ON-OFF Multi-Rate Loss Model of Finite Sources

Bursty traffic is dominant in modem communication networks and keeps the call-level QoS assessment an open issue. ON-OFF traffic models are commonly used to describe bursty traffic. We propose an ON-OFF traffic model of a single link which accommodates service-classes of finite population (f-ON-OFF). Calls compete for the available link bandwidth under the complete sharing policy. Accepted calls enter the system via state ON and then may alternate between ON-OFF states. When a call is transferred to state OFF it releases the bandwidth held in state ON, while when a call tries to return to state ON, it re-requests its bandwidth. If it is available a new ON-period (burst) begins; otherwise the call remains in state OFF (burst blocking). We prove that the proposed f-ON-OFF model has a product form solution, and we provide an accurate recursive formula for the call blocking probabilities calculation. For the burst blocking probabilities calculation we propose an approximate but robust formula. In addition, we show the relation between the f-ON-OFF model and other call-level loss models. Furthermore, we generalize the f-ON-OFF model to include service-classes of both finite and infinite population. Simulation results validate our analytical methodology.

Importance Sampling for the Estimation of Buffer Overflow Probabilities via Trace-Driven Simulations

We develop an importance sampling technique that can be used to speed up the simulation of a model of a buffered communication multiplexer fed by a large number of independent sources. The sources generate traffic according to a periodic function with a random phase. This traffic model accommodates a wide range of situations of practical interest, including ON-OFF periodic traffic models and sequences of bit rates generated by actual variable bit rate sources, such as MPEG video compressors. The simulation seeks to obtain estimates for the buffer overflow probability that in most cases of interest is very small. We use a large deviations result to devise the change of measure used in the importance sampling technique and demonstrate through numerical results that this change of measure leads to a dramatic reduction in the required simulation time over direct Monte Carlo simulation. Possible practical applications include short-term network resource planning and even real-time call admission control.

Analysis of completion of call with on-off data source in wireless networks

In wireless network, call completion probability accounts for users' satisfaction since the admitted ongoing call may be interrupted during hand-off process or even stay in the same cell when dynamically allocating resource to calls because of the loss of resource. We focus on the relationship between call's completion probability and these interruptions and develop an analytical relationship model for homogeneous cellular networks based on probability analysis. Then assuming call's data source is modeled by on-off traffic model, a two dimensional Markov process is established to compute these blocking and dropping probabilities for call's completion probability. The impacts of different new call arrival rate, call's traffic characteristic, user's mobility, call's holding time and call's admission threshold on call's completion are evaluated and compared through numerical examples. These results show that call's completion reaches its maximum value if making no difference between hand-off call and new call in the case of light traffic load. But some resource should be reserved for the hand-off call in high traffic scenario. The analytical model provides a basis for helping to set the call admission threshold.

HAP

Applications to be supported on broadband networks exhibit a wide range of traffic statistics and many of them are sensitive to delay and loss violations. To accurately estimate admissible workload and bandwidth requirement, a detailed traffic model, HAP (Hierarchical Arrival Process) is proposed in this paper. Packets generated from HAP are modulated by processes at user, application, and message levels. This model is a generalization of on-off traffic models and is shown to be equivalent to a special class of MMPP (Markov Modulated Poisson Process). Three algorithmic methods along with simulations are applied to evaluate the queueing performance under HAP traffic. Delay under HAP traffic can be well over tens of times higher than Poisson traffic, depending on parameters and load. Congestion may persist for minutes. HAP's dramatic short-term behavior explains the occasional congestion in the real networks. Conventional traffic models, however, do not exhibit this behavior. With these results, we give implications for broadband network control.

HAP: A New Model for Packet Arrivals

Applications to be supported on broadband networks exhibit a wide range of traffic statistics and many of them are sensitive to delay and loss violations. To accurately estimate admissible workload and bandwidth requirement, a detailed traffic model, HAP (Hierarchical Arrival Process) is proposed in this paper. Packets generated from HAP are modulated by processes at user, application, and message levels. This model is a generalization of ON-OFF traffic models and is shown to be equivalent to a special class of MMPP (Markov Modulated Poisson Process). Three algorithmic methods along with simulations are applied to evaluate the queueing performance under H4P traffic. Delay under HAP traffic can be well over tens of times higher than Poisson traffic, depending on parameters and load. Congestion may persist for minutes. HAP's dramatic short-term behavior explains the occasional congestion in the real networks. Conventional traffic models, however, do not exhibit this behavior. With these results, we give implications for broadband network control.